Marc Peter Deisenroth

175 papers A* 32A 15B 2C 2Misc 3Journal 102Unranked 17

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Learning Physical Operators using Neural Operators. CoRR Vignesh Gopakumar, Ander Gray, Daniel Giles, Lorenzo Zanisi, Matt J. Kusner, Timo Betcke, Stanislas Pamela, Marc Peter Deisenroth
2025	A*	`conf`	Calibrated Physics-Informed Uncertainty Quantification. ICML Vignesh Gopakumar, Ander Gray, Lorenzo Zanisi, Timothy Nunn, Daniel Giles, Matt J. Kusner, Stanislas Pamela, Marc Peter Deisenroth
2025	J	`jnl`	Calibrated Physics-Informed Uncertainty Quantification. CoRR Vignesh Gopakumar, Ander Gray, Lorenzo Zanisi, Timothy Nunn, Stanislas Pamela, Daniel Giles, Matt J. Kusner, Marc Peter Deisenroth
2025	J	`jnl`	Infinite Neural Operators: Gaussian processes on functions. CoRR Daniel Augusto de Souza, Yuchen Zhu, Harry Jake Cunningham, Yuri F. Saporito, Diego Mesquita, Marc Peter Deisenroth
2025	A*	`conf`	Semantic Cross-Pose Correspondence from a Single Example. ICRA Denis Hadjivelichkov, Sicelukwanda Zwane, Marc Peter Deisenroth, Lourdes Agapito, Dimitrios Kanoulas
2024	A	`conf`	A Unifying Variational Framework for Gaussian Process Motion Planning. AISTATS Lucas Cosier, Rares Iordan, Sicelukwanda N. T. Zwane, Giovanni Franzese, James T. Wilson, Marc Peter Deisenroth, Alexander Terenin, Yasemin Bekiroglu
2024	A*	`conf`	Gaussian Processes on Cellular Complexes. ICML Mathieu Alain, So Takao, Brooks Paige, Marc Peter Deisenroth
2024	A	`conf`	Iterated INLA for State and Parameter Estimation in Nonlinear Dynamical Systems. UAI Rafael Anderka, Marc Peter Deisenroth, So Takao
2024	J	`jnl`	Iterated INLA for State and Parameter Estimation in Nonlinear Dynamical Systems. CoRR Rafael Anderka, Marc Peter Deisenroth, So Takao
2024	A	`conf`	Learning Dynamic Tasks on a Large-scale Soft Robot in a Handful of Trials. IROS Sicelukwanda Zwane, Daniel G. Cheney, Curtis C. Johnson, Yicheng Luo, Yasemin Bekiroglu, Marc D. Killpack, Marc Peter Deisenroth
2024	J	`jnl`	Learning Dynamic Tasks on a Large-scale Soft Robot in a Handful of Trials. CoRR Sicelukwanda Zwane, Daniel G. Cheney, Curtis C. Johnson, Yicheng Luo, Yasemin Bekiroglu, Marc D. Killpack, Marc Peter Deisenroth
2024	J	`jnl`	One Initialization to Rule them All: Fine-tuning via Explained Variance Adaptation. CoRR Fabian Paischer, Lukas Hauzenberger, Thomas Schmied, Benedikt Alkin, Marc Peter Deisenroth, Sepp Hochreiter
2024	A*	`conf`	Probabilistic Weather Forecasting with Hierarchical Graph Neural Networks. NeurIPS Joel Oskarsson, Tomas Landelius, Marc Peter Deisenroth, Fredrik Lindsten
2024	J	`jnl`	Probabilistic Weather Forecasting with Hierarchical Graph Neural Networks. CoRR Joel Oskarsson, Tomas Landelius, Marc Peter Deisenroth, Fredrik Lindsten
2024	J	`jnl`	RecMoDiffuse: Recurrent Flow Diffusion for Human Motion Generation. CoRR Mirgahney Mohamed, Harry Jake Cunningham, Marc Peter Deisenroth, Lourdes Agapito
2024	A*	`conf`	Reparameterized Multi-Resolution Convolutions for Long Sequence Modelling. NeurIPS Jake Cunningham, Giorgio Giannone, Mingtian Zhang, Marc Peter Deisenroth
2024	J	`jnl`	Reparameterized Multi-Resolution Convolutions for Long Sequence Modelling. CoRR Harry Jake Cunningham, Giorgio Giannone, Mingtian Zhang, Marc Peter Deisenroth
2024	J	`jnl`	Scalable Data Assimilation with Message Passing. CoRR Oscar Key, So Takao, Daniel Giles, Marc Peter Deisenroth
