Publications

Publications TU-Biblio

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2020

Prangemeier, T. ; Reich, C. ; Koeppl, H. (2020):
Attention-Based Transformers for Instance Segmentation of Cells in Microstructures.
IEEE International Conference on Bioinformatics and Biomedicine (IEEE BIBM 2020), virtual Conference, 16.-19.12., [Conference item]

Kruk, N. ; Maistrenko, Y. ; Koeppl, H. (2020):
Solitary states in the mean-field limit.
In: Chaos: An Interdisciplinary Journal of Nonlinear Science, 30 (11), American Institute of Physics, ISSN 1054-1500,
DOI: 10.1063/5.0029585,
[Article]

Kar, Sounak ; Rehrmann, Robin ; Mukhopadhyay, Arpan ; Alt, Bastian ; Ciucu, Florin ; Koeppl, Heinz ; Carsten, Binnig ; Rizk, Amr (2020):
On the Throughput Optimization in Large-Scale Batch-Processing Systems.
S. 1:15, 38th International Symposium on Computer Performance, Modeling, Measurements and Evaluation (IFIP 2020), virtual Conference, 02.-06.11., [Conference item]

Alt, B. ; Schultheis, M. ; Koeppl, H. (2020):
POMDPs in Continuous Time and Discrete Spaces.
34th Conference on Neural Information Processing Systems (NeurIPS 2020), virtual Conference, 06.-12.12., [Conference item]

Kruk, N. ; Carrillo, J.A. ; Koeppl, H. (2020):
Traveling bands, clouds and vortices of chiral active matter.
In: Physical Review E, 102 (2), S. 022604. American Physical Society, ISSN 2470-0045,
DOI: 10.1103/PhysRevE.102.022604,
[Article]

Yang, S. ; Koeppl, H. (2020):
The Hawkes Edge Partition Model for Continuous-time Event-based Temporal Networks.
S. 460-469, 36th Conference on Uncertainty in Artificial Intelligence (UAI), virtual Conference, August 03.-06., 2020, ISSN 2640-3498,
[Conference item]

Engelmann, N. ; Linzner, D. ; Koeppl, H. (2020):
Continuous-Time Bayesian Networks with Clocks.
International Conference on Machine Learning 2020, virtual Conference, 12.-18.07., [Conference item]

Sinzger, M. ; Gehri, M. ; Koeppl, H. (2020):
Poisson channel with binary Markov input and average sojourn time constraint.
S. 2873-2878, ISIT'20 - International Symposium on Information Theory, virtual online conference, 21.-26. June 2020, ISBN 978-1-7281-6433-5,
DOI: 10.1109/ISIT44484.2020.9174360,
[Conference item]

Prangemeier, T. ; Lehr, F. -X. ; Schoeman, R.M. ; Koeppl, H. (2020):
Microfluidic platforms for the dynamic characterisation of synthetic circuitry.
In: Current Opinion in Biotechnology, 63, S. 167-176. Elsevier, ISSN 0958-1669,
DOI: 10.1016/j.copbio.2020.02.002,
[Article]

KhudaBukhsh, W. R. ; Kar, S. ; Alt, B. ; Rizk, A. ; Koeppl, H. (2020):
Generalized Cost-Based Job Scheduling in Very Large Heterogenous Cluster Systems.
In: IEEE Transactions on Parallel and Distributed Systems (TPDS), 31 (11), S. 2594-2604. IEEE, ISSN 1045-9219, e-ISSN 1045-9219,
DOI: 10.1109/TPDS.2020.2997771,
[Article]

Linzner, D. ; Heinz, K. (2020):
A Variational Perturbative Approach to Planning in Graph-based Markov Decision Processes.
AAAI-20 - Thirty-Fourth AAAI Conference on Artificial Intelligence, New York, USA, February 7-12, 2020, [Conference item]

Kumar, S. ; Lun, X.-K. ; Bodenmiller, B. ; Rodriguez Martinez, M. ; Koeppl, H. (2020):
Stabilized Reconstruction of Signaling Networks from Single-Cell Cue-Response Data.
In: Scientific reports, 10, S. 1233. Springer Nature, ISSN 2045-2322,
DOI: 10.1038/s41598-019-56444-5,
[Article]

Yang, Sikun (2020):
Non-parametric Bayesian Latent Factor Models for Network Reconstruction.
Darmstadt, Technische Universität,
DOI: 10.25534/tuprints-00009695,
[PhD thesis]

Bronstein, Leo (2020):
Approximation and Model Reduction for the Stochastic Kinetics of Reaction Networks.
Darmstadt, Technische Universität,
DOI: 10.25534/tuprints-00013433,
[PhD thesis]

Kruk, N. ; Carrillo, J.A. ; Koeppl, H. (2020):
A Finite Volume Method for Continuum Limit Equations of Nonlocally Interacting Active Chiral Particles.
In: Journal of Computational Physics, Elsevier, [Article]

Prangemeier, T. ; Wildner, C. ; Francani, A. O. ; Reich, C. ; Koeppl, H. (2020):
Multiclass Yeast Segmentation in Microstructured Environments with Deep Learning.
IEEE, International Conference on Computational Intelligence in Bioinformatics and Computational Biology, virtual Conference, October 27-29, 2020, [Conference item]

2019

Altintan, D. ; Koeppl, H. (2019):
Hybrid master equation for jump-diffusion approximation of biomolecular reaction networks.
In: BIT Numerical Mathematics, Springer Nature, Netherlands, ISSN 1572-9125,
DOI: 10.1007/s10543-019-00781-4,
[Article]

KhudaBukhsh, W. R. ; Auddy, A. ; Disser, Y. ; Koeppl, H. (2019):
Approximate Lumpability for Markovian Agent-based Models Using Local Symmetries.
56, In: Jounal of Applied Probability, (3), S. 647-671. Cambridge University Press, DOI: 10.1017/jpr.2019.44,
[Article]

Alt, B. ; Šošić, A. ; Koeppl, H. (2019):
Correlation Priors for Reinforcement Learning.
33rd Conference on Neural Information Processing Systems (NeurIPS 2019), Vancouver, Kanada, 09.12.-13.12.2019, [Conference item]

