Publications

DEPARTMENTS

Emperical Interference

Haptic Intelligence

Modern Magnetic Systems

Perceiving Systems

Physical Intelligence

Robotic Materials

Social Foundations of Computation

Research Groups

Autonomous Vision

Autonomous Learning

Bioinspired Autonomous Miniature Robots

Dynamic Locomotion

Embodied Vision

Human Aspects of Machine Learning

Intelligent Control Systems

Learning and Dynamical Systems

Locomotion in Biorobotic and Somatic Systems

Micro, Nano, and Molecular Systems

Movement Generation and Control

Neural Capture and Synthesis

Physics for Inference and Optimization

Organizational Leadership and Diversity

Probabilistic Learning Group

Topics

Robot Learning

Conference Paper

2022

Autonomous Learning

Robotics

Career

Award

BibTeX

Empirical Inference Probabilistic Learning Group Conference Paper Algorithmic recourse under imperfect causal knowledge: a probabilistic approach Karimi*, A., von Kügelgen*, J., Schölkopf, B., Valera, I. Advances in Neural Information Processing Systems 33 (NeurIPS 2020), 265-277, (Editors: H. Larochelle and M. Ranzato and R. Hadsell and M. F. Balcan and H. Lin), Curran Associates, Inc., 34th Annual Conference on Neural Information Processing Systems, December 2020, *equal contribution (Published) arXiv URL BibTeX

Empirical Inference Probabilistic Learning Group Conference Paper Relative gradient optimization of the Jacobian term in unsupervised deep learning Gresele, L., Fissore, G., Javaloy, A., Schölkopf, B., Hyvarinen, A. Advances in Neural Information Processing Systems 33 (NeurIPS 2020), 16567-16578, (Editors: H. Larochelle and M. Ranzato and R. Hadsell and M. F. Balcan and H. Lin), Curran Associates, Inc., 34th Annual Conference on Neural Information Processing Systems, December 2020 (Published) URL BibTeX

Empirical Inference Probabilistic Learning Group Conference Paper Fair Decisions Despite Imperfect Predictions Kilbertus, N., Gomez Rodriguez, M., Schölkopf, B., Muandet, K., Valera, I. Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics (AISTATS), 108:277-287, Proceedings of Machine Learning Research, (Editors: Silvia Chiappa and Roberto Calandra), PMLR, August 2020 (Published) URL BibTeX

Empirical Inference Probabilistic Learning Group Conference Paper Model-Agnostic Counterfactual Explanations for Consequential Decisions Karimi, A., Barthe, G., Balle, B., Valera, I. Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics (AISTATS), 108:895-905, Proceedings of Machine Learning Research, (Editors: Silvia Chiappa and Roberto Calandra), PMLR, August 2020 (Published) arXiv URL BibTeX

Empirical Inference Perceiving Systems Probabilistic Learning Group Conference Paper From Variational to Deterministic Autoencoders Ghosh*, P., Sajjadi*, M. S. M., Vergari, A., Black, M. J., Schölkopf, B. 8th International Conference on Learning Representations (ICLR) , April 2020, *equal contribution (Published) arXiv URL BibTeX

Probabilistic Learning Group Article General Latent Feature Models for Heterogeneous Datasets Valera, I., Pradier, M. F., Lomeli, M., Ghahramani, Z. Journal of Machine Learning Research, 21(100):1-49, 2020 (Published) URL BibTeX

Probabilistic Learning Group Article Handling incomplete heterogeneous data using VAEs Nazábal, A., Olmos, P. M., Ghahramani, Z., Valera, I. Pattern Recognition, 107:107501, 2020 (Published) DOI BibTeX

Probabilistic Learning Group Article Preliminary Results on Different Text Processing Tasks Using Encoder-Decoder Networks and the Causal Feature Extractor Javaloy, A. G. G. Applied Sciences, 10(17):5772, 2020 (Published) DOI BibTeX

Probabilistic Learning Group Article Text Normalization Using Encoder-Decoder Networks Based on the Causal Feature Extractor Javaloy, A. G. G. Applied Sciences, 10(13):4551, 2020 (Published) DOI BibTeX

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