163 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

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

**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

**Data scarcity, robustness and extreme multi-label classification**
*Machine Learning*, Special Issue of the ECML PKDD 2019 Journal Track, March 2019 (article)

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

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

**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)

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

**Kernel Stein Tests for Multiple Model Comparison**
2019 (conference) Submitted

**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

**Fisher Efficient Inference of Intractable Models**
2019 (conference) Submitted

**Active Probabilistic Inference on Matrices for Pre-Conditioning in Stochastic Optimization**
2019 (conference) Accepted

**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

**Probabilistic Linear Solvers: A Unifying View**
*Statistics and Computing*, 2019 (article) Accepted

**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)

**Camera-specific Image Denoising**
Eberhard Karls Universität Tübingen, Germany, October 2013 (diplomathesis)

**Studying large-scale brain networks: electrical stimulation and neural-event-triggered fMRI**
Twenty-Second Annual Computational Neuroscience Meeting (CNS*2013), July 2013, journal = {BMC Neuroscience},
year = {2013},
month = {7},
volume = {14},
number = {Supplement 1},
pages = {A1}, (talk)

**Correlation of Simultaneously Acquired Diffusion-Weighted Imaging and 2-Deoxy-[18F] fluoro-2-D-glucose Positron Emission Tomography of Pulmonary Lesions in a Dedicated Whole-Body Magnetic Resonance/Positron Emission Tomography System**
*Investigative Radiology*, 48(5):247-255, May 2013 (article)

**Replacing Causal Faithfulness with Algorithmic Independence of Conditionals**
*Minds and Machines*, 23(2):227-249, May 2013 (article)

**What can neurons do for their brain? Communicate selectivity with bursts**
*Theory in Biosciences *, 132(1):27-39, Springer, March 2013 (article)

**Apprenticeship Learning with Few Examples**
*Neurocomputing*, 104, pages: 83-96, March 2013 (article)

**Quasi-Newton Methods: A New Direction**
*Journal of Machine Learning Research*, 14(1):843-865, March 2013 (article)

**Regional effects of magnetization dispersion on quantitative perfusion imaging for pulsed and continuous arterial spin labeling**
*Magnetic Resonance in Medicine*, 69(2):524-530, Febuary 2013 (article)

**The multivariate Watson distribution: Maximum-likelihood estimation and other aspects**
*Journal of Multivariate Analysis*, 114, pages: 256-269, February 2013 (article)

**How the result of graph clustering methods depends on the construction of the graph**
*ESAIM: Probability & Statistics*, 17, pages: 370-418, January 2013 (article)

**Falsification and future performance**
In *Algorithmic Probability and Friends. Bayesian Prediction and Artificial Intelligence*, 7070, pages: 65-78, Lecture Notes in Computer Science, Springer, Berlin, Germany, Solomonoff 85th Memorial Conference, January 2013 (inproceedings)