Lehr, François-Xavier ; Hanst, Maleen ; Vogel, Marc ; Kremer, Jennifer ; Göringer, H. Ulrich ; Suess, Beatrix ; Koeppl, Heinz (2019):
Cell-free prototyping of AND-logic gates based on heterogeneous RNA activators.
8, In: ACS Synthetic Biology, (9), S. 2163-2173. ACS Publications, ISSN 2161-5063,
DOI: 10.1021/acssynbio.9b00238,
[Article]

Linzner, D. ; Schmidt, M. ; Koeppl, H. (2019):
Scalable Structure Learning of Continuous-Time Bayesian Networks from Incomplete Data.
33rd Conference on Neural Information Processing Systems (NeurIPS 2019), Vancouver, Canada, 09.-13.12., [Conference item]

Wildner, Christian ; Koeppl, Heinz PMLR (Urheber) (2019):
Moment-Based Variational Inference for Markov Jump Processes.
In: PMLR, 97, In: Proceedings of Machine Learning Research, S. 6766-6775,
International Conference on Machine Learning, Long Beach, California, USA, June 9-15, 2019, ISSN 2640-3498,
[Conference item]

Alt, Bastian ; Ballard, Trevor ; Steinmetz, Ralf ; Koeppl, Heinz ; Rizk, Amr (2019):
CBA: Contextual Quality Adaptation for Adaptive Bitrate Video Streaming.
S. 1000-1008, IEEE, IEEE Conference on Computer Communications (INFOCOM 2019), Paris, France, 29.04.-02.05., ISBN 978-1-7281-0516-1,
DOI: 10.1109/INFOCOM.2019.8737418,
[Conference item]

KhudaBukhsh, W. R. ; Kar, S. ; Koeppl, H. ; Rizk, A. (2019):
Provisioning and Performance Evaluation of Parallel Systems with Output Synchronization.
In: ACM Transactions on Modeling and Performance Evaluation of Computing Systems (TOMPECS), 4 (1), S. Art. 6. ISSN 2376-3639,
DOI: 10.1145/3300142,
[Article]

Kang, H.-W. ; Khuda Bukhsh, W.R. ; Koeppl, H. ; Rempala, G.A. (2019):
Quasi-steady-state approximations derived from the stochastic model of enzyme kinetics.
In: Bulletin of Mathematical Biology, S. 1-34. Springer US, ISSN 0092-8240,
DOI: 10.1007/s11538-019-00574-4,
[Article]

Alt, Bastian ; Weckesser, Markus ; Becker, Christian ; Hollick, Matthias ; Kar, Sounak ; Klein, Anja ; Klose, Robin ; Kluge, Roland ; Koeppl, Heinz ; KhudaBukhsh, Wasiur R. ; Luthra, Manisha ; Mousavi, Mahdi ; Mühlhäuser, Max ; Pfannemüller, Martin ; Rizk, Amr ; Schürr, Andy ; Steinmetz, Ralf (2019):
Transitions: A Protocol-Independent View of the Future Internet.
In: Proceedings of the IEEE, 107 (4), S. 835-846. ISSN 0018-9219,
DOI: 10.1109/JPROC.2019.2895964,
[Article]

Falk, J. ; Bronstein, L. ; Hanst, M. ; Drossel, B. ; Koeppl, H. (2019):
Context in Synthetic Biology: Memory Effects of Environments with Mono-molecular Reactions.
150, In: The Journal of Chemical Physics, (2), American Institute of Physics, ISSN 0021-9606,
DOI: 10.1063/1.5053816,
[Article]

Hüttenrauch, M. ; Šošić, A. ; Neumann, G. (2019):
Deep Reinforcement Learning for Swarm Systems.
20, In: Journal of Machine Learning Research, (54), S. 1-31. [Article]

2018

Linzner, D. ; Koeppl, H. (2018):
Cluster Variational Approximations for Structure Learning of Continuous-Time Bayesian Networks from Incomplete Data.
32. Conference on Neural Information Processing Systems, Montreal, Canada, December 3-8, 2018, [Conference item]

Hofmann, Anja ; Falk, Johannes ; Prangemeier, Tim ; Happel, Dominic ; Köber, Adrian ; Christmann, Andreas ; Koeppl, Heinz ; Kolmar, Harald (2018):
A tightly regulated and adjustable CRISPR-dCas9 based AND gate in yeast.
47, In: Nucleic Acids Research, (1), S. 509-520. Oxford Academic, ISSN 0305-1048,
DOI: 10.1093/nar/gky1191,
[Article]

Yang, S. ; Koeppl, H. (2018):
Collapsed Variational Inference for Nonparametric Bayesian Group Factor Analysis.
IEEE International Conference on Data Mining (ICDM'18), Singapore, 17.-20. November 2018, [Conference item]

Prangemeier, T. ; Wildner, C. ; Hanst, M. ; Köppl, H. (2018):
Maximizing information gain for the characterization of biomolecular circuits.
5th ACM International Conference on Nanoscale Computing and Communication (NANOCOM'18), Reykjavik, Iceland, September 05 - 07, 2018, DOI: 10.1145/3233188.3233217,
[Conference item]

Al-Sayed, S. ; Koeppl, H. (2018):
Network Reconstruction from Time-Course Perturbation Data Using Multivariate Gaussian Processes.
In: IEEE International Workshop on Machine Learning for Signal Processing,
IEEE International Workshop on Machine Learning for Signal Processing, Aalborg, Denmark, 17.-20. September 2018, [Conference item]

Sulaimanov, N. ; Koeppl, H. ; Burdet, F. ; Ibberson, M. ; Pagni, M. ; Kumar, S. (2018):
Inferring gene expression networks with hubs using a degree weighted Lasso approach.
bty716, In: Bioinformatics (Oxford, England), Oxford University Press, ISSN 1367-4803,
DOI: 10.1093/bioinformatics/bty716,
[Article]

Kruk, N. ; Koeppl, H. ; Maistrenko, Y. (2018):
Self-propelled Chimeras.
In: Physical Review E, American Physical Society, ISSN 2470-0045,
[Article]

