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2017


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Interpolated Policy Gradient: Merging On-Policy and Off-Policy Gradient Estimation for Deep Reinforcement Learning

Gu, S., Lillicrap, T., Turner, R. E., Ghahramani, Z., Schölkopf, B., Levine, S.

Proceedings from the conference "Neural Information Processing Systems 2017., pages: 3849-3858, (Editors: Guyon I. and Luxburg U.v. and Bengio S. and Wallach H. and Fergus R. and Vishwanathan S. and Garnett R.), Curran Associates, Inc., Advances in Neural Information Processing Systems 30 (NIPS), December 2017 (conference)

link (url) [BibTex]

2017

link (url) [BibTex]


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Boosting Variational Inference: an Optimization Perspective

Locatello, F., Khanna, R., Ghosh, J., Rätsch, G.

Workshop: Advances in Approximate Bayesian Inference at the 31st Conference on Neural Information Processing Systems (NIPS), Curran Associates, Inc., Advances in Neural Information Processing Systems 30 (NIPS), December 2017 (conference)

link (url) [BibTex]

link (url) [BibTex]


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Learning Independent Causal Mechanisms

Parascandolo, G., Rojas-Carulla, M., Kilbertus, N., Schölkopf, B.

Workshop: Learning Disentangled Representations: from Perception to Control at the 31st Conference on Neural Information Processing Systems (NIPS), Curran Associates, Inc., Advances in Neural Information Processing Systems 30 (NIPS), December 2017 (conference)

link (url) [BibTex]

link (url) [BibTex]


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Avoiding Discrimination through Causal Reasoning

Kilbertus, N., Rojas-Carulla, M., Parascandolo, G., Hardt, M., Janzing, D., Schölkopf, B.

Proceedings from the conference "Neural Information Processing Systems 2017., pages: 656-666, (Editors: Guyon I. and Luxburg U.v. and Bengio S. and Wallach H. and Fergus R. and Vishwanathan S. and Garnett R.), Curran Associates, Inc., Advances in Neural Information Processing Systems 30 (NIPS), December 2017 (conference)

link (url) [BibTex]

link (url) [BibTex]


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Greedy Algorithms for Cone Constrained Optimization with Convergence Guarantees

Locatello, F., Tschannen, M., Rätsch, G., Jaggi, M.

Proceedings from the conference "Neural Information Processing Systems 2017., pages: 773-784, (Editors: Guyon I. and Luxburg U.v. and Bengio S. and Wallach H. and Fergus R. and Vishwanathan S. and Garnett R.), Curran Associates, Inc., Advances in Neural Information Processing Systems 30 (NIPS), December 2017 (conference)

link (url) [BibTex]

link (url) [BibTex]


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AdaGAN: Boosting Generative Models

Tolstikhin, I., Gelly, S., Bousquet, O., Simon-Gabriel, C. J., Schölkopf, B.

Proceedings from the conference "Neural Information Processing Systems 2017., pages: 5430-5439, (Editors: Guyon I. and Luxburg U.v. and Bengio S. and Wallach H. and Fergus R. and Vishwanathan S. and Garnett R.), Curran Associates, Inc., Advances in Neural Information Processing Systems 30 (NIPS), December 2017 (conference)

arXiv link (url) [BibTex]

arXiv link (url) [BibTex]


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Safe Adaptive Importance Sampling

Stich, S. U., Raj, A., Jaggi, M.

Proceedings from the conference "Neural Information Processing Systems 2017., pages: 4384-4394, (Editors: Guyon I. and Luxburg U.v. and Bengio S. and Wallach H. and Fergus R. and Vishwanathan S. and Garnett R.), Curran Associates, Inc., Advances in Neural Information Processing Systems 30 (NIPS), December 2017 (conference)

link (url) [BibTex]

link (url) [BibTex]


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ConvWave: Searching for Gravitational Waves with Fully Convolutional Neural Nets

Gebhard, T., Kilbertus, N., Parascandolo, G., Harry, I., Schölkopf, B.

Workshop on Deep Learning for Physical Sciences (DLPS) at the 31st Conference on Neural Information Processing Systems (NIPS), Curran Associates, Inc., Advances in Neural Information Processing Systems 30 (NIPS), December 2017 (conference)

link (url) [BibTex]

link (url) [BibTex]


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Online Video Deblurring via Dynamic Temporal Blending Network

Kim, T. H., Lee, K. M., Schölkopf, B., Hirsch, M.

