142 results
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**Selecting causal brain features with a single conditional independence test per feature**
*Advances in Neural Information Processing Systems 32*, 33rd Annual Conference on Neural Information Processing Systems, December 2019 (conference) Accepted

**Neural Signatures of Motor Skill in the Resting Brain**
*Proceedings of the IEEE International Conference on Systems, Man and Cybernetics (SMC 2019)*, October 2019 (conference) Accepted

**Beta Power May Mediate the Effect of Gamma-TACS on Motor Performance**
*Engineering in Medicine and Biology Conference (EMBC)*, July 2019 (conference) Accepted

**Coordinating Users of Shared Facilities via Data-driven Predictive Assistants and Game Theory**
*Proceedings of the 35th Conference on Uncertainty in Artificial Intelligence (UAI)*, pages: 49, (Editors: Amir Globerson and Ricardo Silva), AUAI Press, July 2019 (conference)

**The Sensitivity of Counterfactual Fairness to Unmeasured Confounding**
*Proceedings of the 35th Conference on Uncertainty in Artificial Intelligence (UAI)*, pages: 213, (Editors: Amir Globerson and Ricardo Silva), AUAI Press, July 2019 (conference)

**The Incomplete Rosetta Stone problem: Identifiability results for Multi-view Nonlinear ICA**
*Proceedings of the 35th Conference on Uncertainty in Artificial Intelligence (UAI)*, pages: 53, (Editors: Amir Globerson and Ricardo Silva), AUAI Press, July 2019, *equal contribution (conference)

**Random Sum-Product Networks: A Simple and Effective Approach to Probabilistic Deep Learning**
*Proceedings of the 35th Conference on Uncertainty in Artificial Intelligence (UAI)*, pages: 124, (Editors: Amir Globerson and Ricardo Silva), AUAI Press, July 2019 (conference)

**Kernel Mean Matching for Content Addressability of GANs**
*Proceedings of the 36th International Conference on Machine Learning (ICML)*, 97, pages: 3140-3151, Proceedings of Machine Learning Research, (Editors: Chaudhuri, Kamalika and Salakhutdinov, Ruslan), PMLR, June 2019, *equal contribution (conference)

**Challenging Common Assumptions in the Unsupervised Learning of Disentangled Representations**
*Proceedings of the 36th International Conference on Machine Learning (ICML)*, 97, pages: 4114-4124, Proceedings of Machine Learning Research, (Editors: Chaudhuri, Kamalika and Salakhutdinov, Ruslan), PMLR, June 2019 (conference)

**Local Temporal Bilinear Pooling for Fine-grained Action Parsing**
In *Proceedings IEEE Conf. on Computer Vision and Pattern Recognition (CVPR)*, IEEE International Conference on Computer Vision and Pattern Recognition (CVPR) 2019, June 2019 (inproceedings)

**Generate Semantically Similar Images with Kernel Mean Matching**
*6th Workshop Women in Computer Vision (WiCV) (oral presentation)*, June 2019, *equal contribution (conference) Accepted

**Robustly Disentangled Causal Mechanisms: Validating Deep Representations for Interventional Robustness**
*Proceedings of the 36th International Conference on Machine Learning (ICML)*, 97, pages: 6056-6065, Proceedings of Machine Learning Research, (Editors: Chaudhuri, Kamalika and Salakhutdinov, Ruslan), PMLR, June 2019 (conference)

**First-Order Adversarial Vulnerability of Neural Networks and Input Dimension**
*Proceedings of the 36th International Conference on Machine Learning (ICML)*, 97, pages: 5809-5817, Proceedings of Machine Learning Research, (Editors: Chaudhuri, Kamalika and Salakhutdinov, Ruslan), PMLR, June 2019 (conference)

**Overcoming Mean-Field Approximations in Recurrent Gaussian Process Models**
In *Proceedings of the 36th International Conference on Machine Learning (ICML)*, 97, pages: 2931-2940, Proceedings of Machine Learning Research, (Editors: Chaudhuri, Kamalika and Salakhutdinov, Ruslan), PMLR, June 2019 (inproceedings)

**Meta learning variational inference for prediction**
*7th International Conference on Learning Representations (ICLR)*, May 2019 (conference) Accepted

**Deep Lagrangian Networks: Using Physics as Model Prior for Deep Learning**
*7th International Conference on Learning Representations (ICLR)*, May 2019 (conference) Accepted

