47 results
(View BibTeX file of all listed publications)

**Fast Non-Parametric Learning to Accelerate Mixed-Integer Programming for Online Hybrid Model Predictive Control**
*21rst IFAC World Congress*, July 2020 (conference) Accepted

**Analytical classical density functionals from an equation learning network**
*The Journal of Chemical Physics*, 152(2):021102, 2020, arXiv preprint \url{https://arxiv.org/abs/1910.12752} (article)

**A Real-Robot Dataset for Assessing Transferability of Learned Dynamics Models **
*IEEE International Conference on Robotics and Automation (ICRA)*, 2020 (conference) Accepted

**Differentiation of Blackbox Combinatorial Solvers**
In *International Conference on Learning Representations*, ICLR’20, 2020 (incollection)

**Optimizing Rank-based Metrics with Blackbox Differentiation**
In * Proceedings IEEE Conf. on Computer Vision and Pattern Recognition (CVPR)*, IEEE International Conference on Computer Vision and Pattern Recognition (CVPR) 2020, 2020, Best paper nomination (inproceedings)

**Deep Reinforcement Learning for Event-Triggered Control**
In *Proceedings of the 57th IEEE International Conference on Decision and Control (CDC)*, pages: 943-950, 57th IEEE International Conference on Decision and Control (CDC), December 2018 (inproceedings)

**Probabilistic Solutions To Ordinary Differential Equations As Non-Linear Bayesian Filtering: A New Perspective**
*ArXiv preprint 2018*, arXiv:1810.03440 [stat.ME], October 2018 (article)

**Kernel Recursive ABC: Point Estimation with Intractable Likelihood**
*Proceedings of the 35th International Conference on Machine Learning*, pages: 2405-2414, PMLR, July 2018 (conference)

**Convergence Rates of Gaussian ODE Filters**
*arXiv preprint 2018*, arXiv:1807.09737 [math.NA], July 2018 (article)

**Counterfactual Mean Embedding: A Kernel Method for Nonparametric Causal Inference**
*Workshop on Machine Learning for Causal Inference, Counterfactual Prediction, and Autonomous Action (CausalML) at ICML*, July 2018 (conference)

**Nonlinear decoding of a complex movie from the mammalian retina**
*PLOS Computational Biology*, 14(5):1-27, Public Library of Science, May 2018 (article)

**Gaussian Processes and Kernel Methods: A Review on Connections and Equivalences**
*Arxiv e-prints*, arXiv:1805.08845v1 [stat.ML], 2018 (article)

**Dissecting Adam: The Sign, Magnitude and Variance of Stochastic Gradients**
In *Proceedings of the 35th International Conference on Machine Learning (ICML)*, 2018 (inproceedings) Accepted

**Counterfactual Mean Embedding: A Kernel Method for Nonparametric Causal Inference**
*Arxiv e-prints*, arXiv:1805.08845v1 [stat.ML], 2018 (article)

**Model-based Kernel Sum Rule: Kernel Bayesian Inference with Probabilistic Models**
*Arxiv e-prints*, arXiv:1409.5178v2 [stat.ML], 2018 (article)

**L4: Practical loss-based stepsize adaptation for deep learning**
In *Advances in Neural Information Processing Systems 31 (NeurIPS 2018)*, pages: 6434-6444, (Editors: S. Bengio and H. Wallach and H. Larochelle and K. Grauman and N. Cesa-Bianchi and R. Garnett), Curran Associates, Inc., 2018 (inproceedings)

**A probabilistic model for the numerical solution of initial value problems**
*Statistics and Computing*, Springer US, 2018 (article)

**Systematic self-exploration of behaviors for robots in a dynamical systems framework**
In *Proc. Artificial Life XI*, pages: 319-326, MIT Press, Cambridge, MA, 2018 (inproceedings)

**Analytical incorporation of fractionation effects in probabilistic treatment planning for intensity-modulated proton therapy**
*Medical Physics*, 2018 (article)

**Probabilistic Approaches to Stochastic Optimization**
Eberhard Karls Universität Tübingen, Germany, 2018 (phdthesis)

**Learning equations for extrapolation and control**
In *Proc. 35th International Conference on Machine Learning, ICML 2018, Stockholm, Sweden, 2018*, 80, pages: 4442-4450, http://proceedings.mlr.press/v80/sahoo18a/sahoo18a.pdf, (Editors: Dy, Jennifer and Krause, Andreas), PMLR, 2018 (inproceedings)

**Robust Affordable 3D Haptic Sensation via Learning Deformation Patterns**
*Proceedings International Conference on Humanoid Robots*, pages: 846-853, IEEE, New York, NY, USA, 2018 IEEE-RAS International Conference on Humanoid Robots, 2018, Oral Presentation (conference)

**Large sample analysis of the median heuristic**
2018 (misc) In preparation

**Probabilistic Ordinary Differential Equation Solvers — Theory and Applications**
Eberhard Karls Universität Tübingen, Germany, 2018 (phdthesis)

**Approximate dual control maintaining the value of information with an application to building control**
In *European Control Conference (ECC)*, pages: 800-806, June 2016 (inproceedings)

**Active Uncertainty Calibration in Bayesian ODE Solvers**
*Proceedings of the 32nd Conference on Uncertainty in Artificial Intelligence (UAI)*, pages: 309-318, (Editors: Ihler, A. and Janzing, D.), AUAI Press, June 2016 (conference)

