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Pyfectious: An individual-level simulator to discover optimal containment polices for epidemic diseases


Mar 24, 2021
Arash Mehrjou, Ashkan Soleymani, Amin Abyaneh, Bernhard Schölkopf, Stefan Bauer


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A prior-based approximate latent Riemannian metric


Mar 09, 2021
Georgios Arvanitidis, Bogdan Georgiev, Bernhard Schölkopf


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From Majorization to Interpolation: Distributionally Robust Learning using Kernel Smoothing


Mar 04, 2021
Jia-Jie Zhu, Yassine Nemmour, Bernhard Schölkopf


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Learning with Hyperspherical Uniformity


Mar 02, 2021
Weiyang Liu, Rongmei Lin, Zhen Liu, Li Xiong, Bernhard Schölkopf, Adrian Weller

* AISTATS 2021 

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Nonlinear Invariant Risk Minimization: A Causal Approach


Feb 24, 2021
Chaochao Lu, Yuhuai Wu, Jośe Miguel Hernández-Lobato, Bernhard Schölkopf


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Towards Causal Representation Learning


Feb 22, 2021
Bernhard Schölkopf, Francesco Locatello, Stefan Bauer, Nan Rosemary Ke, Nal Kalchbrenner, Anirudh Goyal, Yoshua Bengio

* Special Issue of Proceedings of the IEEE - Advances in Machine Learning and Deep Neural Networks 

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Conditional Distributional Treatment Effect with Kernel Conditional Mean Embeddings and U-Statistic Regression


Feb 16, 2021
Junhyung Park, Uri Shalit, Bernhard Schölkopf, Krikamol Muandet


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Bayesian Quadrature on Riemannian Data Manifolds


Feb 12, 2021
Christian Fröhlich, Alexandra Gessner, Philipp Hennig, Bernhard Schölkopf, Georgios Arvanitidis


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An Optimal Witness Function for Two-Sample Testing


Feb 10, 2021
Jonas M. Kübler, Wittawat Jitkrittum, Bernhard Schölkopf, Krikamol Muandet

* Under Review - Code available upon personal request 

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Sample-Efficient Reinforcement Learning via Counterfactual-Based Data Augmentation


Dec 16, 2020
Chaochao Lu, Biwei Huang, Ke Wang, José Miguel Hernández-Lobato, Kun Zhang, Bernhard Schölkopf

* Neural Information Processing Systems Workshop on Offline Reinforcement Learning 

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COVI-AgentSim: an Agent-based Model for Evaluating Methods of Digital Contact Tracing


Oct 30, 2020
Prateek Gupta, Tegan Maharaj, Martin Weiss, Nasim Rahaman, Hannah Alsdurf, Abhinav Sharma, Nanor Minoyan, Soren Harnois-Leblanc, Victor Schmidt, Pierre-Luc St. Charles, Tristan Deleu, Andrew Williams, Akshay Patel, Meng Qu, Olexa Bilaniuk, Gaétan Marceau Caron, Pierre Luc Carrier, Satya Ortiz-Gagné, Marc-Andre Rousseau, David Buckeridge, Joumana Ghosn, Yang Zhang, Bernhard Schölkopf, Jian Tang, Irina Rish, Christopher Pal, Joanna Merckx, Eilif B. Muller, Yoshua Bengio


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On the Transfer of Disentangled Representations in Realistic Settings


Oct 27, 2020
Andrea Dittadi, Frederik Träuble, Francesco Locatello, Manuel Wüthrich, Vaibhav Agrawal, Ole Winther, Stefan Bauer, Bernhard Schölkopf


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A Sober Look at the Unsupervised Learning of Disentangled Representations and their Evaluation


Oct 27, 2020
Francesco Locatello, Stefan Bauer, Mario Lucic, Gunnar Rätsch, Sylvain Gelly, Bernhard Schölkopf, Olivier Bachem

* Journal of Machine Learning Research 2020, Volume 21, Number 209 
* arXiv admin note: substantial text overlap with arXiv:1811.12359 

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Predicting Infectiousness for Proactive Contact Tracing