**DeepOBS: A Deep Learning Optimizer Benchmark Suite**
*7th International Conference on Learning Representations (ICLR)*, May 2019 (conference) Accepted

**Disentangled State Space Models: Unsupervised Learning of Dynamics across Heterogeneous Environments**
*Deep Generative Models for Highly Structured Data Workshop at ICLR*, May 2019, *equal contribution (conference) Accepted

**SOM-VAE: Interpretable Discrete Representation Learning on Time Series**
*7th International Conference on Learning Representations (ICLR)*, May 2019 (conference) Accepted

**Resampled Priors for Variational Autoencoders**
*22nd International Conference on Artificial Intelligence and Statistics*, April 2019 (conference) Accepted

**Semi-Generative Modelling: Covariate-Shift Adaptation with Cause and Effect Features**
*Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics (AISTATS)*, 89, pages: 1361-1369, (Editors: Kamalika Chaudhuri and Masashi Sugiyama), PMLR, April 2019 (conference)

**Sobolev Descent**
*Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics (AISTATS)*, 89, pages: 2976-2985, (Editors: Kamalika Chaudhuri and Masashi Sugiyama), PMLR, April 2019 (conference)

**Fast and Robust Shortest Paths on Manifolds Learned from Data**
*Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics (AISTATS)*, 89, pages: 1506-1515, (Editors: Kamalika Chaudhuri and Masashi Sugiyama), PMLR, April 2019 (conference)

**Fast Gaussian Process Based Gradient Matching for Parameter Identification in Systems of Nonlinear ODEs**
*Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics (AISTATS)*, 89, pages: 1351-1360, (Editors: Kamalika Chaudhuri and Masashi Sugiyama), PMLR, April 2019 (conference)

**Active Probabilistic Inference on Matrices for Pre-Conditioning in Stochastic Optimization**
*Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics (AISTATS)*, 89, pages: 1448-1457, (Editors: Kamalika Chaudhuri and Masashi Sugiyama), PMLR, April 2019 (conference)

**Witnessing Adversarial Training in Reproducing Kernel Hilbert Spaces**
2019 (conference) Submitted

**AReS and MaRS Adversarial and MMD-Minimizing Regression for SDEs**
*Proceedings of the 36th International Conference on Machine Learning (ICML)*, 97, pages: 1-10, Proceedings of Machine Learning Research, (Editors: Chaudhuri, Kamalika and Salakhutdinov, Ruslan), PMLR, 2019, *equal contribution (conference)

**Kernel Stein Tests for Multiple Model Comparison**
*Advances in Neural Information Processing Systems 32*, 33rd Annual Conference on Neural Information Processing Systems, 2019 (conference) To be published

**MYND: A Platform for Large-scale Neuroscientific Studies**
*Proceedings of the 2019 Conference on Human Factors in Computing Systems (CHI)*, 2019 (conference) Accepted

**A Kernel Stein Test for Comparing Latent Variable Models**
2019 (conference) Submitted

**From Variational to Deterministic Autoencoders**
2019, *equal contribution (conference) Submitted

**Fisher Efficient Inference of Intractable Models**
*Advances in Neural Information Processing Systems 32*, 33rd Annual Conference on Neural Information Processing Systems, 2019 (conference) To be published

**BCPy2000**
Workshop "Machine Learning Open-Source Software" at NIPS, December 2008 (talk)

**A Predictive Model for Imitation Learning in Partially Observable Environments**
In *ICMLA 2008*, pages: 83-90, (Editors: Wani, M. A., X.-W. Chen, D. Casasent, L. A. Kurgan, T. Hu, K. Hafeez), IEEE, Piscataway, NJ, USA, Seventh International Conference on Machine Learning and Applications, December 2008 (inproceedings)

**Stereo Matching for Calibrated Cameras without Correspondence**
In *CDC 2008*, pages: 2408-2413, IEEE Service Center, Piscataway, NJ, USA, 47th IEEE Conference on Decision and Control, December 2008 (inproceedings)

**Joint Kernel Support Estimation for Structured Prediction**
In *Proceedings of the NIPS 2008 Workshop on "Structured Input - Structured Output" (NIPS SISO 2008)*, pages: 1-4, NIPS Workshop on "Structured Input - Structured Output" (NIPS SISO), December 2008 (inproceedings)