2024	J	`jnl`	Uncertainty Quantification of Pre-Trained and Fine-Tuned Surrogate Models using Conformal Prediction. CoRR Vignesh Gopakumar, Ander Gray, Joel Oskarsson, Lorenzo Zanisi, Stanislas Pamela, Daniel Giles, Matt J. Kusner, Marc Peter Deisenroth
2024	J	`jnl`	Valid Error Bars for Neural Weather Models using Conformal Prediction. CoRR Vignesh Gopakumar, Joel Oskarrson, Ander Gray, Lorenzo Zanisi, Stanislas Pamela, Daniel Giles, Matt J. Kusner, Marc Peter Deisenroth
2023	J	`jnl`	A Unifying Variational Framework for Gaussian Process Motion Planning. CoRR Lucas Cosier, Rares Iordan, Sicelukwanda Zwane, Giovanni Franzese, James T. Wilson, Marc Peter Deisenroth, Alexander Terenin, Yasemin Bekiroglu
2023	A	`conf`	Actually Sparse Variational Gaussian Processes. AISTATS Harry Jake Cunningham, Daniel Augusto de Souza, So Takao, Mark van der Wilk, Marc Peter Deisenroth
2023	J	`jnl`	Actually Sparse Variational Gaussian Processes. CoRR Harry Jake Cunningham, Daniel Augusto de Souza, So Takao, Mark van der Wilk, Marc Peter Deisenroth
2023	J	`jnl`	Faster Training of Neural ODEs Using Gauß-Legendre Quadrature. CoRR Alexander Norcliffe, Marc Peter Deisenroth
2023	J	`jnl`	Faster Training of Neural ODEs Using Gauß-Legendre Quadrature. Trans. Mach. Learn. Res. Alexander Luke Ian Norcliffe, Marc Peter Deisenroth
2023	J	`jnl`	Finetuning from Offline Reinforcement Learning: Challenges, Trade-offs and Practical Solutions. CoRR Yicheng Luo, Jackie Kay, Edward Grefenstette, Marc Peter Deisenroth
2023	J	`jnl`	Gaussian Processes on Cellular Complexes. CoRR Mathieu Alain, So Takao, Brooks Paige, Marc Peter Deisenroth
2023	J	`jnl`	Grasp Transfer Based on Self-Aligning Implicit Representations of Local Surfaces. IEEE Robotics Autom. Lett. Ahmet Ercan Tekden, Marc Peter Deisenroth, Yasemin Bekiroglu
2023	J	`jnl`	Grasp Transfer based on Self-Aligning Implicit Representations of Local Surfaces. CoRR Ahmet Ercan Tekden, Marc Peter Deisenroth, Yasemin Bekiroglu
2023	J	`jnl`	Implicit regularisation in stochastic gradient descent: from single-objective to two-player games. CoRR Mihaela Rosca, Marc Peter Deisenroth
2023	J	`jnl`	Investigating the Edge of Stability Phenomenon in Reinforcement Learning. CoRR Rares Iordan, Marc Peter Deisenroth, Mihaela Rosca
2023	A	`conf`	Neural Field Movement Primitives for Joint Modelling of Scenes and Motions. IROS Ahmet Ercan Tekden, Marc Peter Deisenroth, Yasemin Bekiroglu
2023	J	`jnl`	Neural Field Movement Primitives for Joint Modelling of Scenes and Motions. CoRR Ahmet Ercan Tekden, Marc Peter Deisenroth, Yasemin Bekiroglu
2023	J	`jnl`	On Combining Expert Demonstrations in Imitation Learning via Optimal Transport. CoRR Ilana Sebag, Samuel Cohen, Marc Peter Deisenroth
2023	A*	`conf`	Optimal Transport for Offline Imitation Learning. ICLR Yicheng Luo, Zhengyao Jiang, Samuel Cohen, Edward Grefenstette, Marc Peter Deisenroth
2023	J	`jnl`	Optimal Transport for Offline Imitation Learning. CoRR Yicheng Luo, Zhengyao Jiang, Samuel Cohen, Edward Grefenstette, Marc Peter Deisenroth
2023	J	`jnl`	Plasma Surrogate Modelling using Fourier Neural Operators. CoRR Vignesh Gopakumar, Stanislas Pamela, Lorenzo Zanisi, Zongyi Li, Ander Gray, Daniel Brennand, Nitesh Bhatia, Gregory Stathopoulos, Matt J. Kusner, Marc Peter Deisenroth, Anima Anandkumar, JOREK Team, MAST Team
2023	—	`conf`	Queer In AI: A Case Study in Community-Led Participatory AI. FAccT Organizers Of QueerInAI, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J. Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi Jethwani, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx McLean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J. Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y. Bilenko, Andrew McNamara, Raphael Gontijo Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, Luke Stark
