Publications | Empirical Inference - Max Planck Institute for Intelligent Systems

Babbar, R., Schölkopf, B.

Data scarcity, robustness and extreme multi-label classification

Machine Learning, 108(8):1329-1351, September 2019, Special Issue of the ECML PKDD 2019 Journal Track (article)

Babbar, R., Schölkopf, B. Data scarcity, robustness and extreme multi-label classification Machine Learning, 108(8):1329-1351, September 2019, Special Issue of the ECML PKDD 2019 Journal Track (article)

Learning Transferable Representations

Rojas-Carulla, M.

University of Cambridge, UK, 2019 (phdthesis)

Rojas-Carulla, M. Learning Transferable Representations University of Cambridge, UK, 2019 (phdthesis)

Sample-efficient deep reinforcement learning for continuous control

Gu, S.

University of Cambridge, UK, 2019 (phdthesis)

Gu, S. Sample-efficient deep reinforcement learning for continuous control University of Cambridge, UK, 2019 (phdthesis)

A 32-channel multi-coil setup optimized for human brain shimming at 9.4T

Aghaeifar, A., Zhou, J., Heule, R., Tabibian, B., Schölkopf, B., Jia, F., Zaitsev, M., Scheffler, K.

Magnetic Resonance in Medicine, 2019, (Early View) (article)

Aghaeifar, A., Zhou, J., Heule, R., Tabibian, B., Schölkopf, B., Jia, F., Zaitsev, M., Scheffler, K. A 32-channel multi-coil setup optimized for human brain shimming at 9.4T Magnetic Resonance in Medicine, 2019, (Early View) (article)

DOI Project Page Project Page [BibTex]

Multidimensional Contrast Limited Adaptive Histogram Equalization

Stimper, V., Bauer, S., Ernstorfer, R., Schölkopf, B., Xian, R. P.

IEEE Access, 7, pages: 165437-165447, 2019 (article)

arXiv link (url) DOI [BibTex]

Stimper, V., Bauer, S., Ernstorfer, R., Schölkopf, B., Xian, R. P. Multidimensional Contrast Limited Adaptive Histogram Equalization IEEE Access, 7, pages: 165437-165447, 2019 (article)

arXiv link (url) DOI [BibTex]

Enhancing Human Learning via Spaced Repetition Optimization

Tabibian, B., Upadhyay, U., De, A., Zarezade, A., Schölkopf, B., Gomez Rodriguez, M.

Proceedings of the National Academy of Sciences, 2019, PNAS published ahead of print January 22, 2019 (article)

Tabibian, B., Upadhyay, U., De, A., Zarezade, A., Schölkopf, B., Gomez Rodriguez, M. Enhancing Human Learning via Spaced Repetition Optimization Proceedings of the National Academy of Sciences, 2019, PNAS published ahead of print January 22, 2019 (article)

DOI Project Page Project Page [BibTex]

Formally justified and modular Bayesian inference for probabilistic programs

Ścibior*, A.

University of Cambridge, UK, 2019 (phdthesis)

Ścibior*, A. Formally justified and modular Bayesian inference for probabilistic programs University of Cambridge, UK, 2019 (phdthesis)

Spatial Filtering based on Riemannian Manifold for Brain-Computer Interfacing

Xu, J.

Technical University of Munich, Germany, 2019 (mastersthesis)

Xu, J. Spatial Filtering based on Riemannian Manifold for Brain-Computer Interfacing Technical University of Munich, Germany, 2019 (mastersthesis)

Learning to Control Highly Accelerated Ballistic Movements on Muscular Robots

Büchler, D., Calandra, R., Peters, J.

