Publications

(2019). Variational Integrator Networks. Bayesian Deep Learning Workshop at NeurIPS.

(2018). Orthogonally Decoupled Variational Gaussian Processes. Advances in Neural Information Processing Systems (NeurIPS).

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(2018). Maximizing Acquisition Functions for Bayesian Optimization. Advances in Neural Information Processing Systems (NeurIPS).

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(2018). Meta Reinforcement Learning with Latent Variable Gaussian Processes. Proceedings of the Conference on Uncertainty in Artificial Intelligence (UAI).

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(2018). Data-Efficient Reinforcement Learning with Probabilistic Model Predictive Control. Proceedings of the International Conference on Artificial Intelligence and Statistics (AISTATS).

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(2018). Gaussian Process Conditional Density Estimation. Advances in Neural Information Processing Systems (NeurIPS).

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(2017). Doubly Stochastic Variational Inference for Deep Gaussian Processes. Advances in Neural Information Processing Systems (NIPS).

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(2017). Probabilistic Inference of Twitter Users' Age based on What They Follow. Proceedings of the European Conference on Machine Learning & Principles and Practice of Knowledge Discovery in Databases (ECML/PKDD).

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(2017). Neural Embeddings of Graphs in Hyperbolic Space. International Workshop on Mining and Learning with Graphs.

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(2017). Deeply Non-Stationary Gaussian Processes. NIPS Workshop on Bayesian Deep Learning.

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(2017). Customer Life Time Value Prediction Using Embeddings. Proceedings of the International Conference on Knowledge Discovery and Data Mining (KDD).

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(2016). Manifold Gaussian Processes for Regression. Proceedings of the IEEE International Joint Conference on Neural Networks (IJCNN).

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(2016). Knowledge Transfer in Automatic Optimisation of Reconfigurable Designs. Proceedings of the IEEE International Symposium on Field-Programmable Custom Computing Machines (FCCM).

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(2015). Learning Torque Control in Presence of Contacts using Tactile Sensing from Robot Skin. Proceedings of the IEEE-RAS International Conference on Humanoid Robots (HUMANOIDS).

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(2015). Learning Inverse Dynamics Models with Contacts. Proceedings of the IEEE International Conference on Robotics and Automation.

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(2015). Learning Deep Dynamical Models From Image Pixels. Proceedings of the IFAC Symposium on System Identification (SYSID).

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(2015). Distributed Gaussian Processes. Proceedings of the International Conference on Machine Learning (ICML).

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(2014). Multi-Task Policy Search for Robotics. Proceedings of the IEEE International Conference on Robotics and Automation (ICRA).

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(2014). Multi-Modal Filtering for Non-linear Estimation. International Conference on Acoustics, Speech, and Signal Processing (ICASSP).

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(2014). Model-based Inverse Reinforcement Learning. Workshop on Autonomously Learning Robots at NIPS 2014.

(2014). Bayesian Gait Optimization for Bipedal Locomotion. Proceedings of the International Conference on Learning and Intelligent Optimization (LION).

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(2014). Approximate Inference for Long-Term Forecasting with Periodic Gaussian Processes. Proceedings of the International Conference on Artificial Intelligence and Statistics (AISTATS).

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(2014). An Experimental Evaluation of Bayesian Optimization on Bipedal Locomotion. Proceedings of the IEEE International Conference on Robotics and Automation (ICRA).

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(2013). Model-based Imitation Learning by Probabilistic Trajectory Matching. Proceedings of the IEEE International Conference on Robotics and Automation (ICRA).

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(2013). Feedback Error Learning for Rhythmic Motor Primitives. Proceedings of the IEEE International Conference on Robotics and Automation (ICRA).

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(2012). Toward Fast Policy Search for Learning Legged Locomotion. Proceedings of IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).

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(2012). Solving Continuous State-Action-Observation POMDPs. Proceedings of the International Conference on Machine Learning.

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(2012). Learning Deep Belief Networks from Non-Stationary Streams. Proceedings of International Conference on Artificial Neural Networks (ICANN).

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(2012). Expectation Propagation in Gaussian Process Dynamical Systems. Advances in Neural Information Processing Systems (NIPS).

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(2011). PILCO: A Model-Based and Data-Efficient Approach to Policy Search. Proceedings of the International Conference on Machine Learning (ICML).

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(2011). Learning to Control a Low-Cost Manipulator using Data-Efficient Reinforcement Learning. Proceedings of the International Conference on Robotics: Science and Systems (RSS).

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(2010). State-Space Inference and Learning with Gaussian Processes. Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics (AISTATS).

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(2009). Efficient Reinforcement Learning for Motor Control. Proceedings of the 10th International Workshop on Systems and Control.

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(2009). Bayesian Inference for Efficient Learning in Control. Multidisciplinary Symposium on Reinforcement Learning (MSRL).

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(2009). Analytic Moment-based Gaussian Process Filtering. Proceedings of the 26th International Conference on Machine Learning (ICML).

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(2008). Model-Based Reinforcement Learning with Continuous States and Actions. Proceedings of the 16th European Symposium on Artificial Neural Networks (ESANN).

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(2008). Approximate Dynamic Programming with Gaussian Processes. Proceedings of the 2008 American Control Conference (ACC).

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(2006). Finite-Horizon Optimal State Feedback Control of Nonlinear Stochastic Systems Based on a Minimum Principle. Proceedings of the 6th IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems (MFI).

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