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)

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)

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)

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]

Inferring causation from time series with perspectives in Earth system sciences

Nature Communications, 2019 (article) In revision

[BibTex]

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

[BibTex]

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)

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)

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)

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)

2016

Contextual Policy Search for Linear and Nonlinear Generalization of a Humanoid Walking Controller

Abdolmaleki, A., Lau, N., Reis, L., Peters, J., Neumann, G.

Journal of Intelligent & Robotic Systems, 83(3-4):393-408, (Editors: Luis Almeida, Lino Marques ), September 2016, Special Issue: Autonomous Robot Systems (article)

2016

Abdolmaleki, A., Lau, N., Reis, L., Peters, J., Neumann, G. Contextual Policy Search for Linear and Nonlinear Generalization of a Humanoid Walking Controller Journal of Intelligent & Robotic Systems, 83(3-4):393-408, (Editors: Luis Almeida, Lino Marques ), September 2016, Special Issue: Autonomous Robot Systems (article)

Acquiring and Generalizing the Embodiment Mapping from Human Observations to Robot Skills

Maeda, G., Ewerton, M., Koert, D., Peters, J.

IEEE Robotics and Automation Letters, 1(2):784-791, July 2016 (article)

Maeda, G., Ewerton, M., Koert, D., Peters, J. Acquiring and Generalizing the Embodiment Mapping from Human Observations to Robot Skills IEEE Robotics and Automation Letters, 1(2):784-791, July 2016 (article)

On estimation of functional causal models: General results and application to post-nonlinear causal model

Zhang, K., Wang, Z., Zhang, J., Schölkopf, B.

ACM Transactions on Intelligent Systems and Technologies, 7(2):article no. 13, January 2016 (article)

Zhang, K., Wang, Z., Zhang, J., Schölkopf, B. On estimation of functional causal models: General results and application to post-nonlinear causal model ACM Transactions on Intelligent Systems and Technologies, 7(2):article no. 13, January 2016 (article)

Gaussian Process-Based Predictive Control for Periodic Error Correction

Klenske, E. D., Zeilinger, M., Schölkopf, B., Hennig, P.

IEEE Transactions on Control Systems Technology , 24(1):110-121, 2016 (article)

Klenske, E. D., Zeilinger, M., Schölkopf, B., Hennig, P. Gaussian Process-Based Predictive Control for Periodic Error Correction IEEE Transactions on Control Systems Technology , 24(1):110-121, 2016 (article)

Pymanopt: A Python Toolbox for Optimization on Manifolds using Automatic Differentiation

Townsend, J., Koep, N., Weichwald, S.

Journal of Machine Learning Research, 17(137):1-5, 2016 (article)

PDF Arxiv Code Project page link (url) [BibTex]

Townsend, J., Koep, N., Weichwald, S. Pymanopt: A Python Toolbox for Optimization on Manifolds using Automatic Differentiation Journal of Machine Learning Research, 17(137):1-5, 2016 (article)

PDF Arxiv Code Project page link (url) [BibTex]

A Causal, Data-driven Approach to Modeling the Kepler Data

Wang, D., Hogg, D. W., Foreman-Mackey, D., Schölkopf, B.

Publications of the Astronomical Society of the Pacific, 128(967):094503, 2016 (article)

Wang, D., Hogg, D. W., Foreman-Mackey, D., Schölkopf, B. A Causal, Data-driven Approach to Modeling the Kepler Data Publications of the Astronomical Society of the Pacific, 128(967):094503, 2016 (article)

Probabilistic Inference for Determining Options in Reinforcement Learning

Daniel, C., van Hoof, H., Peters, J., Neumann, G.

Machine Learning, Special Issue, 104(2):337-357, (Editors: Gärtner, T., Nanni, M., Passerini, A. and Robardet, C.), European Conference on Machine Learning im Machine Learning, Journal Track, 2016, Best Student Paper Award of ECML-PKDD 2016 (article)

Daniel, C., van Hoof, H., Peters, J., Neumann, G. Probabilistic Inference for Determining Options in Reinforcement Learning Machine Learning, Special Issue, 104(2):337-357, (Editors: Gärtner, T., Nanni, M., Passerini, A. and Robardet, C.), European Conference on Machine Learning im Machine Learning, Journal Track, 2016, Best Student Paper Award of ECML-PKDD 2016 (article)

Influence of initial fixation position in scene viewing

Rothkegel, L. O. M., Trukenbrod, H. A., Schütt, H. H., Wichmann, F. A., Engbert, R.