Yang, S. ; Koeppl, H. (2018):
Dependent Relational Gamma Process Models for Longitudinal Networks.
80, In: Proceedings of Machine Learning Research (PMLR), S. 5547-5556,
Thirty-fifth International Conference on Machine Learning, Stockholm, Denmark, July 10-15, 2018, [Conference item]

Bronstein, L. ; Koeppl, H. (2018):
Marginal process framework: A model reduction tool for Markov jump processes.
E 97, In: Physical Review E, E 97 (062147), American Physical Society, ISSN 2470-0045,
DOI: 10.1103/PhysRevE.97.062147,
[Article]

Šošić, A. ; Zoubir, A. M. ; Koeppl, H. (2018):
A Bayesian Approach to Policy Recognition and State Representation Learning.
In: IEEE Transactions on Pattern Analysis and Machine Intelligence, 40 (6), S. 1295-1308. DOI: 10.1109/TPAMI.2017.2711024,
[Article]

Alt, Bastian ; Messer, Michael ; Roeper, Jochen ; Schneider, Gaby ; Koeppl, Heinz (2018):
Non-Parametric Bayesian Inference for Change Point Detection in Neural Spike Trains.
2018 IEEE Statistical Signal Processing Workshop (SSP 2018), Freiburg im Breisgau, Germany, 10.-13.06., [Conference item]

Šošić, A. ; Zoubir, A. M. ; Koeppl, H. (2018):
Reinforcement Learning in a Continuum of Agents.
12, In: Swarm Intelligence, (1), S. 23-51. DOI: 10.1007/s11721-017-0142-9,
[Article]

Al-Sayed, S. ; Plata-Chaves, J ; Muma, M. ; Moonen, M. ; Zoubir, A. M. (2018):
Node-Specific Diffusion LMS-Based Distributed Detection Over Adaptive Networks.
66, In: IEEE Transactions on Signal Processing, (3), S. 682-697. ISSN 1053-587X,
[Article]

Bronstein, L. ; Koeppl, H. (2018):
A variational approach to moment-closure approximations for the kinetics of biomolecular reaction networks.
148, In: The Journal of Chemical Physics, (1), American Institute of Physics (AIP), ISSN 00219606,
DOI: 10.1063/1.5003892,
[Article]

KhudaBukhsh, Wasiur R. ; Alt, Bastian ; Kar, Sounak ; Rizk, Amr ; Koeppl, Heinz (2018):
Collaborative Uploading in Heterogeneous Networks: Optimal and Adaptive Strategies.
INFOCOM 2018 - IEEE Conference on Computer Communications, Honolulu, USA, 16.-19.04., DOI: 10.1109/INFOCOM.2018.8486310,
[Conference item]

KhudaBukhsh, Wasiur Rahman (2018):
Model reductions for queueing and agent-based systems with applications in communication networks.
Darmstadt, Technische Universität,
[PhD thesis]

Yang, S. ; Koeppl, H. (2018):
A Poisson Gamma Probabilistic Model for Latent Node-group Memberships in Dynamic Networks.
AAAI 2018, Association for the Advancement of Artificial Intelligence, New Orleans, 2018, [Conference item]

Šošić, A. ; Rueckert, E. ; Peters, J. ; Zoubir, A. M. ; Koeppl, H. (2018):
Inverse Reinforcement Learning via Nonparametric Spatio-Temporal Subgoal Modeling.
19, In: Journal of Machine Learning Research, (69), S. 1-45. [Article]

Šošić, A. ; Zoubir, A. M. ; Koeppl, H. (2018):
Inverse Reinforcement Learning via Nonparametric Subgoal Modeling.
In: AAAI Spring Symposium on Data-Efficient Reinforcement Learning, [Conference item]

2017

Al-Sayed, S. ; Zoubir, A. M. ; Sayed, A. H. (2017):
Robust Distributed Estimation by Networked Agents.
65, In: IEEE Transactions on Signal Processing, (15), S. 3909-3921. ISSN 1941-0476,
[Article]

KhudaBukhsh, W. R. ; Rizk, A. ; Froemmgen, A. ; Koeppl, H. (2017):
Optimizing Stochastic Scheduling in Fork-Join Queueing Models: Bounds and Applications.
In: Technical Program of IEEE INFOCOM 2017, IEEE, [Article]

Ruess, J. ; Koeppl, H. ; Zechner, C. (2017):
Sensitivity estimation for stochastic models of biochemical reaction networks in the presence of extrinsic variability.
146, In: The Journal of Chemical Physics, (124122), AIP, [Article]

Machkour, J. ; Alt, B. ; Muma, M. ; Zoubir, A. M. (2017):
The Outlier-Corrected-Data-Adaptive Lasso: A New Robust Estimator for the Independent Contamination Model.
S. 1699-1703, European Signal Processing Conference 2017 (EUSIPCO 2017), Kos, Greece, 28.08.-02.09., DOI: 10.23919/EUSIPCO.2017.8081489,
[Conference item]

Bronstein, L. ; Diemer, J. ; Koeppl, H. ; Schneider, C. ; Suess, Beatrix (2017):
ROC'n'Ribo: Characterizing a riboswitching expression system by modeling single-cell data.
In: ACS Synthetic Biology, (7), S. 1211-1224. ACS, ISSN 2161-5063,
[Article]

Sulaimanov, N. ; Klose, M. ; Busch, H. ; Boerries, M. (2017):
Understanding the mTOR signaling pathway via mathematical modeling.
9, In: WIREs Systems Biology and Medicine, (4), Wiley, [Article]

Šošić, A. ; KhudaBukhsh, W. R. ; Zoubir, A. M. ; Koeppl, H. (2017):
Inverse Reinforcement Learning in Swarm Systems.
In: AAMAS Workshop on Transfer in Reinforcement Learning, [Conference item]

Šošić, A. ; KhudaBukhsh, W. R. ; Zoubir, A. M. ; Koeppl, H. (2017):
Inverse Reinforcement Learning in Swarm Systems (Best Paper Award Finalist).
In: International Conference on Autonomous Agents and Multiagent Systems, [Conference item]