2019 (article) Submitted

Abstract

High-speed and high-acceleration movements are inherently hard to control. Applying learning to the control of such motions on anthropomorphic robot arms can improve the accuracy of the control but might damage the system. The inherent exploration of learning approaches can lead to instabilities and the robot reaching joint limits at high speeds. Having hardware that enables safe exploration of high-speed and high-acceleration movements is therefore desirable. To address this issue, we propose to use robots actuated by Pneumatic Artificial Muscles (PAMs). In this paper, we present a four degrees of freedom (DoFs) robot arm that reaches high joint angle accelerations of up to 28000 °/s^2 while avoiding dangerous joint limits thanks to the antagonistic actuation and limits on the air pressure ranges. With this robot arm, we are able to tune control parameters using Bayesian optimization directly on the hardware without additional safety considerations. The achieved tracking performance on a fast trajectory exceeds previous results on comparable PAM-driven robots. We also show that our system can be controlled well on slow trajectories with PID controllers due to careful construction considerations such as minimal bending of cables, lightweight kinematics and minimal contact between PAMs and PAMs with the links. Finally, we propose a novel technique to control the the co-contraction of antagonistic muscle pairs. Experimental results illustrate that choosing the optimal co-contraction level is vital to reach better tracking performance. Through the use of PAM-driven robots and learning, we do a small step towards the future development of robots capable of more human-like motions.

Arxiv Video [BibTex]

Büchler, D., Calandra, R., Peters, J. Learning to Control Highly Accelerated Ballistic Movements on Muscular Robots 2019 (article) Submitted

Arxiv Video [BibTex]

Pragmatism and Variable Transformations in Causal Modelling

Weichwald, S.

ETH Zurich, 2019 (phdthesis)

Weichwald, S. Pragmatism and Variable Transformations in Causal Modelling ETH Zurich, 2019 (phdthesis)

Inferring causation from time series with perspectives in Earth system sciences

Nature Communications, 2019 (article) In revision

Runge, J., Bathiany, S., Bollt, E., Camps-Valls, G., Coumou, D., Deyle, E., Glymour, C., Kretschmer, M., Mahecha, M., van Nes, E., Peters, J., Quax, R., Reichstein, M., Scheffer, M. S. B., Spirtes, P., Sugihara, G., Sun, J., Zhang, K., Zscheischler, J. Inferring causation from time series with perspectives in Earth system sciences Nature Communications, 2019 (article) In revision

Quantification of tumor heterogeneity using PET/MRI and machine learning

Katiyar, P.

Eberhard Karls Universität Tübingen, Germany, 2019 (phdthesis)

Katiyar, P. Quantification of tumor heterogeneity using PET/MRI and machine learning Eberhard Karls Universität Tübingen, Germany, 2019 (phdthesis)

Kübler, J. M., Muandet, K., Schölkopf, B.

Quantum mean embedding of probability distributions

Physical Review Research, 1(3):033159, American Physical Society, 2019 (article)

Kübler, J. M., Muandet, K., Schölkopf, B. Quantum mean embedding of probability distributions Physical Review Research, 1(3):033159, American Physical Society, 2019 (article)

Reliable Real-Time Ball Tracking for Robot Table Tennis

Gomez-Gonzalez, S., Nemmour, Y., Schölkopf, B., Peters, J.

Robotics, 8(4):90, 2019 (article)

Gomez-Gonzalez, S., Nemmour, Y., Schölkopf, B., Peters, J. Reliable Real-Time Ball Tracking for Robot Table Tennis Robotics, 8(4):90, 2019 (article)

Advances in Probabilistic Modelling: Sparse Gaussian Processes, Autoencoders, and Few-shot Learning

Bauer, M.

University of Cambridge, UK, 2019 (phdthesis)

Bauer, M. Advances in Probabilistic Modelling: Sparse Gaussian Processes, Autoencoders, and Few-shot Learning University of Cambridge, UK, 2019 (phdthesis)

arXiv link (url) DOI Project Page [BibTex]

Optimizing the Execution of Dynamic Robot Movements With Learning Control

Koc, O., Maeda, G., Peters, J.