**Metropolis Algorithms for Representative Subgraph Sampling**
In pages: 283-292, (Editors: Giannotti, F.), IEEE, Piscataway, NJ, USA, Eighth IEEE International Conference on Data Mining (ICDM '08) , December 2008 (inproceedings)

**Frequent Subgraph Retrieval in Geometric Graph Databases**
In *ICDM 2008*, pages: 953-958, (Editors: Giannotti, F. , D. Gunopulos, F. Turini, C. Zaniolo, N. Ramakrishnan, X. Wu), IEEE Computer Society, Los Alamitos, CA, USA, 8th IEEE International Conference on Data Mining, December 2008 (inproceedings)

**Block Iterative Algorithms for Non-negative Matrix Approximation**
In *ICDM 2008*, pages: 1037-1042, (Editors: Giannotti, F. , D. Gunopulos, F. Turini, C. Zaniolo, N. Ramakrishnan, X. Wu), IEEE Service Center, Piscataway, NJ, USA, Eighth IEEE International Conference on Data Mining, December 2008 (inproceedings)

**A Bayesian Approach to Switching Linear Gaussian State-Space Models for Unsupervised Time-Series Segmentation**
In *ICMLA 2008*, pages: 3-9, (Editors: Wani, M. A., X.-W. Chen, D. Casasent, L. Kurgan, T. Hu, K. Hafeez), IEEE Computer Society, Los Alamitos, CA, USA, 7th International Conference on Machine Learning and Applications, December 2008 (inproceedings)

**Infinite Kernel Learning**
In *Proceedings of the NIPS 2008 Workshop on "Kernel Learning: Automatic Selection of Optimal Kernels"*, pages: 1-4, NIPS Workshop on "Kernel Learning: Automatic Selection of Optimal Kernels" (LK ASOK´08), December 2008 (inproceedings)

**Logistic Regression for Graph Classification**
NIPS Workshop on "Structured Input - Structured Output" (NIPS SISO), December 2008 (talk)

**Prediction-Directed Compression of POMDPs**
In *ICMLA 2008*, pages: 99-105, (Editors: Wani, M. A., X.-W. Chen, D. Casasent, L. A. Kurgan, T. Hu, K. Hafeez), IEEE, Piscataway, NJ, USA, Seventh International Conference on Machine Learning and Applications, December 2008 (inproceedings)

**New Projected Quasi-Newton Methods with Applications**
Microsoft Research Tech-talk, December 2008 (talk)

**Iterative Subgraph Mining for Principal Component Analysis**
In *ICDM 2008*, pages: 1007-1012, (Editors: Giannotti, F. , D. Gunopulos, F. Turini, C. Zaniolo, N. Ramakrishnan, X. Wu), IEEE Computer Society, Los Alamitos, CA, USA, IEEE International Conference on Data Mining, December 2008 (inproceedings)

**Probabilistic Inference for Fast Learning in Control**
In *EWRL 2008*, pages: 229-242, (Editors: Girgin, S. , M. Loth, R. Munos, P. Preux, D. Ryabko), Springer, Berlin, Germany, 8th European Workshop on Reinforcement Learning, November 2008 (inproceedings)

**Policy Learning: A Unified Perspective with Applications in Robotics**
In *EWRL 2008*, pages: 220-228, (Editors: Girgin, S. , M. Loth, R. Munos, P. Preux, D. Ryabko), Springer, Berlin, Germany, 8th European Workshop on Reinforcement Learning, November 2008 (inproceedings)

**Two-Channel Control for Scaled Teleoperation**
In *International Conference on Control, Automation and Systems*, pages: 1284-1289, IEEE, Piscataway, NJ, USA, International Conference on Control, Automation and Systems (ICCAS), October 2008 (inproceedings)

**Learning to Localize Objects with Structured Output Regression**
In *ECCV 2008*, pages: 2-15, (Editors: Forsyth, D. A., P. H.S. Torr, A. Zisserman), Springer, Berlin, Germany, 10th European Conference on Computer Vision, October 2008, Best Student Paper Award (inproceedings)

**Automatic Image Colorization Via Multimodal Predictions**
In *Computer Vision - ECCV 2008, Lecture Notes in Computer Science, Vol. 5304*, pages: 126-139, (Editors: DA Forsyth and PHS Torr and A Zisserman), Springer, Berlin, Germany, 10th European Conference on Computer Vision, October 2008 (inproceedings)