2016

Bronstein, L. ; Koeppl, H. (2016):
Scalable inference using PMCMC and parallel tempering for high-throughput measurements of biomolecular reaction networks.
55th IEEE Conference on Decision and Control, Las Vegas, December 2016, [Conference item]

Sulaimanov, N. ; Koeppl, H. (2016):
Graph reconstruction using covariance based methods.
In: EURASIP Journal on Bioinformatics and Systems Biology, Springer, [Article]

Bronstein, L. ; Koeppl, H. (2016):
A Diagram Technique for cumulant equations in biomolecular reaction networks with mass-action kinetics.
55th IEEE Conference on Decision and Control, Las Vegas, USA, December 2016, [Conference item]

Ganguly, A. ; Altintan, D. ; Koeppl, H. (2016):
Efficient Simulation of Multiscale Reaction.
American Control Conference, Boston, Juli 2016, [Conference item]

Hill, S. M. ; Heiser, L. M. ; Cokalaer, T. ; Unger, M. ; Nesser, N. K. ; Carlin, D. E. ; Zhang, Y. ; Sokolov, A. ; Paull, E. O. ; Wong, C. K. ; Graim, K. ; Bivol, A. ; Wang, H. ; Zhu, F. ; Afsari, B. ; Danilova, L. V. ; Favorov, A. V. ; Lee, W. S. ; Taylor, D. ; Hu, C. W. ; Long, B. L. ; Noren, D. P. ; Bisberg, A. J. ; Mills, G. B. ; Gray, J. W. ; Kellen, M. ; Norman, T. ; Friend, S. ; Qutub, A. A. ; Fertig, E. J. ; Guan, Y. ; Song, M. ; Stuart, J. M. ; Spellman, P. T. ; Koeppl, H. ; Stolovitzky, G. ; Saez-Rodriguez, J. ; Mukherjee, S. (2016):
Interferring causal molecular networks: empirical assessment through a community-based effort.
13, In: Nature methods, (4), S. 310-318. Nature Publishing Group, e-ISSN 1548-7105,
[Article]

Studer, L. ; Paulevé, L. ; Zechner, C. ; Reumann, M. ; Rodriguez Martinez, M. ; Koeppl, H. (2016):
Marginalized Continuous Time Bayesian Networks for Network Reconstruction from Incomplete Observations.
Phoenix, USA, AAAI, Association for the Advancement of Artificial Intelligence, Phoenix, USA, 12.-17.02.2016, [Conference item]

Huang, L. ; Hansen, A. S. ; Pauleve, L. ; Unger, M. ; Zechner, C. ; Koeppl, H. (2016):
Reconstructing dynamic molecular states from single-cell time series.
13, In: Journal of The Royal Society Interface, (122), Royal Society Publishing, ISSN 1742-5689,
[Article]

KhudaBukhsh, W. R. ; Rueckert, J. ; Wulfheide, J. ; Hausheer, D. ; Koeppl, H. (2016):
Analysing and Leveraging Client Heterogeneity in Swarming-based Live Streaming.
In: IFIP International Conference on Networking (NETWORKING), S. 386-394,
IFIP International Conference on Networking, Wien, Austria, Mai 2016, [Conference item]

Richerzhagen, B. ; Wulfheide, J. ; Koeppl, H. ; Mauthe, A. U. ; Nahrstedt, K. ; Steinmetz, R. (2016):
Enabling Crowdsourced Live Event Coverage with Adaptive Collaborative Upload Strategies.
In: 2016 IEEE 17th International Symposium on "A World of Wireless, Mobile and Multimedia Networks" (WoWMoM),
Coimbra, Portugal, [Conference item]

Sutter, T. ; Ganguly, A. ; Koeppl, H. (2016):
A variational approach to path estimation and parameter inference of hidden diffusion processes.
In: Journal of Machine Learning Research, 17 (190), S. 1-37. [Article]

Šošić, A. ; Zoubir, A. M. ; Koeppl, H. (2016):
Policy Recognition via Expectation Maximization.
IEEE International Conference on Acoustics, Speech and Signal Processing, DOI: 10.1109/ICASSP.2016.7472589,
[Conference item]

2015

Hegemann, B. ; Unger, M. ; Lee, S. S. ; Stoffel-Studer, I. ; van den Heuvel, J. ; Pelet, S. ; Koeppl, H. ; Peter, M. (2015):
A Cellular System for Spatial Signal Decoding in Chemical Gradients.
35, In: Developmental Cell, (4), S. 458-470. Elsevier, [Article]

Huang, L. ; Hjalmarsson, H. ; Koeppl, H. (2015):
Almost sure stability and stabilization of discrete-time stochastic systems.
82, In: Systems & Control Letters, S. 26-32. [Article]

Altintan, D. ; Ganguly, A. ; Koeppl, H. (2015):
Error bound and simulation algorithm for piecewise deterministic approximations of stochastic reaction systems.
In: American Control Conference (ACC), 2015,
American Control Conference (ACC), 2015, Chicago, 1-3 July 2015, [Conference item]

Bronstein, L. ; Zechner, C. ; Koeppl, H. (2015):
Bayesian inference of reaction kinetics from single-cell recordings across a heterogeneous cell population.
85, In: ScienceDirect - Methods, S. 22-35. Elsevier, [Article]

KhudaBukhsh, W. R. ; Rueckert, J. ; Wulfheide, J. ; Hausheer, D. ; Koeppl, H. KhudaBukhsh W. R. (Urheber) (2015):
A Comprehensive Analysis of Swarming-based Live Streaming to Leverage Client Heterogenieity.
In: Technical Report, Darmstadt, Technische Universität Darmstadt, [Report]

Altintan, D. ; Ganguly, A. ; Koeppl, H. (2015):
Jump-Diffusion Approximation of Stochastic Reaction Dynamics: Error bounds and Algorithms.
13, In: SIAM Multiscale Modeling and Simulation, (4), SIAM (Society for Industrial and Applied Mathematics), ISSN 1540-3459,
[Article]

Geiger, B. C. ; Petrov, T. ; Kubin, G. ; Koeppl, H. (2015):
Optimal Kullback-Leibler Aggregation via Information Bottleneck.
60, In: IEEE Transactions on Automatic Control, (4), S. 1010-1022. IEEE, ISSN 0018-9286,
[Article]