IEEE Transactions on Robotics, pages: 1-16, 2019 (article)

Koc, O., Maeda, G., Peters, J. Optimizing the Execution of Dynamic Robot Movements With Learning Control IEEE Transactions on Robotics, pages: 1-16, 2019 (article)

arXiv link (url) DOI Project Page [BibTex]

Learning to Serve: An Experimental Study for a New Learning From Demonstrations Framework

Koc, O., Peters, J.

IEEE Robotics and Automation Letters, 4(2):1784-1791, 2019 (article)

link (url) DOI Project Page [BibTex]

Koc, O., Peters, J. Learning to Serve: An Experimental Study for a New Learning From Demonstrations Framework IEEE Robotics and Automation Letters, 4(2):1784-1791, 2019 (article)

link (url) DOI Project Page [BibTex]

Eigendecompositions of Transfer Operators in Reproducing Kernel Hilbert Spaces

Klus, S., Schuster, I., Muandet, K.

Journal of Nonlinear Science, 2019, First Online: 21 August 2019 (article)

Klus, S., Schuster, I., Muandet, K. Eigendecompositions of Transfer Operators in Reproducing Kernel Hilbert Spaces Journal of Nonlinear Science, 2019, First Online: 21 August 2019 (article)

2015

easyGWAS: An Integrated Computational Framework for Advanced Genome-Wide Association Studies

Grimm, Dominik

Eberhard Karls Universität Tübingen, November 2015 (phdthesis)

2015

Grimm, Dominik easyGWAS: An Integrated Computational Framework for Advanced Genome-Wide Association Studies Eberhard Karls Universität Tübingen, November 2015 (phdthesis)

Quantifying changes in climate variability and extremes: Pitfalls and their overcoming

Sippel, S., Zscheischler, J., Heimann, M., Otto, F. E. L., Peters, J., Mahecha, M. D.

Geophysical Research Letters, 42(22):9990-9998, November 2015 (article)

Sippel, S., Zscheischler, J., Heimann, M., Otto, F. E. L., Peters, J., Mahecha, M. D. Quantifying changes in climate variability and extremes: Pitfalls and their overcoming Geophysical Research Letters, 42(22):9990-9998, November 2015 (article)

Diversity of sharp wave-ripple LFP signatures reveals differentiated brain-wide dynamical events

Ramirez-Villegas, J. F., Logothetis, N. K., Besserve, M.

Proceedings of the National Academy of Sciences U.S.A, 112(46):E6379-E6387, November 2015 (article)

Ramirez-Villegas, J. F., Logothetis, N. K., Besserve, M. Diversity of sharp wave-ripple LFP signatures reveals differentiated brain-wide dynamical events Proceedings of the National Academy of Sciences U.S.A, 112(46):E6379-E6387, November 2015 (article)

Causal Discovery Beyond Conditional Independences

Sgouritsa, E.

Eberhard Karls Universität Tübingen, Germany, October 2015 (phdthesis)

Sgouritsa, E. Causal Discovery Beyond Conditional Independences Eberhard Karls Universität Tübingen, Germany, October 2015 (phdthesis)

Noise masking of White’s illusion exposes the weakness of current spatial filtering models of lightness perception

Betz, T., Shapley, R. M., Wichmann, F. A., Maertens, M.

Journal of Vision, 15(14):1-17, October 2015 (article)

Betz, T., Shapley, R. M., Wichmann, F. A., Maertens, M. Noise masking of White’s illusion exposes the weakness of current spatial filtering models of lightness perception Journal of Vision, 15(14):1-17, October 2015 (article)

Causal Inference for Empirical Time Series Based on the Postulate of Independence of Cause and Mechanism

Besserve, M.

53rd Annual Allerton Conference on Communication, Control, and Computing, September 2015 (talk)

Besserve, M. Causal Inference for Empirical Time Series Based on the Postulate of Independence of Cause and Mechanism 53rd Annual Allerton Conference on Communication, Control, and Computing, September 2015 (talk)

From Points to Probability Measures: A Statistical Learning on Distributions with Kernel Mean Embedding

Muandet, K.