Oct 23, 2020
Yoshua Bengio, Prateek Gupta, Tegan Maharaj, Nasim Rahaman, Martin Weiss, Tristan Deleu, Eilif Muller, Meng Qu, Victor Schmidt, Pierre-Luc St-Charles, Hannah Alsdurf, Olexa Bilanuik, David Buckeridge, Gáetan Marceau Caron, Pierre-Luc Carrier, Joumana Ghosn, Satya Ortiz-Gagne, Chris Pal, Irina Rish, Bernhard Schölkopf, Abhinav Sharma, Jian Tang, Andrew Williams


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Maximum Moment Restriction for Instrumental Variable Regression


Oct 15, 2020
Rui Zhang, Masaaki Imaizumi, Bernhard Schölkopf, Krikamol Muandet

* 30 pages 

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Function Contrastive Learning of Transferable Representations


Oct 14, 2020
Muhammad Waleed Gondal, Shruti Joshi, Nasim Rahaman, Stefan Bauer, Manuel Wüthrich, Bernhard Schölkopf


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On the Fairness of Causal Algorithmic Recourse


Oct 14, 2020
Julius von Kügelgen, Umang Bhatt, Amir-Hossein Karimi, Isabel Valera, Adrian Weller, Bernhard Schölkopf


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Physically constrained causal noise models for high-contrast imaging of exoplanets


Oct 12, 2020
Timothy D. Gebhard, Markus J. Bonse, Sascha P. Quanz, Bernhard Schölkopf

* Submitted to the "Machine Learning and the Physical Sciences" workshop at NeurIPS 2020. 8 pages, 6 figures 

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CausalWorld: A Robotic Manipulation Benchmark for Causal Structure and Transfer Learning


Oct 08, 2020
Ossama Ahmed, Frederik Träuble, Anirudh Goyal, Alexander Neitz, Manuel Wüthrich, Yoshua Bengio, Bernhard Schölkopf, Stefan Bauer

* The first two authors contributed equally 

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A survey of algorithmic recourse: definitions, formulations, solutions, and prospects


Oct 08, 2020
Amir-Hossein Karimi, Gilles Barthe, Bernhard Schölkopf, Isabel Valera


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Causal Curiosity: RL Agents Discovering Self-supervised Experiments for Causal Representation Learning


Oct 07, 2020
Sumedh A. Sontakke, Arash Mehrjou, Laurent Itti, Bernhard Schölkopf


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Learning explanations that are hard to vary


Sep 05, 2020
Giambattista Parascandolo, Alexander Neitz, Antonio Orvieto, Luigi Gresele, Bernhard Schölkopf

* From v0: extended experiment in Section 3.1, Figure 7 (multiple thresholds and XOR mask) 

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Real-time Prediction of COVID-19 related Mortality using Electronic Health Records


Aug 31, 2020
Patrick Schwab, Arash Mehrjou, Sonali Parbhoo, Leo Anthony Celi, Jürgen Hetzel, Markus Hofer, Bernhard Schölkopf, Stefan Bauer


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Learning Dynamical Systems using Local Stability Priors


Aug 23, 2020
Arash Mehrjou, Andrea Iannelli, Bernhard Schölkopf


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TriFinger: An Open-Source Robot for Learning Dexterity


Aug 08, 2020
Manuel Wüthrich, Felix Widmaier, Felix Grimminger, Joel Akpo, Shruti Joshi, Vaibhav Agrawal, Bilal Hammoud, Majid Khadiv, Miroslav Bogdanovic, Vincent Berenz, Julian Viereck, Maximilien Naveau, Ludovic Righetti, Bernhard Schölkopf, Stefan Bauer


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Geometrically Enriched Latent Spaces


Aug 02, 2020
Georgios Arvanitidis, Søren Hauberg, Bernhard Schölkopf


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A Commentary on the Unsupervised Learning of Disentangled Representations


Jul 28, 2020
Francesco Locatello, Stefan Bauer, Mario Lucic, Gunnar Rätsch, Sylvain Gelly, Bernhard Schölkopf, Olivier Bachem

* The Thirty-Fourth AAAI Conference on Artificial Intelligence 2020 (AAAI-20) 

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