Vision Research, 129, pages: 33-49, 2016 (article)

Rothkegel, L. O. M., Trukenbrod, H. A., Schütt, H. H., Wichmann, F. A., Engbert, R. Influence of initial fixation position in scene viewing Vision Research, 129, pages: 33-49, 2016 (article)

Testing models of peripheral encoding using metamerism in an oddity paradigm

Wallis, T. S. A., Bethge, M., Wichmann, F. A.

Journal of Vision, 16(2), 2016 (article)

Wallis, T. S. A., Bethge, M., Wichmann, F. A. Testing models of peripheral encoding using metamerism in an oddity paradigm Journal of Vision, 16(2), 2016 (article)

Code link (url) DOI Project Page [BibTex]

Modeling Confounding by Half-Sibling Regression

Schölkopf, B., Hogg, D., Wang, D., Foreman-Mackey, D., Janzing, D., Simon-Gabriel, C. J., Peters, J.

Proceedings of the National Academy of Science, 113(27):7391-7398, 2016 (article)

Schölkopf, B., Hogg, D., Wang, D., Foreman-Mackey, D., Janzing, D., Simon-Gabriel, C. J., Peters, J. Modeling Confounding by Half-Sibling Regression Proceedings of the National Academy of Science, 113(27):7391-7398, 2016 (article)

Code link (url) DOI Project Page [BibTex]

Dual Control for Approximate Bayesian Reinforcement Learning

Klenske, E. D., Hennig, P.

Journal of Machine Learning Research, 17(127):1-30, 2016 (article)

PDF link (url) [BibTex]

Klenske, E. D., Hennig, P. Dual Control for Approximate Bayesian Reinforcement Learning Journal of Machine Learning Research, 17(127):1-30, 2016 (article)

PDF link (url) [BibTex]

A Population Based Gaussian Mixture Model Incorporating 18F-FDG-PET and DW-MRI Quantifies Tumor Tissue Classes

Divine, M. R., Katiyar, P., Kohlhofer, U., Quintanilla-Martinez, L., Disselhorst, J. A., Pichler, B. J.

Journal of Nuclear Medicine, 57(3):473-479, 2016 (article)

Divine, M. R., Katiyar, P., Kohlhofer, U., Quintanilla-Martinez, L., Disselhorst, J. A., Pichler, B. J. A Population Based Gaussian Mixture Model Incorporating 18F-FDG-PET and DW-MRI Quantifies Tumor Tissue Classes Journal of Nuclear Medicine, 57(3):473-479, 2016 (article)

Comparison of Positron Emission Tomography Quantification Using Magnetic Resonance–and Computed Tomography–Based Attenuation Correction in Physiological Tissues and Lesions: A Whole-Body Positron Emission Tomography/Magnetic Resonance Study in 66 Patients

Seith, F., Gatidis, S., Schmidt, H., Bezrukov, I., la Fougère, C., Nikolaou, K., Pfannenberg, C., Schwenzer, N.

Investigative Radiology, 51(1):66-71, 2016 (article)

Seith, F., Gatidis, S., Schmidt, H., Bezrukov, I., la Fougère, C., Nikolaou, K., Pfannenberg, C., Schwenzer, N. Comparison of Positron Emission Tomography Quantification Using Magnetic Resonance–and Computed Tomography–Based Attenuation Correction in Physiological Tissues and Lesions: A Whole-Body Positron Emission Tomography/Magnetic Resonance Study in 66 Patients Investigative Radiology, 51(1):66-71, 2016 (article)

link (url) Project Page Project Page [BibTex]

Estimating Diffusion Networks: Recovery Conditions, Sample Complexity and Soft-thresholding Algorithm

Gomez Rodriguez, M., Song, L., Daneshmand, H., Schölkopf, B.

Journal of Machine Learning Research, 17(90):1-29, 2016 (article)

Gomez Rodriguez, M., Song, L., Daneshmand, H., Schölkopf, B. Estimating Diffusion Networks: Recovery Conditions, Sample Complexity and Soft-thresholding Algorithm Journal of Machine Learning Research, 17(90):1-29, 2016 (article)

link (url) Project Page Project Page [BibTex]

Analysis of multiparametric MRI using a semi-supervised random forest framework allows the detection of therapy response in ischemic stroke

Castaneda, S., Katiyar, P., Russo, F., Calaminus, C., Disselhorst, J. A., Ziemann, U., Kohlhofer, U., Quintanilla-Martinez, L., Poli, S., Pichler, B. J.