University of Tübingen, Germany, University of Tübingen, Germany, September 2015 (phdthesis)

Muandet, K. From Points to Probability Measures: A Statistical Learning on Distributions with Kernel Mean Embedding University of Tübingen, Germany, University of Tübingen, Germany, September 2015 (phdthesis)

Machine Learning Approaches to Image Deconvolution

Schuler, C.

University of Tübingen, Germany, University of Tübingen, Germany, September 2015 (phdthesis)

Schuler, C. Machine Learning Approaches to Image Deconvolution University of Tübingen, Germany, University of Tübingen, Germany, September 2015 (phdthesis)

Shifts of Gamma Phase across Primary Visual Cortical Sites Reflect Dynamic Stimulus-Modulated Information Transfer

Besserve, M., Lowe, S. C., Logothetis, N. K., Schölkopf, B., Panzeri, S.

PLOS Biology, 13(9):e1002257, September 2015 (article)

Besserve, M., Lowe, S. C., Logothetis, N. K., Schölkopf, B., Panzeri, S. Shifts of Gamma Phase across Primary Visual Cortical Sites Reflect Dynamic Stimulus-Modulated Information Transfer PLOS Biology, 13(9):e1002257, September 2015 (article)

Janzing, D., Schölkopf, B.

Semi-Supervised Interpolation in an Anticausal Learning Scenario

Journal of Machine Learning Research, 16, pages: 1923-1948, September 2015 (article)

Janzing, D., Schölkopf, B. Semi-Supervised Interpolation in an Anticausal Learning Scenario Journal of Machine Learning Research, 16, pages: 1923-1948, September 2015 (article)

Testing the role of luminance edges in White’s illusion with contour adaptation

Betz, T., Shapley, R. M., Wichmann, F. A., Maertens, M.

Journal of Vision, 15(11):1-16, August 2015 (article)

Betz, T., Shapley, R. M., Wichmann, F. A., Maertens, M. Testing the role of luminance edges in White’s illusion with contour adaptation Journal of Vision, 15(11):1-16, August 2015 (article)

Blind Retrospective Motion Correction of MR Images

Loktyushin, A.

University of Tübingen, Germany, May 2015 (phdthesis)

Loktyushin, A. Blind Retrospective Motion Correction of MR Images University of Tübingen, Germany, May 2015 (phdthesis)

Independence of cause and mechanism in brain networks

Besserve, M.

DALI workshop on Networks: Processes and Causality, April 2015 (talk)

Besserve, M. Independence of cause and mechanism in brain networks DALI workshop on Networks: Processes and Causality, April 2015 (talk)

Blind multirigid retrospective motion correction of MR images

Loktyushin, A., Nickisch, H., Pohmann, R., Schölkopf, B.

Magnetic Resonance in Medicine, 73(4):1457-1468, April 2015 (article)

Loktyushin, A., Nickisch, H., Pohmann, R., Schölkopf, B. Blind multirigid retrospective motion correction of MR images Magnetic Resonance in Medicine, 73(4):1457-1468, April 2015 (article)

A quantum advantage for inferring causal structure

Ried, K., Agnew, M., Vermeyden, L., Janzing, D., Spekkens, R. W., Resch, K. J.

Nature Physics, 11(5):414-420, March 2015 (article)

Abstract

The problem of inferring causal relations from observed correlations is relevant to a wide variety of scientific disciplines. Yet given the correlations between just two classical variables, it is impossible to determine whether they arose from a causal influence of one on the other or a common cause influencing both. Only a randomized trial can settle the issue. Here we consider the problem of causal inference for quantum variables. We show that the analogue of a randomized trial, causal tomography, yields a complete solution. We also show that, in contrast to the classical case, one can sometimes infer the causal structure from observations alone. We implement a quantum-optical experiment wherein we control the causal relation between two optical modes, and two measurement schemes—with and without randomization—that extract this relation from the observed correlations. Our results show that entanglement and quantum coherence provide an advantage for causal inference.