2014

Koeppl, H. ; Zechner, C. (2014):
Uncoupled analysis of stochastic reaction networks in fluctuating environments.
10, In: PLOS Computational Biology, (12), Cornell University, ISSN 1476-928X,
[Article]

Koeppl, H. ; Hafner, M. ; Lu, J. (2014):
From Specification to Parameters: A Linearization Approach.
Part II, In: A Systems Theoretic Approach to Systems and Synthetic Biology II: Analysis and Design of Cellular Systems, S. 245-256, Netherlands, Springer, ISBN 978-94-017-9046-8,
[Book section]

Zechner, C. ; Unger, M. ; Pelet, S. ; Peter, M. ; Koeppl, H. (2014):
Scalable inference of heterogeneous reaction kinetics from pooled single-cell recordings.
11, In: Nature methods, (2), S. 197-202. [Article]

Zechner, C. ; Wadehn, F. ; Koeppl, H. (2014):
Sparse learning of Markovian population models in random environments.
S. 1723-1728, Cornell, IFAC 2014, The 19th World Congress of the International Federation of Automatic Control, Promoting automatic control for the benefit of humankind, Cape Town, South Africa, 24-29 August 2014, [Conference item]

2013

Ganguly, A. ; Petrov, T. ; Koeppl, H. (2013):
Markov chain aggregation and its applications to combinatorial reaction networks.
69, In: Journal of mathematical biology, (3), S. 767-797. [Article]

Tarca, A. L. ; Lauria, M. ; Unger, M. ; Bilal, E. ; Boue, S. ; Kumar Dey, K. ; Hoeng, J. ; Koeppl, H. ; Martin, F. ; Meyer, P. ; Nandy, P. ; Norel, R. ; Peitsch, M. ; Rice, J. ; Romero, R. ; Stolovitzky, G. ; Talikka, M. ; Xiang, Y. ; Zechner, C. (2013):
Strengths and limitations of microarray-based phenotype prediction: lessons learned from the IMPROVER Diagnostic Signature Challenge.
29, In: Bioinformatics (Oxford, England), (22), S. 2892-2899. [Article]

de Heras Ciechomski, P. ; Klann, M. ; Mange, R. ; Koeppl, H. (2013):
From biochemical reaction networks to 3D dynamics in the cell: The ZigCell3D modeling, simulation and visualisation framework.
S. 41-48, IEEE, 2013 IEEE Symposium on Biological Data Visualization (BioVis), Atlanta, USA, 13.-14.10., ISBN 978-1-4799-1658-0,
DOI: 10.1109/BioVis.2013.6664345,
[Conference item]

Klann, M. ; Koeppl, H. (2013):
Reaction schemes, escape times and geminate recombinations in particle-based spatial simulations of biochemical reactions.
10, In: Physical biology, (4), S. 046005. [Article]

Lu, J. ; August, E. ; Koeppl, H. (2013):
Inverse problems from biomedicine : Inference of putative disease mechanisms and robust therapeutic strategies.
67, In: Journal of mathematical biology, (1), S. 143-168. Springer Verlag, ISSN 0303-6812,
[Article]

Paulevé, L. ; Craciun, G. ; Koeppl, H. (2013):
Dynamical properties of Discrete Reaction Networks.
69, In: Journal of mathematical biology, S. 55-72. [Article]

Nandy, P. ; Unger, M. ; Zechner, C. ; Dey, K. ; Koeppl, H. (2013):
Learning diagnostic signatures from microarray data using Ll-regularized logistic regression.
1, In: Systems Biomedicine, (4), Taylor & Francis, [Article]

Feret, J. ; Koeppl, H. ; Petrov, T. (2013):
Stochastic fragments: A framework for the exact reduction of the stochastic semantics of rule-based models.
7, In: International Journal of Software and Informatics, (4), S. 527-604. [Article]

Klann, M. ; Paulevé, L. ; Petrov, T. ; Koeppl, H. (2013):
Coarse-Grained Brownian Dynamics Simulation of Rule-Based Models.
8130, S. 64-77, Springer Berlin Heidelberg, 11th International Conference on Computational Methods in Systems Biology (CMSB 2013), [Conference item]

Koeppl, H. ; Hafner, M. ; Lu, J. (2013):
Mapping behavioral specifications to model parameters in synthetic biology.
14, In: BMC Bioinformatics, S. S9. [Article]

Koeppl, H. ; Petrov, T. (2013):
Approximate model reductions for combinatorial reaction systems; European Control Conferenc (ECC 2013).
S. 4172-4177, European Control Conferenc (ECC 2013), Zuerich, 17-19 July 2013, [Conference item]

Paulevé, L. ; Andrieux, G. ; Koeppl, H. (2013):
Under-approximating cut sets for reachability in large scale automata Networks.
8044, S. 69-84, Springer, 25th International Conference on Computer Aided Verification (CAV 2013), [Conference item]

Zechner, C. ; Deb, S. ; Koeppl, H. (2013):
Marginal dynamics of stochastic biochemical networks in random environments.
S. 4269-4274, IEEE, 2013 European Control Conference (ECC), Zürich, 2013, [Conference item]

2012

August, E. ; Craciun, G. ; Koeppl, H. (2012):
Finding invariant sets for biological systems using monomial domination.
S. 3001-3006, Maui, HI, USA, IEEE, 51st IEEE Conference on Decision and Control (CDC), 2012, 2012, [Conference item]

August, E. ; Koeppl, H. (2012):
Computing enclosures for uncertain biochemical systems.
6, In: IET Systems Biology, (6), S. 232-240. [Article]

Petrov, T. ; Feret, J. ; Koeppl, H. (2012):
Reconstructing species-based dynamics from reduced stochastic rule-based models.
S. 15, ACM, 2012 Winter Simulation Conference (WSC'12), Berlin, Germany, 09.-12.12., [Conference item]

Zechner, C. ; Nandy, P. ; Unger, M. ; Koeppl, H. (2012):
Optimal variational perturbations for the inference of stochastic reaction dynamics.
S. 5336-5341, IEEE, 2012 IEEE 51st IEEE Conference on Decision and Control (CDC), [Conference item]