World Molecular Imaging Conference, 2016 (talk)

Castaneda, S., Katiyar, P., Russo, F., Calaminus, C., Disselhorst, J. A., Ziemann, U., Kohlhofer, U., Quintanilla-Martinez, L., Poli, S., Pichler, B. J. Analysis of multiparametric MRI using a semi-supervised random forest framework allows the detection of therapy response in ischemic stroke World Molecular Imaging Conference, 2016 (talk)

Painfree and accurate Bayesian estimation of psychometric functions for (potentially) overdispersed data

Schütt, H. H., Harmeling, S., Macke, J. H., Wichmann, F. A.

Vision Research, 122, pages: 105-123, 2016 (article)

Schütt, H. H., Harmeling, S., Macke, J. H., Wichmann, F. A. Painfree and accurate Bayesian estimation of psychometric functions for (potentially) overdispersed data Vision Research, 122, pages: 105-123, 2016 (article)

Identification of causal relations in neuroimaging data with latent confounders: An instrumental variable approach

Grosse-Wentrup, M., Janzing, D., Siegel, M., Schölkopf, B.

NeuroImage, 125, pages: 825-833, 2016 (article)

Grosse-Wentrup, M., Janzing, D., Siegel, M., Schölkopf, B. Identification of causal relations in neuroimaging data with latent confounders: An instrumental variable approach NeuroImage, 125, pages: 825-833, 2016 (article)

Hierarchical Relative Entropy Policy Search

Daniel, C., Neumann, G., Kroemer, O., Peters, J.

Journal of Machine Learning Research, 17(93):1-50, 2016 (article)

Daniel, C., Neumann, G., Kroemer, O., Peters, J. Hierarchical Relative Entropy Policy Search Journal of Machine Learning Research, 17(93):1-50, 2016 (article)

Kernel Mean Shrinkage Estimators

Muandet, K., Sriperumbudur, B., Fukumizu, K., Gretton, A., Schölkopf, B.

Journal of Machine Learning Research, 17(48):1-41, 2016 (article)

Muandet, K., Sriperumbudur, B., Fukumizu, K., Gretton, A., Schölkopf, B. Kernel Mean Shrinkage Estimators Journal of Machine Learning Research, 17(48):1-41, 2016 (article)

Learning to Deblur

Schuler, C. J., Hirsch, M., Harmeling, S., Schölkopf, B.

IEEE Transactions on Pattern Analysis and Machine Intelligence, 38(7):1439-1451, IEEE, 2016 (article)

Schuler, C. J., Hirsch, M., Harmeling, S., Schölkopf, B. Learning to Deblur IEEE Transactions on Pattern Analysis and Machine Intelligence, 38(7):1439-1451, IEEE, 2016 (article)

Transfer Learning in Brain-Computer Interfaces

Jayaram, V., Alamgir, M., Altun, Y., Schölkopf, B., Grosse-Wentrup, M.

IEEE Computational Intelligence Magazine, 11(1):20-31, 2016 (article)

Jayaram, V., Alamgir, M., Altun, Y., Schölkopf, B., Grosse-Wentrup, M. Transfer Learning in Brain-Computer Interfaces IEEE Computational Intelligence Magazine, 11(1):20-31, 2016 (article)

MERLiN: Mixture Effect Recovery in Linear Networks

Weichwald, S., Grosse-Wentrup, M., Gretton, A.

IEEE Journal of Selected Topics in Signal Processing, 10(7):1254-1266, 2016 (article)

Arxiv Code PDF DOI Project Page [BibTex]

Weichwald, S., Grosse-Wentrup, M., Gretton, A. MERLiN: Mixture Effect Recovery in Linear Networks IEEE Journal of Selected Topics in Signal Processing, 10(7):1254-1266, 2016 (article)

Arxiv Code PDF DOI Project Page [BibTex]

Causal inference using invariant prediction: identification and confidence intervals

Peters, J., Bühlmann, P., Meinshausen, N.

Journal of the Royal Statistical Society, Series B (Statistical Methodology), 78(5):947-1012, 2016, (with discussion) (article)

Peters, J., Bühlmann, P., Meinshausen, N. Causal inference using invariant prediction: identification and confidence intervals Journal of the Royal Statistical Society, Series B (Statistical Methodology), 78(5):947-1012, 2016, (with discussion) (article)

Causal discovery and inference: concepts and recent methodological advances

Spirtes, P., Zhang, K.