Proceedings IEEE International Conference on Computer Vision (ICCV), pages: 4038-4047, IEEE, Piscataway, NJ, USA, IEEE International Conference on Computer Vision (ICCV), October 2017 (conference)

link (url) [BibTex]

link (url) [BibTex]


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EnhanceNet: Single Image Super-Resolution through Automated Texture Synthesis

Sajjadi, M. S. M., Schölkopf, B., Hirsch, M.

Proceedings IEEE International Conference on Computer Vision (ICCV), pages: 4501-4510, IEEE, Piscataway, NJ, USA, IEEE International Conference on Computer Vision (ICCV), October 2017 (conference)

Arxiv Project link (url) DOI [BibTex]

Arxiv Project link (url) DOI [BibTex]


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Learning Blind Motion Deblurring

Wieschollek, P., Hirsch, M., Schölkopf, B., Lensch, H.

Proceedings IEEE International Conference on Computer Vision (ICCV), pages: 231-240, IEEE, Piscataway, NJ, USA, IEEE International Conference on Computer Vision (ICCV), October 2017 (conference)

link (url) [BibTex]

link (url) [BibTex]


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Closing One’s Eyes Affects Amplitude Modulation but Not Frequency Modulation in a Cognitive BCI

Görner, M., Schölkopf, B., Grosse-Wentrup, M.

Proceedings of the 7th Graz Brain-Computer Interface Conference 2017 - From Vision to Reality, pages: 165-170, (Editors: Müller-Putz G.R., Steyrl D., Wriessnegger S. C., Scherer R.), Graz University of Technology, Austria, Graz Brain-Computer Interface Conference, September 2017 (conference)

DOI [BibTex]

DOI [BibTex]


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A Guided Task for Cognitive Brain-Computer Interfaces

Moser, J., Hohmann, M. R., Schölkopf, B., Grosse-Wentrup, M.

Proceedings of the 7th Graz Brain-Computer Interface Conference 2017 - From Vision to Reality, pages: 326-331, (Editors: Müller-Putz G.R., Steyrl D., Wriessnegger S. C., Scherer R.), Graz University of Technology, Austria, Graz Brain-Computer Interface Conference, September 2017 (conference)

DOI [BibTex]

DOI [BibTex]


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Bayesian Regression for Artifact Correction in Electroencephalography

Fiebig, K., Jayaram, V., Hesse, T., Blank, A., Peters, J., M., G.

Proceedings of the 7th Graz Brain-Computer Interface Conference 2017 - From Vision to Reality, pages: 131-136, (Editors: Müller-Putz G.R., Steyrl D., Wriessnegger S. C., Scherer R.), Graz University of Technology, Austria, Graz Brain-Computer Interface Conference, September 2017 (conference)

DOI [BibTex]

DOI [BibTex]


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Investigating Music Imagery as a Cognitive Paradigm for Low-Cost Brain-Computer Interfaces

Grossberger, L., Hohmann, M. R., Peters, J., M., G.

Proceedings of the 7th Graz Brain-Computer Interface Conference 2017 - From Vision to Reality, pages: 160-164, (Editors: Müller-Putz G.R., Steyrl D., Wriessnegger S. C., Scherer R.), Graz University of Technology, Austria, Graz Brain-Computer Interface Conference, September 2017 (conference)

DOI [BibTex]

DOI [BibTex]


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Correlations of Motor Adaptation Learning and Modulation of Resting-State Sensorimotor EEG Activity

Ozdenizci, O., Yalcin, M., Erdogan, A., Patoglu, V., Grosse-Wentrup, M., Cetin, M.

Proceedings of the 7th Graz Brain-Computer Interface Conference 2017 - From Vision to Reality, pages: 384-388, (Editors: Müller-Putz G.R., Steyrl D., Wriessnegger S. C., Scherer R.), Graz University of Technology, Austria, Graz Brain-Computer Interface Conference, September 2017 (conference)

DOI [BibTex]

DOI [BibTex]


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Local Bayesian Optimization of Motor Skills

Akrour, R., Sorokin, D., Peters, J., Neumann, G.

Proceedings of the 34th International Conference on Machine Learning, 70, pages: 41-50, Proceedings of Machine Learning Research, (Editors: Doina Precup, Yee Whye Teh), PMLR, International Conference on Machine Learning (ICML), August 2017 (conference)

link (url) [BibTex]

link (url) [BibTex]


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Sequence Tutor: Conservative fine-tuning of sequence generation models with KL-control

Jaques, N., Gu, S., Bahdanau, D., Hernández-Lobato, J. M., Turner, R. E., Eck, D.