**Automatic LQR Tuning Based on Gaussian Process Global Optimization**
In *Proceedings of the IEEE International Conference on Robotics and Automation (ICRA)*, pages: 270-277, IEEE, IEEE International Conference on Robotics and Automation, May 2016 (inproceedings)

**Batch Bayesian Optimization via Local Penalization**
*Proceedings of the 19th International Conference on Artificial Intelligence and Statistics (AISTATS)*, 51, pages: 648-657, JMLR Workshop and Conference Proceedings, (Editors: Gretton, A. and Robert, C. C.), May 2016 (conference)

**Probabilistic Approximate Least-Squares**
*Proceedings of the 19th International Conference on Artificial Intelligence and Statistics (AISTATS)*, 51, pages: 676-684, JMLR Workshop and Conference Proceedings, (Editors: Gretton, A. and Robert, C. C. ), May 2016 (conference)

**Gaussian Process-Based Predictive Control for Periodic Error Correction **
*IEEE Transactions on Control Systems Technology *, 24(1):110-121, 2016 (article)

**Dual Control for Approximate Bayesian Reinforcement Learning**
*Journal of Machine Learning Research*, 17(127):1-30, 2016 (article)

**Extrapolation and learning equations**
2016, arXiv preprint \url{https://arxiv.org/abs/1610.02995} (misc)

**Probabilistic Progress Bars**
In *Conference on Pattern Recognition (GCPR)*, 8753, pages: 331-341, Lecture Notes in Computer Science, (Editors: Jiang, X., Hornegger, J., and Koch, R.), Springer, GCPR, September 2014 (inproceedings)

**Probabilistic Solutions to Differential Equations and their Application to Riemannian Statistics**
In *Proceedings of the 17th International Conference on Artificial Intelligence and Statistics*, 33, pages: 347-355, JMLR: Workshop and Conference Proceedings, (Editors: S Kaski and J Corander), Microtome Publishing, Brookline, MA, AISTATS, April 2014 (inproceedings)

**Local Gaussian Regression**
*arXiv preprint*, March 2014, clmc (misc)

**Probabilistic ODE Solvers with Runge-Kutta Means**
In *Advances in Neural Information Processing Systems 27*, pages: 739-747, (Editors: Z. Ghahramani, M. Welling, C. Cortes, N.D. Lawrence and K.Q. Weinberger), Curran Associates, Inc., 28th Annual Conference on Neural Information Processing Systems (NIPS), 2014 (inproceedings)

**Active Learning of Linear Embeddings for Gaussian Processes**
In *Proceedings of the 30th Conference on Uncertainty in Artificial Intelligence*, pages: 230-239, (Editors: NL Zhang and J Tian), AUAI Press , Corvallis, Oregon, UAI2014, 2014, another link: http://arxiv.org/abs/1310.6740 (inproceedings)

**Probabilistic Shortest Path Tractography in DTI Using Gaussian Process ODE Solvers**
In *Medical Image Computing and Computer-Assisted Intervention – MICCAI 2014, Lecture Notes in Computer Science Vol. 8675*, pages: 265-272, (Editors: P. Golland, N. Hata, C. Barillot, J. Hornegger and R. Howe), Springer, Heidelberg, MICCAI, 2014 (inproceedings)

**Sampling for Inference in Probabilistic Models with Fast Bayesian Quadrature**
In *Advances in Neural Information Processing Systems 27*, pages: 2789-2797, (Editors: Z. Ghahramani, M. Welling, C. Cortes, N.D. Lawrence and K.Q. Weinberger), Curran Associates, Inc., 28th Annual Conference on Neural Information Processing Systems (NIPS), 2014 (inproceedings)

**Incremental Local Gaussian Regression**
In *Advances in Neural Information Processing Systems 27*, pages: 972-980, (Editors: Z. Ghahramani, M. Welling, C. Cortes, N.D. Lawrence and K.Q. Weinberger), 28th Annual Conference on Neural Information Processing Systems (NIPS), 2014, clmc (inproceedings)

**Efficient Bayesian Local Model Learning for Control**
In *Proceedings of the IEEE International Conference on Intelligent Robots and Systems*, pages: 2244 - 2249, IROS, 2014, clmc (inproceedings)

**Self-Exploration of the Stumpy Robot with Predictive Information Maximization**
In *Proc. From Animals to Animats, SAB 2014*, 8575, pages: 32-42, LNCS, Springer, 2014 (inproceedings)

**Robot Learning by Guided Self-Organization**
In *Guided Self-Organization: Inception*, 9, pages: 223-260, Emergence, Complexity and Computation, Springer Berlin Heidelberg, 2014 (incollection)

**Let It Roll – Emerging Sensorimotor Coordination in a Spherical Robot**
In *Proc, Artificial Life X*, pages: 192-198, Intl. Society for Artificial Life, MIT Press, August 2006 (inproceedings)

**From Motor Babbling to Purposive Actions: Emerging Self-exploration in a Dynamical Systems Approach to Early Robot Development**
In *Proc. From Animals to Animats 9, SAB 2006*, 4095, pages: 406-421, LNCS, Springer, 2006 (inproceedings)

**Rocking Stamper and Jumping Snake from a Dynamical System Approach to Artificial Life**
*Adaptive Behavior*, 14(2):105-115, 2006 (article)

**Learning to Feel the Physics of a Body**
In *Computational Intelligence for Modelling, Control and Automation, CIMCA 2005 *, 2, pages: 252-257, Washington, DC, USA, 2005 (inproceedings)