Applied Informatics, 3(3):1-28, 2016 (article)

Spirtes, P., Zhang, K. Causal discovery and inference: concepts and recent methodological advances Applied Informatics, 3(3):1-28, 2016 (article)

Self-regulation of brain rhythms in the precuneus: a novel BCI paradigm for patients with ALS

Fomina, T., Lohmann, G., Erb, M., Ethofer, T., Schölkopf, B., Grosse-Wentrup, M.

Journal of Neural Engineering, 13(6):066021, 2016 (article)

Fomina, T., Lohmann, G., Erb, M., Ethofer, T., Schölkopf, B., Grosse-Wentrup, M. Self-regulation of brain rhythms in the precuneus: a novel BCI paradigm for patients with ALS Journal of Neural Engineering, 13(6):066021, 2016 (article)

Influence Estimation and Maximization in Continuous-Time Diffusion Networks

Gomez-Rodriguez, M., Song, L., Du, N., Zha, H., Schölkopf, B.

ACM Transactions on Information Systems, 34(2):9:1-9:33, 2016 (article)

Gomez-Rodriguez, M., Song, L., Du, N., Zha, H., Schölkopf, B. Influence Estimation and Maximization in Continuous-Time Diffusion Networks ACM Transactions on Information Systems, 34(2):9:1-9:33, 2016 (article)

Zwischen Harmonie und Chaos - ein verallgemeinertes Modell des Doppelpendels

Stimper, V.

Junge Wissenschaft, (109), 2016 (article)

Stimper, V. Zwischen Harmonie und Chaos - ein verallgemeinertes Modell des Doppelpendels Junge Wissenschaft, (109), 2016 (article)

The population of long-period transiting exoplanets

Foreman-Mackey, D., Morton, T. D., Hogg, D. W., Agol, E., Schölkopf, B.

The Astronomical Journal, 152(6):206, 2016 (article)

Foreman-Mackey, D., Morton, T. D., Hogg, D. W., Agol, E., Schölkopf, B. The population of long-period transiting exoplanets The Astronomical Journal, 152(6):206, 2016 (article)

An overview of quantitative approaches in Gestalt perception

Jäkel, F., Singh, M., Wichmann, F. A., Herzog, M. H.

Vision Research, 126, pages: 3-8, 2016 (article)

Jäkel, F., Singh, M., Wichmann, F. A., Herzog, M. H. An overview of quantitative approaches in Gestalt perception Vision Research, 126, pages: 3-8, 2016 (article)

Bootstrat: Population Informed Bootstrapping for Rare Variant Tests

Huang, H., Peloso, G. M., Howrigan, D., Rakitsch, B., Simon-Gabriel, C. J., Goldstein, J. I., Daly, M. J., Borgwardt, K., Neale, B. M.

bioRxiv, 2016, preprint (article)

Huang, H., Peloso, G. M., Howrigan, D., Rakitsch, B., Simon-Gabriel, C. J., Goldstein, J. I., Daly, M. J., Borgwardt, K., Neale, B. M. Bootstrat: Population Informed Bootstrapping for Rare Variant Tests bioRxiv, 2016, preprint (article)

Probabilistic Movement Models Show that Postural Control Precedes and Predicts Volitional Motor Control

Rueckert, E., Camernik, J., Peters, J., Babic, J.

Nature PG: Scientific Reports, 6(Article number: 28455), 2016 (article)

Rueckert, E., Camernik, J., Peters, J., Babic, J. Probabilistic Movement Models Show that Postural Control Precedes and Predicts Volitional Motor Control Nature PG: Scientific Reports, 6(Article number: 28455), 2016 (article)

Distinguishing cause from effect using observational data: methods and benchmarks

Mooij, J., Peters, J., Janzing, D., Zscheischler, J., Schölkopf, B.

Journal of Machine Learning Research, 17(32):1-102, 2016 (article)

Mooij, J., Peters, J., Janzing, D., Zscheischler, J., Schölkopf, B. Distinguishing cause from effect using observational data: methods and benchmarks Journal of Machine Learning Research, 17(32):1-102, 2016 (article)

Learning Taxonomy Adaptation in Large-scale Classification

Babbar, R., Partalas, I., Gaussier, E., Amini, M., Amblard, C.