Ried, K., Agnew, M., Vermeyden, L., Janzing, D., Spekkens, R. W., Resch, K. J. A quantum advantage for inferring causal structure Nature Physics, 11(5):414-420, March 2015 (article)

Positive definite matrices and the S-divergence

Sra, S.

Proceedings of the American Mathematical Society, 2015, Published electronically: October 22, 2015 (article)

Sra, S. Positive definite matrices and the S-divergence Proceedings of the American Mathematical Society, 2015, Published electronically: October 22, 2015 (article)

Structural Intervention Distance (SID) for Evaluating Causal Graphs

Peters, J., Bühlmann, P.

Neural Computation , 27(3):771-799, 2015 (article)

Peters, J., Bühlmann, P. Structural Intervention Distance (SID) for Evaluating Causal Graphs Neural Computation , 27(3):771-799, 2015 (article)

Likelihood and Consilience: On Forster’s Counterexamples to the Likelihood Theory of Evidence

Zhang, J., Zhang, K.

Philosophy of Science, Supplementary Volume 2015, 82(5):930-940, 2015 (article)

Zhang, J., Zhang, K. Likelihood and Consilience: On Forster’s Counterexamples to the Likelihood Theory of Evidence Philosophy of Science, Supplementary Volume 2015, 82(5):930-940, 2015 (article)

On the Intersection Property of Conditional Independence and its Application to Causal Discovery

Peters, J.

Journal of Causal Inference, 3(1):97-108, 2015 (article)

Peters, J. On the Intersection Property of Conditional Independence and its Application to Causal Discovery Journal of Causal Inference, 3(1):97-108, 2015 (article)

Information-Theoretic Implications of Classical and Quantum Causal Structures

Chaves, R., Majenz, C., Luft, L., Maciel, T., Janzing, D., Schölkopf, B., Gross, D.

18th Conference on Quantum Information Processing (QIP), 2015 (talk)

Web link (url) [BibTex]

Chaves, R., Majenz, C., Luft, L., Maciel, T., Janzing, D., Schölkopf, B., Gross, D. Information-Theoretic Implications of Classical and Quantum Causal Structures 18th Conference on Quantum Information Processing (QIP), 2015 (talk)

Web link (url) [BibTex]

Crowdsourced analysis of clinical trial data to predict amyotrophic lateral sclerosis progression

Nature Biotechnology, 33, pages: 51-57, 2015 (article)

Küffner, R., Zach, N., Norel, R., Hawe, J., Schoenfeld, D., Wang, L., Li, G., Fang, L., Mackey, L., Hardiman, O., Cudkowicz, M., Sherman, A., Ertaylan, G., Grosse-Wentrup, M., Hothorn, T., van Ligtenberg, J., Macke, J., Meyer, T., Schölkopf, B., Tran, L., Vaughan, R., Stolovitzky, G., Leitner, M. Crowdsourced analysis of clinical trial data to predict amyotrophic lateral sclerosis progression Nature Biotechnology, 33, pages: 51-57, 2015 (article)

Probabilistic Interpretation of Linear Solvers

Hennig, P.

SIAM Journal on Optimization, 25(1):234-260, 2015 (article)

Hennig, P. Probabilistic Interpretation of Linear Solvers SIAM Journal on Optimization, 25(1):234-260, 2015 (article)

Developing biorobotics for veterinary research into cat movements

Mariti, C., Muscolo, G., Peters, J., Puig, D., Recchiuto, C., Sighieri, C., Solanas, A., von Stryk, O.

Journal of Veterinary Behavior: Clinical Applications and Research, 10(3):248-254, 2015 (article)

Mariti, C., Muscolo, G., Peters, J., Puig, D., Recchiuto, C., Sighieri, C., Solanas, A., von Stryk, O. Developing biorobotics for veterinary research into cat movements Journal of Veterinary Behavior: Clinical Applications and Research, 10(3):248-254, 2015 (article)

Spatial statistics and attentional dynamics in scene viewing

Engbert, R., Trukenbrod, H., Barthelmé, S., Wichmann, F.

