173 results
(View BibTeX file of all listed publications)

**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

**Projections for Approximate Policy Iteration Algorithms**
*Proceedings of the 36th International Conference on Machine Learning (ICML)*, 97, pages: 181-190, Proceedings of Machine Learning Research, (Editors: Chaudhuri, Kamalika and Salakhutdinov, Ruslan), PMLR, June 2019 (conference)

**Switching Linear Dynamics for Variational Bayes Filtering**
*Proceedings of the 36th International Conference on Machine Learning (ICML)*, 97, pages: 553-562, Proceedings of Machine Learning Research, (Editors: Chaudhuri, Kamalika and Salakhutdinov, Ruslan), PMLR, June 2019 (conference)

**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)

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

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

**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)

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

**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)

**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)

**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)

**Learning Transferable Representations**
University of Cambridge, UK, 2019 (phdthesis)

**Sample-efficient deep reinforcement learning for continuous control**
University of Cambridge, UK, 2019 (phdthesis)

**Formally justified and modular Bayesian inference for probabilistic programs**
University of Cambridge, UK, 2019 (phdthesis)

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

**Spatial Filtering based on Riemannian Manifold for Brain-Computer Interfacing**
Technical University of Munich, Germany, 2019 (mastersthesis)

**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)

**Pragmatism and Variable Transformations in Causal Modelling**
ETH Zurich, 2019 (phdthesis)

**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

**Quantification of tumor heterogeneity using PET/MRI and machine learning**
Eberhard Karls Universität Tübingen, Germany, 2019 (phdthesis)

**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

**Advances in Probabilistic Modelling: Sparse Gaussian Processes, Autoencoders, and Few-shot Learning**
University of Cambridge, UK, 2019 (phdthesis)

**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

**Kernel ICA for Large Scale Problems**
In pages: -, NIPS Workshop on Large Scale Kernel Machines, December 2005 (inproceedings)

**Infinite dimensional exponential families by reproducing kernel Hilbert spaces**
In *IGAIA 2005*, pages: 324-333, 2nd International Symposium on Information Geometry and its Applications, December 2005 (inproceedings)

**Shortest-path kernels on graphs**
In pages: 74-81, IEEE Computer Society, Los Alamitos, CA, USA, Fifth International Conference on Data Mining (ICDM), November 2005 (inproceedings)

**Extension to Kernel Dependency Estimation with Applications to Robotics**
Biologische Kybernetik, Technische Universität Berlin, Berlin, November 2005 (phdthesis)

**Training Support Vector Machines with Multiple Equality Constraints **
In *Proceedings of the 16th European Conference on Machine Learning, Lecture Notes in Computer Science, Vol. 3720*, pages: 182-193, (Editors: JG Carbonell and J Siekmann), Springer, Berlin, Germany, ECML, November 2005 (inproceedings)

**Geometrical aspects of statistical learning theory**
Biologische Kybernetik, Darmstadt, Darmstadt, November 2005 (phdthesis)

**Measuring Statistical Dependence with Hilbert-Schmidt Norms**
In *Algorithmic Learning Theory, Lecture Notes in Computer Science, Vol. 3734*, pages: 63-78, (Editors: S Jain and H-U Simon and E Tomita), Springer, Berlin, Germany, 16th International Conference ALT, October 2005 (inproceedings)

**An Analysis of the Anti-Learning Phenomenon for the Class Symmetric Polyhedron**
In *Algorithmic Learning Theory: 16th International Conference*, pages: 78-92, Algorithmic Learning Theory, October 2005 (inproceedings)

**Implicit Surfaces For Modelling
Human Heads**
Biologische Kybernetik, Eberhard-Karls-Universität, Tübingen, September 2005 (diplomathesis)