Klann, M. ; Ganguly, A. ; Koeppl, H. (2012):
Hybrid spatial Gillespie and particle tracking simulation.
28, In: Bioinformatics (Oxford, England), (18), S. i549. [Article]

Koeppl, H. ; Zechner, C. ; Ganguly, A. ; Pelet, S. ; Peter, M. (2012):
Accounting for extrinsic variability in the estimation of stochastic rate constants.
22, In: International Journal of Robust and Nonlinear Control, (10), S. 1103-1119. Wiley-Blackwell, [Article]

Nandy, P. ; Unger, M. ; Zechner, C. ; Koeppl, H. (2012):
Optimal Perturbations for the Identification of Stochastic Reaction Dynamics.
S. 686-691, Elsevier, 16th IFAC Symposium on System Identification, [Conference item]

Petrov, T. ; Ganguly, A. ; Koeppl, H. (2012):
Model Decomposition and Stochastic Fragments.
284, In: Electronic Notes in Theoretical Computer Science, S. 105-124. [Article]

Pantea, C. ; Koeppl, H. ; Craciun, G. (2012):
Global injectivity and multiple equilibria in uni- and bi-molecular reaction networks.
17, In: Discrete and Continuous Dynamical Systems - Series B, (6), S. 2153-2170. American Institute of Mathematical Sciences, [Article]

Zechner, C. ; Ruess, J. ; Krenn, P. ; Pelet, S. ; Peter, M. ; Lygeros, J. ; Koeppl, H. (2012):
Moment-based inference predicts bimodality in transient gene expression.
109, In: Proceedings of the National Academy of Sciences of the United States of America, (21), S. 8340-8345. [Article]

Feret, J. ; Henzinger, T. ; Koeppl, H. ; Petrov, T. (2012):
Lumpability Abstractions of Rule-based Systems.
431, In: Journal of Theoretical Comuter Science, S. 137-164. [Article]

Hafner, M. ; Koeppl, H. ; Gonze, D. (2012):
Effect of network architecture on synchronization and entrainment properties of the circadian oscillations in the suprachiasmatic nucleus.
8, In: PLoS computational biology, (3), S. e1002419. [Article]

Hiroi, N. ; Klann, M. ; Iba, K. ; de Heras Ciechomski, P. ; Yamashita, S. ; Tabira, A. ; Okuhara, T. ; Kubojima, T. ; Okada, Y. ; Oka, K. ; Mange, R. ; Unger, M. ; Funahashi, A. ; Koeppl, H. (2012):
From microscopy data to in silico environments for in vivo-oriented simulations.
2012, In: EURASIP Journal on Bioinformatics and Systems Biology, (1), S. 7. [Article]

Klann, M. ; Koeppl, H. (2012):
Spatial simulations in systems biology: from molecules to cells.
13, In: International journal of molecular sciences, (6), S. 7798-7827. [Article]

Klann, M. ; Koeppl, H. ; Reuss, M. (2012):
Spatial modeling of vesicle transport and the cytoskeleton: the challenge of hitting the right road.
7, In: PloS one, (1), S. e29645. [Article]

August, E. ; Lu, J. ; Koeppl, H. (2012):
Trajectory enclosures for systems with uncertainties in initial conditions and parameter values.
S. 1488-1493, Fairmont Queen Elizabeth, Montreal, Canada, 2012 American Control Conference, Fairmont Queen Elizabeth, Montreal, Canada, 2012, [Conference item]

Klann, M. ; Koeppl, H. (2012):
Spatial stochastic simulation of transcription factor binding reveals mechaniscms to control gene activation.
61, S. 51-54, Tampere University of Technology, Tampere International Center for Signal Processing, 9th International Workshop on Computational Systems Biology (WCSB 2012), [Conference item]

Koeppl, H. ; Petrov, T. (2012):
Reductions of stochastic rule-based models: HOG pathway in yeast.
ICSB : The 13th International Conference on Systems Biology, [Conference item]

2011

Zechner, C. ; Pelet, S. ; Peter, M. ; Koeppl, H. (2011):
Recursive Bayesian estimation of stochastic rate constants from heterogeneous cell populations.
In: IEEE Conference on Decision and Control and European Control Conference, S. 5837-5843. IEEE, [Article]

Koeppl, H. ; Hafner, M. ; Ganguly, A. ; Mehrotra, A. (2011):
Deterministic characterization of phase noise in biomolecular oscillators.
8, In: Physical biology, (5), S. 55008. [Article]

Meyer, P. ; Alexopoulos, L. G. ; Bonk, T. ; Califano, A. ; Cho, C. R. ; de la Fuente, A. ; de Graaf, D. ; Hartemink, A. J. ; Hoeng, J. ; Ivanov, N. V. ; Koeppl, H. ; Linding, R. ; Marbach, D. ; Norel, R. ; Peitsch, M. C. ; Rice, J. J. ; Royyuru, A. ; Schacherer, F. ; Sprengel, J. ; Stolle, K. ; Vitkup, D. ; Stolovitzky, G. (2011):
Verification of systems biology research in the age of collaborative competition.
29, In: Nature biotechnology, (9), S. 811-815. [Article]

Koeppl, H. ; Petrov, T. (2011):
Stochastic Semantics of Signaling as a Composition of Agent-view Automata.
272, In: Electronic Notes in Theoretical Computer Science, S. 3-17. [Article]

August, E. ; Wang, Y. ; Doyle, F. J. ; Lu, J. ; Koeppl, H. (2011):
Computationally implementable sufficient conditions for the synchronisation of coupled dynamical systems with time delays in the coupling.
S. 839-844, San Francisco, CA, USA, IEEE, Proceedings of the 2011 American Control Conference, [Conference item]

Danos, V. ; Koeppl, H. ; Wilson-Kanamori, J. (2011):
Cooperative assembly systems.
S. 1-21, Springer, 17th International Conference on DNA-Based Computers (DNA 2011), Pasadena, USA, 19.-23.09., ISBN 978-3-642-23637-2,
DOI: 10.1007/978-3-642-23638-9_1,
[Conference item]