Proceedings of the 34th International Conference on Machine Learning, 70, pages: 1645-1654, Proceedings of Machine Learning Research, (Editors: Doina Precup, Yee Whye Teh), PMLR, International Conference on Machine Learning (ICML), August 2017 (conference)

Arxiv link (url) [BibTex]

Arxiv link (url) [BibTex]


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Lost Relatives of the Gumbel Trick

Balog, M., Tripuraneni, N., Ghahramani, Z., Weller, A.

Proceedings of the 34th International Conference on Machine Learning, 70, pages: 371-379, Proceedings of Machine Learning Research, (Editors: Doina Precup, Yee Whye Teh), PMLR, International Conference on Machine Learning (ICML), August 2017 (conference)

Code link (url) [BibTex]

Code link (url) [BibTex]


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Approximate Steepest Coordinate Descent

Stich, S., Raj, A., Jaggi, M.

Proceedings of the 34th International Conference on Machine Learning, 70, pages: 3251-3259, Proceedings of Machine Learning Research, (Editors: Doina Precup, Yee Whye Teh), PMLR, International Conference on Machine Learning (ICML), August 2017 (conference)

link (url) [BibTex]

link (url) [BibTex]


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Causal Consistency of Structural Equation Models

Rubenstein*, P. K., Weichwald*, S., Bongers, S., Mooij, J. M., Janzing, D., Grosse-Wentrup, M., Schölkopf, B.

Proceedings of the 33rd Conference on Uncertainty in Artificial Intelligence (UAI), (Editors: Gal Elidan, Kristian Kersting, and Alexander T. Ihler), Association for Uncertainty in Artificial Intelligence (AUAI), Conference on Uncertainty in Artificial Intelligence (UAI), August 2017, *equal contribution (conference)

Arxiv link (url) [BibTex]

Arxiv link (url) [BibTex]


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Causal Discovery from Temporally Aggregated Time Series

Gong, M., Zhang, K., Schölkopf, B., Glymour, C., Tao, D.

Proceedings Conference on Uncertainty in Artificial Intelligence (UAI) 2017, pages: ID 269, (Editors: Gal Elidan, Kristian Kersting, and Alexander T. Ihler), Association for Uncertainty in Artificial Intelligence (AUAI), Conference on Uncertainty in Artificial Intelligence (UAI), August 2017 (conference)

link (url) [BibTex]

link (url) [BibTex]


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Flexible Spatio-Temporal Networks for Video Prediction

Lu, C., Hirsch, M., Schölkopf, B.

Proceedings IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 2017, pages: 2137-2145, IEEE, Piscataway, NJ, USA, IEEE Conference on Computer Vision and Pattern Recognition (CVPR), July 2017 (conference)

link (url) DOI [BibTex]

link (url) DOI [BibTex]


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Discovering Causal Signals in Images

Lopez-Paz, D., Nishihara, R., Chintala, S., Schölkopf, B., Bottou, L.

Proceedings IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 2017, pages: 58-66, IEEE, Piscataway, NJ, USA, IEEE Conference on Computer Vision and Pattern Recognition (CVPR), July 2017 (conference)

link (url) DOI [BibTex]

link (url) DOI [BibTex]


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Dynamic Time-of-Flight

Schober, M., Adam, A., Yair, O., Mazor, S., Nowozin, S.

Proceedings IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 2017, pages: 170-179, IEEE, Piscataway, NJ, USA, IEEE Conference on Computer Vision and Pattern Recognition (CVPR), July 2017 (conference)

DOI [BibTex]

DOI [BibTex]


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Ecological feedback in quorum-sensing microbial populations can induce heterogeneous production of autoinducers

Bauer*, M., Knebel*, J., Lechner, M., Pickl, P., Frey, E.

{eLife}, July 2017, *equal contribution (article)

DOI [BibTex]

DOI [BibTex]


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Deep Reinforcement Learning for Robotic Manipulation with Asynchronous Off-Policy Updates

Gu*, S., Holly*, E., Lillicrap, T., Levine, S.

Proceedings 2017 IEEE International Conference on Robotics and Automation (ICRA), IEEE, Piscataway, NJ, USA, IEEE International Conference on Robotics and Automation (ICRA), May 2017, *equal contribution (conference)

Arxiv [BibTex]

Arxiv [BibTex]


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Q-Prop: Sample-Efficient Policy Gradient with An Off-Policy Critic

Gu, S., Lillicrap, T., Ghahramani, Z., Turner, R. E., Levine, S.

