252 results
(View BibTeX file of all listed publications)

**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

**Data scarcity, robustness and extreme multi-label classification**
*Machine Learning*, 108(8):1329-1351, September 2019, Special Issue of the ECML PKDD 2019 Journal Track (article)

**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**
*22nd International Conference on Artificial Intelligence and Statistics (AISTATS)*, April 2019 (conference) Accepted

**Sobolev Descent**
*22nd International Conference on Artificial Intelligence and Statistics (AISTATS)*, April 2019 (conference) Accepted

**Fast and Robust Shortest Paths on Manifolds Learned from Data**
* 22nd International Conference on Artificial Intelligence and Statistics (AISTATS)*, April 2019 (conference) Accepted

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

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

**A 32-channel multi-coil setup optimized for human brain shimming at 9.4T**
*Magnetic Resonance in Medicine*, 2019, (Early View) (article)

**Enhancing Human Learning via Spaced Repetition Optimization**
*Proceedings of the National Academy of Sciences*, 2019, PNAS published ahead of print January 22, 2019 (article)

**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)

**Learning to Control Highly Accelerated Ballistic Movements on Muscular Robots**
2019 (article) 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)

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

**Perception of temporal dependencies in autoregressive motion**
European Conference on Visual Perception (ECVP), 2019 (poster)

**Inferring causation from time series with perspectives in Earth system sciences**
*Nature Communications*, 2019 (article) In revision

**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

**Phenomenal Causality and Sensory Realism**
European Conference on Visual Perception (ECVP), 2019 (poster)

**Fast Gaussian Process Based Gradient Matching for Parameter Identification in Systems of Nonlinear ODEs**
*22nd International Conference on Artificial Intelligence and Statistics (AISTATS)*, 2019 (conference) Accepted

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

**Optimizing the Execution of Dynamic Robot Movements With Learning Control**
*IEEE Transactions on Robotics*, pages: 1-16, 2019 (article)

**Learning to Serve: An Experimental Study for a New Learning From Demonstrations Framework**
*IEEE Robotics and Automation Letters*, 4(2):1784-1791, 2019 (article)

**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

**Statistical estimation for optimization problems on graphs**
In pages: 1-6, NIPS Workshop on Discrete Optimization in Machine Learning (DISCML): Uncertainty, Generalization and Feedback , December 2011 (inproceedings)

**Projected Newton-type methods in machine learning**
In *Optimization for Machine Learning*, pages: 305-330, (Editors: Sra, S., Nowozin, S. and Wright, S. J.), MIT Press, Cambridge, MA, USA, December 2011 (inbook)

**On the discardability of data in Support Vector Classification problems**
In pages: 3210-3215, IEEE, Piscataway, NJ, USA, 50th IEEE Conference on Decision and Control and European Control Conference (CDC - ECC), December 2011 (inproceedings)

**Combined whole-body PET/MR imaging: MR contrast agents do not affect the quantitative accuracy of PET following attenuation correction**
(SST15-05 ), 97th Scientific Assemble and Annual Meeting of the Radiological Society of North America (RSNA), December 2011 (talk)

**Causal Inference on Discrete Data using Additive Noise Models**
*IEEE Transactions on Pattern Analysis and Machine Intelligence*, 33(12):2436-2450, December 2011 (article)