Falk, M. ; Ott, M. ; Ertl, T. ; Klann, M. ; Koeppl, H. (2011):
Parallelized Agent-based Simulation on CPU and Graphics Hardware for Spatial and Stochastic Models in Biology Categories and Subject Descriptors.
In: CMSB '11 Proceedings of the 9th International Conference on Computational Methods in Systems Biology, S. 73-82,
New York, New York, USA, ACM Press, [Conference item]

Hafner, M. ; Koeppl, H. (2011):
Stochastic Simulations in Systems Biology.
1, In: Handbook of Research on Computational Science and Engineering: Theory and Practice, S. 267-286, IGI Global, [Book section]

Hafner, M. ; Lu, J. ; Petrov, T. ; Koeppl, H. (2011):
Rational design of robust biomolecular circuits: From specification to parameters.
In: Analysis and Design of Biomolecular Circuits, S. 253-281, New York, NY, Springer, [Book section]

Klann, M. ; Ganguly, A. ; Koeppl, H. (2011):
Improved Reaction Scheme for Spatial Stochastic Simulations with Single Molecule Detail.
57, S. 93-96, Tampere, Tampere University of Technology, Eighth International Workshop on Computational Systems Biology (WCSB 2011), [Conference item]

Koeppl, H. ; Andreozzi, S. ; Steuer, R. (2011):
Guaranteed and Randomized Methods for Stability Analysis of Uncertain Metabolic Networks.
407, In: Lecture notes in control and information sciences, S. 297-309. Springer, [Article]

Lu, J. ; Grass, P. ; Koeppl, H. (2011):
Computational identification of optimal multi target drug intervention strategies for combination theory.
S. 132, Zurich, Eighth International Workshop on Computational Systems Biology, WCSB 2011, June 6-8, 2011, Zurich, Switzerland, [Conference item]

Unger, M. ; Lee, S.-S. ; Peter, M. ; Koeppl, H. (2011):
Pulse Width Modulation of Liquid Flows.
S. 1567-1569, San Diego, CA, Chemical and Biological Microsystems Society, 15th International Conference on Miniaturized Systems for Chemistry and Life Sciences, [Conference item]

2010

Camporesi, F. ; Feret, J. ; Koeppl, H. ; Petrov, T. (2010):
Combining Model Reductions.
265, In: Electronic Notes in Theoretical Computer Science, S. 73-96. [Article]

Koeppl, H. ; Setti, G. ; Pelet, S. ; Mangia, M. ; Petrov, T. ; Peter, M. (2010):
Probability metrics to calibrate stochastic chemical kinetics.
In: Circuits and Systems (ISCAS), Proceedings of 2010 IEEE International Symposium on, [Article]

Petrov, T. ; Koeppl, H. (2010):
Maximal reduction of deterministic semantics of rule-based models - Google-Suche.
S. 83-87, Proceedings of the International Workshop on computational Systems Biology (WCSB) in 2010, [Conference item]

2009

Hafner, M. ; Koeppl, H. ; Hasler, M. ; Wagner, A. (2009):
'Glocal' robustness analysis and model discrimination for circadian oscillators.
5, In: PLoS Computational Biology, (10), S. e1000534. [Article]

Koeppl, H. ; Setti, G. (2009):
Analysis and design of biological circuits and systems.
S. 297-300, Taipeh, Taiwan, IEEE, 2009 IEEE International Symposium on Circuits and Systems, [Conference item]

Rodrigues, A. ; Koeppl, H. ; Ohtsuki, H. ; Satake, A. (2009):
A Game Theoretical Model of deforestation in human-environment relationships.
258, In: Journal of Theoretical Biology, (1), S. 127-134. [Article]

Koeppl, H. (2009):
A Local Nonlinear Model for the Approximation and Identification of a Class of Systems.
56, In: IEEE Transactions on Circuits and Systems II: Express Briefs, (4), S. 315-319. [Article]

Hafner, M. ; Koeppl, H. ; Wagner, A. (2009):
Robustness and evolution in oscillatory systems with feedback loops.
S. 4, Denver, USA, IEEE, Proc. of the Third IEEE International Conference on Foundations of Systems Biology in Engineering (FOSBE), [Conference item]

Parisi, F. ; Koeppl, H. ; Naef, F. (2009):
Network inference by combining biologically motivated regulatory constraints with penalized regression.
1158, In: Annals of the New York Academy of Sciences, S. 114-124. [Article]

Hafner, M. ; Danos, V. ; Koeppl, H. (2009):
Rule-based modeling for protein-protein interaction networks - the Cyanobacterial circadian clock as a case studyproceedings.
S. 87-90, Aarhus, Denmark, Proceedings of the International Workshop on Computational Systems Biology (WCSB), [Conference item]

Koeppl, H. ; Haeusler, S. (2009):
Motifs, algebraic connectivity and computational performance of two data- based cortical circuit templates.
In: Proceedings of the sixth International Workshop on Computational Systems Biology, S. 83-86. [Article]

Koeppl, H. ; Hafner, M. ; Steuer, R. (2009):
Semi-quantitative stability analysis constrains saturation levels in metabolic networks.
S. 91-94, Aarhus, Denmark, Proceedings of the Intenational Workshop on Computational Systems Biology (WCSB), [Conference item]

Koeppl, H. ; Schumacher, L. ; Danos, V. (2009):
A Statistical analysis of receptor.
S. 95-98, Aarhus, Denmark, Proceedings of the International Workshop on Computtional Systmes Biology (WCSB), [Conference item]

2008

Krall, C. ; Witrisal, K. ; Leus, G. ; Koeppl, H. (2008):
Minimum Mean-Square Error Equalization for Second-Order Volterra Systems.
56, In: IEEE Transactions on Signal Processing, (10), S. 4729-4737. IEEE, [Article]

Murmann, B. ; Vogel, C. ; Koeppl, H. (2008):
Digitally enhanced analog circuits: System aspects.
S. 560-563, IEEE, 2008 IEEE International Symposium on Circuits and Systems, [Conference item]

2007

Singerl, P. ; Koeppl, H. (2007):
A Low-rate identification method for digital predistorters based on Volterra kernel interpolation.
56, In: Analog Integrated Circuits and Signal Processing, (1-2), S. 107-115. Springer, [Article]