Journal of Vision, 15(1):1-17, 2015 (article)

Engbert, R., Trukenbrod, H., Barthelmé, S., Wichmann, F. Spatial statistics and attentional dynamics in scene viewing Journal of Vision, 15(1):1-17, 2015 (article)

The Randomized Causation Coefficient

Lopez-Paz, D., Muandet, K., Recht, B.

Journal of Machine Learning, 16, pages: 2901-2907, 2015 (article)

Lopez-Paz, D., Muandet, K., Recht, B. The Randomized Causation Coefficient Journal of Machine Learning, 16, pages: 2901-2907, 2015 (article)

Towards denoising XMCD movies of fast magnetization dynamics using extended Kalman filter

Kopp, M., Harmeling, S., Schütz, G., Schölkopf, B., Fähnle, M.

Ultramicroscopy, 148, pages: 115-122, 2015 (article)

Abstract

The Kalman filter is a well-established approach to get information on the time-dependent state of a system from noisy observations. It was developed in the context of the Apollo project to see the deviation of the true trajectory of a rocket from the desired trajectory. Afterwards it was applied to many different systems with small numbers of components of the respective state vector (typically about 10). In all cases the equation of motion for the state vector was known exactly. The fast dissipative magnetization dynamics is often investigated by x-ray magnetic circular dichroism movies (XMCD movies), which are often very noisy. In this situation the number of components of the state vector is extremely large (about 105), and the equation of motion for the dissipative magnetization dynamics (especially the values of the material parameters of this equation) is not well known. In the present paper it is shown by theoretical considerations that – nevertheless – there is no principle problem for the use of the Kalman filter to denoise XMCD movies of fast dissipative magnetization dynamics.

Web DOI [BibTex]

Kopp, M., Harmeling, S., Schütz, G., Schölkopf, B., Fähnle, M. Towards denoising XMCD movies of fast magnetization dynamics using extended Kalman filter Ultramicroscopy, 148, pages: 115-122, 2015 (article)

Web DOI [BibTex]

Causal interpretation rules for encoding and decoding models in neuroimaging

Weichwald, S., Meyer, T., Özdenizci, O., Schölkopf, B., Ball, T., Grosse-Wentrup, M.

NeuroImage, 110, pages: 48–59, 2015 (article)

PDF Video Video-2 Arxiv DOI [BibTex]

Weichwald, S., Meyer, T., Özdenizci, O., Schölkopf, B., Ball, T., Grosse-Wentrup, M. Causal interpretation rules for encoding and decoding models in neuroimaging NeuroImage, 110, pages: 48–59, 2015 (article)

PDF Video Video-2 Arxiv DOI [BibTex]

Computing Functions of Random Variables via Reproducing Kernel Hilbert Space Representations

Schölkopf, B., Muandet, K., Fukumizu, K., Harmeling, S., Peters, J.

Statistics and Computing , 25(4):755-766, 2015 (article)

Schölkopf, B., Muandet, K., Fukumizu, K., Harmeling, S., Peters, J. Computing Functions of Random Variables via Reproducing Kernel Hilbert Space Representations Statistics and Computing , 25(4):755-766, 2015 (article)

Artificial intelligence: Learning to see and act

Schölkopf, B.

Nature, News & Views, 518(7540):486-487, 2015 (article)

Schölkopf, B. Artificial intelligence: Learning to see and act Nature, News & Views, 518(7540):486-487, 2015 (article)

Context affects lightness at the level of surfaces

Maertens, M., Wichmann, F., Shapley, R.

Journal of Vision, 15(1):1-15, 2015 (article)

Maertens, M., Wichmann, F., Shapley, R. Context affects lightness at the level of surfaces Journal of Vision, 15(1):1-15, 2015 (article)