Proceedings International Conference on Learning Representations (ICLR), OpenReviews.net, International Conference on Learning Representations, April 2017 (conference)

PDF link (url) [BibTex]

PDF link (url) [BibTex]


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Categorical Reparametrization with Gumble-Softmax

Jang, E., Gu, S., Poole, B.

Proceedings International Conference on Learning Representations 2017, OpenReviews.net, International Conference on Learning Representations, April 2017 (conference)

link (url) [BibTex]

link (url) [BibTex]


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DeepCoder: Learning to Write Programs

Balog, M., Gaunt, A. L., Brockschmidt, M., Nowozin, S., Tarlow, D.

Proceedings International Conference on Learning Representations 2017, OpenReviews.net, International Conference on Learning Representations, April 2017 (conference)

Arxiv link (url) [BibTex]

Arxiv link (url) [BibTex]


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Model-based Contextual Policy Search for Data-Efficient Generalization of Robot Skills

Kupcsik, A., Deisenroth, M., Peters, J., Ai Poh, L., Vadakkepat, V., Neumann, G.

Artificial Intelligence, 247, pages: 415-439, 2017, Special Issue on AI and Robotics (article)

link (url) DOI [BibTex]

link (url) DOI [BibTex]


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Anticipatory Action Selection for Human-Robot Table Tennis

Wang, Z., Boularias, A., Mülling, K., Schölkopf, B., Peters, J.

Artificial Intelligence, 247, pages: 399-414, 2017, Special Issue on AI and Robotics (article)

Abstract
Abstract Anticipation can enhance the capability of a robot in its interaction with humans, where the robot predicts the humans' intention for selecting its own action. We present a novel framework of anticipatory action selection for human-robot interaction, which is capable to handle nonlinear and stochastic human behaviors such as table tennis strokes and allows the robot to choose the optimal action based on prediction of the human partner's intention with uncertainty. The presented framework is generic and can be used in many human-robot interaction scenarios, for example, in navigation and human-robot co-manipulation. In this article, we conduct a case study on human-robot table tennis. Due to the limited amount of time for executing hitting movements, a robot usually needs to initiate its hitting movement before the opponent hits the ball, which requires the robot to be anticipatory based on visual observation of the opponent's movement. Previous work on Intention-Driven Dynamics Models (IDDM) allowed the robot to predict the intended target of the opponent. In this article, we address the problem of action selection and optimal timing for initiating a chosen action by formulating the anticipatory action selection as a Partially Observable Markov Decision Process (POMDP), where the transition and observation are modeled by the \{IDDM\} framework. We present two approaches to anticipatory action selection based on the \{POMDP\} formulation, i.e., a model-free policy learning method based on Least-Squares Policy Iteration (LSPI) that employs the \{IDDM\} for belief updates, and a model-based Monte-Carlo Planning (MCP) method, which benefits from the transition and observation model by the IDDM. Experimental results using real data in a simulated environment show the importance of anticipatory action selection, and that \{POMDPs\} are suitable to formulate the anticipatory action selection problem by taking into account the uncertainties in prediction. We also show that existing algorithms for POMDPs, such as \{LSPI\} and MCP, can be applied to substantially improve the robot's performance in its interaction with humans.

DOI [BibTex]

DOI [BibTex]


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easyGWAS: A Cloud-based Platform for Comparing the Results of Genome-wide Association Studies

Grimm, D., Roqueiro, D., Salome, P., Kleeberger, S., Greshake, B., Zhu, W., Liu, C., Lippert, C., Stegle, O., Schölkopf, B., Weigel, D., Borgwardt, K.

The Plant Cell, 29(1):5-19, 2017 (article)

link (url) DOI [BibTex]

link (url) DOI [BibTex]


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A Novel Unsupervised Segmentation Approach Quantifies Tumor Tissue Populations Using Multiparametric MRI: First Results with Histological Validation

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

Molecular Imaging and Biology, 19(3):391-397, 2017 (article)

DOI [BibTex]

DOI [BibTex]


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Elements of Causal Inference - Foundations and Learning Algorithms

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

Adaptive Computation and Machine Learning Series, The MIT Press, Cambridge, MA, USA, 2017 (book)

PDF [BibTex]

PDF [BibTex]


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Minimax Estimation of Kernel Mean Embeddings

Tolstikhin, I., Sriperumbudur, B., Muandet, K.