Koeppl, H. (2007):
The Composition Rule for Multivariate Volterra Operators and its Application to Circuit Analysis.
S. 441-444, IEEE, 2007 IEEE International Symposium on Circuits and Systems, [Conference item]

Huang, C.-H. ; Koeppl, H. (2007):
A Bio-inspired Computer Fovea Model based on hexagonal-type cellular neural networks.
54, In: IEEE Transactions on circuits and systems-I : regular papers, (1), IEEE, [Article]

Koeppl, H. ; Chua, L. O. (2007):
An Adaptive Cellular Nonlinear Network and its Application.
In: Proceedings of the International Symposium on Nonlinear Theory and its Applications (NOLTA), pages 15–18, Sept. 16-19, 2007, Vancouver, Canada., [Article]

Wolkerstorfer, M. ; Koeppl, H. (2007):
On the Projection Dynamic for Selfish Routing.
Dresden, Germany, European Complex Systems Conference, [Conference item]

2006

Koeppl, H. ; Singerl, P. (2006):
An Efficient Scheme for Nonlinear Modeling and Predistortion in Mixed-Signal Systems.
53, In: IEEE Transactions on Circuits and Systems II: Express Briefs, (12), S. 1368-1372. [Article]

Koeppl, H. (2006):
An Adaptive Cellular Network for Subspace Extraction.
S. 1037-1041, Pacific Grove, CA, USA, IEEE, 2006 Fortieth Asilomar Conference on Signals, Systems and Computers, [Conference item]

Koeppl, H. (2006):
Information Rate Maximization over a Resistive Grid.
S. 5196-5203, Vancouver, BC, IEEE, The 2006 IEEE International Joint Conference on Neural Network Proceedings, [Conference item]

2005

Singerl, P. ; Koeppl, H. (2005):
A Low-rate identification method for digital predistorters based on Volterra kernel interpolation.
2, In: Circuits and Systems, 2005. 48th Midwest Symposium, S. 1533-1536. IEEE, [Article]

Krall, C. ; Witrisal, K. ; Koeppl, H. ; Leus, G. ; Pausini, M. (2005):
Nonlinear equalization for frame-differential IR-UWB receivers.
In: 2005 IEEE International Conference on Ultra-Wideband, S. 576-581. IEEE, [Article]

Schwingshackl, D. ; Koeppl, H. ; Kubin, G. (2005):
Exact discrete-time representation of continuous-time Volterra filters.
In: NSIP 2005. Abstracts. IEEE-Eurasip Nonlinear Signal and Image Processing, 2005., S. 11. IEEE, [Article]

Singerl, P. ; Koeppl, H. (2005):
Volterra kernel interpolation for system modeling and predistortion purposes.
1, S. 251-254, IEEE, International Symposium on Signals, Circuits and Systems, 2005. ISSCS 2005., [Conference item]

2004

Shutin, D. ; Koeppl, H. (2004):
Application of the Evidence Procedure to Linear Problems in Signal Processing.
735, S. 161-168, AIP, AIP Conference Proceedings, [Conference item]

Koeppl, H. ; Josan, A. S. ; Paoli, G. ; Kubin, G. (2004):
The Cramer-Rao Bound and DMT Signal Optimisation for the Identification of a Wiener-Type Model.
12, In: EURASIP Journal on Applied Signal Processing, S. 1817-1830. [Article]

Koeppl, H. (2004):
Nonlinear System Identification for Mixed Signal Processing | Signal Processing and Speech Communication Laboratory.
Graz Universitay of Technology, Graz, Austria,
[PhD thesis]

Koeppl, H. ; Schwingshackl, D. (2004):
Comparison of discrete-time approximations for continuous-time nonlinear systems.
2, In: 2004 IEEE International Conference on Acoustics, Speech, and Signal Processing, S. ii-881. IEEE, [Article]

2003

Koeppl, H. ; Kubin, G. ; Paoli, G. (2003):
Bayesian methods for sparse RLS adaptive filters.
2, S. 1273-1277, Pacific Grove, CA, USA, IEEE, The Thrity-Seventh Asilomar Conference on Signals, Systems & Computers, 2003, [Conference item]

Koeppl, H. ; Paoli, G. ; Kubin, G. (2003):
The Cramer-Rao bound for a factorizable Volterra system.
Grado, Italy, IEEE, IEEE Workshop on Nonlinear Signal and Image Processing, [Conference item]

Vogel, C. ; Koeppl, H. (2003):
Behavioral Modeling of Time-Interleaved ADCs using MATLAB.
S. 45-48, Austrochip 2003, Linz, Austria, 03.-12.10.2003, [Conference item]

2002

Koeppl, H. ; Paoli, G. (2002):
Non-Linear System Identification of a Broadband Subscriber Line Interface Circuitry Using the Volterra Approach.
V, In: Mathematics in Signal Processing V, (Chapter 13), Oxford University Press, [Article]

Koeppl, H. ; Paoli, G. (2002):
Non-linear modeling of a broadband SLIC for ADSL-Lite-over-POTS using harmonic analysis.
2, S. II-133, Scottsdale, Arizona, USA, IEEE, 2002 IEEE International Symposium on Circuits and Systems. Proceedings (Cat. No.02CH37353), [Conference item]

2001

Koeppl, H. (2001):
Identification of a non-linear analog circuitry for an ADSL application.
Karl-Franzens-Universität, Graz, Austria, [Master thesis]

Paoli, G. ; Koeppl, H. (2001):
Non-linear identification and modeling of large scale analog integrated circuitties for DMT based applications.
S. 84-87, Bratislava, Slovakia, Proc. of the Electronic Circuits and Systems Conference, [Conference item]

2000

Koeppl, H. ; Paoli, G. The Institute of Mathematics and its Applications (IMA) (Urheber) (2000):
Non-Linear System Identification of a Broadband Subscriber Line Interface Circuit for ADSL-Lite Using the Volterra Approach.
S. 359-362, 5th IMA International Conference on Mathematics in Signal Processing, Warwick, United Kingdom, [Conference item]

This list was generated on Wed Dec 2 02:24:57 2020 CET.