Journal of Machine Learning Research, 17(98):1-37, 2016 (article)

Babbar, R., Partalas, I., Gaussier, E., Amini, M., Amblard, C. Learning Taxonomy Adaptation in Large-scale Classification Journal of Machine Learning Research, 17(98):1-37, 2016 (article)

Algorithmic independence of initial condition and dynamical law in thermodynamics and causal inference

Janzing, D., Chaves, R., Schölkopf, B.

New Journal of Phyiscs, 18(9):093052, 2016 (article)

PDF link (url) DOI [BibTex]

Janzing, D., Chaves, R., Schölkopf, B. Algorithmic independence of initial condition and dynamical law in thermodynamics and causal inference New Journal of Phyiscs, 18(9):093052, 2016 (article)

PDF link (url) DOI [BibTex]

Multi-view learning on multiparametric PET/MRI quantifies intratumoral heterogeneity and determines therapy efficacy

Katiyar, P., Divine, M. R., Kohlhofer, U., Quintanilla-Martinez, L., Siegemund, M., Pfizenmaier, K., Kontermann, R., Pichler, B. J., Disselhorst, J. A.

World Molecular Imaging Conference, 2016 (talk)

Katiyar, P., Divine, M. R., Kohlhofer, U., Quintanilla-Martinez, L., Siegemund, M., Pfizenmaier, K., Kontermann, R., Pichler, B. J., Disselhorst, J. A. Multi-view learning on multiparametric PET/MRI quantifies intratumoral heterogeneity and determines therapy efficacy World Molecular Imaging Conference, 2016 (talk)

BOiS—Berlin Object in Scene Database: Controlled Photographic Images for Visual Search Experiments with Quantified Contextual Priors

Mohr, J., Seyfarth, J., Lueschow, A., Weber, J. E., Wichmann, F. A., Obermayer, K.

Frontiers in Psychology, 2016 (article)

Mohr, J., Seyfarth, J., Lueschow, A., Weber, J. E., Wichmann, F. A., Obermayer, K. BOiS—Berlin Object in Scene Database: Controlled Photographic Images for Visual Search Experiments with Quantified Contextual Priors Frontiers in Psychology, 2016 (article)

Preface to the ACM TIST Special Issue on Causal Discovery and Inference

Zhang, K., Li, J., Bareinboim, E., Schölkopf, B., Pearl, J.

ACM Transactions on Intelligent Systems and Technologies, 7(2):article no. 17, 2016 (article)

Zhang, K., Li, J., Bareinboim, E., Schölkopf, B., Pearl, J. Preface to the ACM TIST Special Issue on Causal Discovery and Inference ACM Transactions on Intelligent Systems and Technologies, 7(2):article no. 17, 2016 (article)

Recurrent Spiking Networks Solve Planning Tasks

Rueckert, E., Kappel, D., Tanneberg, D., Pecevski, D., Peters, J.

Nature PG: Scientific Reports, 6(Article number: 21142), 2016 (article)

Rueckert, E., Kappel, D., Tanneberg, D., Pecevski, D., Peters, J. Recurrent Spiking Networks Solve Planning Tasks Nature PG: Scientific Reports, 6(Article number: 21142), 2016 (article)

Bio-inspired feedback-circuit implementation of discrete, free energy optimizing, winner-take-all computations

Genewein, T, Braun, DA

Biological Cybernetics, 110(2):135–150, June 2016 (article)

Abstract

Bayesian inference and bounded rational decision-making require the accumulation of evidence or utility, respectively, to transform a prior belief or strategy into a posterior probability distribution over hypotheses or actions. Crucially, this process cannot be simply realized by independent integrators, since the different hypotheses and actions also compete with each other. In continuous time, this competitive integration process can be described by a special case of the replicator equation. Here we investigate simple analog electric circuits that implement the underlying differential equation under the constraint that we only permit a limited set of building blocks that we regard as biologically interpretable, such as capacitors, resistors, voltage-dependent conductances and voltage- or current-controlled current and voltage sources. The appeal of these circuits is that they intrinsically perform normalization without requiring an explicit divisive normalization. However, even in idealized simulations, we find that these circuits are very sensitive to internal noise as they accumulate error over time. We discuss in how far neural circuits could implement these operations that might provide a generic competitive principle underlying both perception and action.

Genewein, T, Braun, DA Bio-inspired feedback-circuit implementation of discrete, free energy optimizing, winner-take-all computations Biological Cybernetics, 110(2):135–150, June 2016 (article)