Journal of Machine Learning Research, 18(86):1-47, 2017 (article)

link (url) [BibTex]

link (url) [BibTex]


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Kernel Mean Embedding of Distributions: A Review and Beyond

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

Foundations and Trends in Machine Learning, 10(1-2):1-141, 2017 (article)

DOI [BibTex]

DOI [BibTex]


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Case Series: Slowing Alpha Rhythm in Late-Stage ALS Patients

Hohmann, M. R., Fomina, T., Jayaram, V., Emde, T., Just, J., Synofzik, M., Schölkopf, B., Schöls, L., Grosse-Wentrup, M.

Clinical Neurophysiology, 129(2):406-408, 2017 (article)

link (url) DOI [BibTex]

link (url) DOI [BibTex]


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Pre-Movement Contralateral EEG Low Beta Power Is Modulated with Motor Adaptation Learning

Ozdenizci, O., Yalcin, M., Erdogan, A., Patoglu, V., Grosse-Wentrup, M., Cetin, M.

International Conference on Acoustics, Speech and Signal Processing (ICASSP), pages: 934-938, 2017 (conference)

DOI [BibTex]

DOI [BibTex]


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Spectral Clustering predicts tumor tissue heterogeneity using dynamic 18F-FDG PET: a complement to the standard compartmental modeling approach

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

Journal of Nuclear Medicine, 58(4):651-657, 2017 (article)

link (url) DOI [BibTex]

link (url) DOI [BibTex]


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Electroencephalographic identifiers of motor adaptation learning

Ozdenizci, O., Yalcin, M., Erdogan, A., Patoglu, V., Grosse-Wentrup, M., Cetin, M.

Journal of Neural Engineering, 14(4):046027, 2017 (article)

link (url) [BibTex]

link (url) [BibTex]


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Detecting distortions of peripherally presented letter stimuli under crowded conditions

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

Attention, Perception, & Psychophysics, 79(3):850-862, 2017 (article)

DOI [BibTex]

DOI [BibTex]


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Automatic detection of motion artifacts in MR images using CNNS

Meding, K., Loktyushin, A., Hirsch, M.

IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2017), pages: 811-815, 2017 (conference)

DOI [BibTex]

DOI [BibTex]


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Discriminative k-shot learning using probabilistic models

Bauer*, M., Rojas-Carulla*, M., Świątkowski, J. B., Schölkopf, B., Turner, R. E.

Second Workshop on Bayesian Deep Learning at the 31st Conference on Neural Information Processing Systems (NIPS) , 2017, *equal contribution (conference)

link (url) [BibTex]

link (url) [BibTex]


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Personalized Brain-Computer Interface Models for Motor Rehabilitation

Mastakouri, A., Weichwald, S., Ozdenizci, O., Meyer, T., Schölkopf, B., Grosse-Wentrup, M.

Proceedings of the IEEE International Conference on Systems, Man, and Cybernetics (SMC), pages: 3024-3029, 2017 (conference)

PDF DOI [BibTex]

PDF DOI [BibTex]


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Distilling Information Reliability and Source Trustworthiness from Digital Traces

Tabibian, B., Valera, I., Farajtabar, M., Song, L., Schölkopf, B., Gomez Rodriguez, M.

Proceedings of the 26th International Conference on World Wide Web (WWW), pages: 847-855, (Editors: Barrett, R., Cummings, R., Agichtein, E. and Gabrilovich, E. ), ACM, 2017 (conference)

Project DOI [BibTex]

Project DOI [BibTex]


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Causal Discovery from Nonstationary/Heterogeneous Data: Skeleton Estimation and Orientation Determination

Zhang, K., Huang, B., Zhang, J., Glymour, C., Schölkopf, B.

Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence (IJCAI), pages: 1347-1353, (Editors: Carles Sierra), 2017 (conference)

PDF DOI [BibTex]

PDF DOI [BibTex]


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Behind Distribution Shift: Mining Driving Forces of Changes and Causal Arrows

Huang, B., Zhang, K., Zhang, J., Sanchez-Romero, R., Glymour, C., Schölkopf, B.

IEEE 17th International Conference on Data Mining (ICDM), pages: 913-918, (Editors: Vijay Raghavan,Srinivas Aluru, George Karypis, Lucio Miele and Xindong Wu), 2017 (conference)

DOI [BibTex]

DOI [BibTex]