2023	J	`jnl`	Queer In AI: A Case Study in Community-Led Participatory AI. CoRR Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J. Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi Jethwani, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx McLean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J. Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y. Bilenko, Andrew McNamara, Raphael Gontijo Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, Luke Stark
2023	—	`conf`	Safe Trajectory Sampling in Model-Based Reinforcement Learning. CASE Sicelukwanda Zwane, Denis Hadjivelichkov, Yicheng Luo, Yasemin Bekiroglu, Dimitrios Kanoulas, Marc Peter Deisenroth
2023	J	`jnl`	Short-term Prediction and Filtering of Solar Power Using State-Space Gaussian Processes. CoRR Sean Nassimiha, Peter Dudfield, Jack Kelly, Marc Peter Deisenroth, So Takao
2023	A	`conf`	Sliding Touch-Based Exploration for Modeling Unknown Object Shape with Multi-Fingered Hands. IROS Yiting Chen, Ahmet Ercan Tekden, Marc Peter Deisenroth, Yasemin Bekiroglu
2023	J	`jnl`	Sliding Touch-based Exploration for Modeling Unknown Object Shape with Multi-fingered Hands. CoRR Yiting Chen, Ahmet Ercan Tekden, Marc Peter Deisenroth, Yasemin Bekiroglu
2023	J	`jnl`	Thin and Deep Gaussian Processes. CoRR Daniel Augusto de Souza, Alexander Nikitin, St John, Magnus Ross, Mauricio A. Álvarez, Marc Peter Deisenroth, João P. P. Gomes, Diego Mesquita, César Lincoln C. Mattos
2023	A*	`conf`	Thin and deep Gaussian processes. NeurIPS Daniel Augusto de Souza, Alexander Nikitin, St John, Magnus Ross, Mauricio A. Álvarez, Marc Peter Deisenroth, João Paulo Pordeus Gomes, Diego Mesquita, César Lincoln C. Mattos
2023	A*	`conf`	Understanding Deep Generative Models with Generalized Empirical Likelihoods. CVPR Suman V. Ravuri, Mélanie Rey, Shakir Mohamed, Marc Peter Deisenroth
2023	J	`jnl`	Understanding Deep Generative Models with Generalized Empirical Likelihoods. CoRR Suman V. Ravuri, Mélanie Rey, Shakir Mohamed, Marc Peter Deisenroth
2022	—	`conf`	Bayesian Optimization-based Nonlinear Adaptive PID Controller Design for Robust Mobile Manipulation. CASE Hadi Hajieghrary, Marc Peter Deisenroth, Yasemin Bekiroglu
2022	J	`jnl`	Bayesian Optimization-based Nonlinear Adaptive PID Controller Design for Robust Mobile Manipulation. CoRR Hadi Hajieghrary, Marc Peter Deisenroth, Yasemin Bekiroglu
2022	J	`jnl`	Cauchy-Schwarz Regularized Autoencoder. J. Mach. Learn. Res. Linh Tran, Maja Pantic, Marc Peter Deisenroth
2022	J	`jnl`	Enhanced GPIS Learning Based on Local and Global Focus Areas. IEEE Robotics Autom. Lett. Zuka Murvanidze, Marc Peter Deisenroth, Yasemin Bekiroglu
2022	J	`jnl`	Iterative State Estimation in Non-linear Dynamical Systems Using Approximate Expectation Propagation. Trans. Mach. Learn. Res. Sanket Kamthe, So Takao, Shakir Mohamed, Marc Peter Deisenroth
2022	Misc	`conf`	One-Shot Transfer of Affordance Regions? AffCorrs! CoRL Denis Hadjivelichkov, Sicelukwanda Zwane, Lourdes Agapito, Marc Peter Deisenroth, Dimitrios Kanoulas
2022	J	`jnl`	One-Shot Transfer of Affordance Regions? AffCorrs! CoRR Denis Hadjivelichkov, Sicelukwanda Zwane, Marc Peter Deisenroth, Lourdes Agapito, Dimitrios Kanoulas
2022	J	`jnl`	The Graph Cut Kernel for Ranked Data. Trans. Mach. Learn. Res. Michelangelo Conserva, Marc Peter Deisenroth, K. S. Sesh Kumar
2021	A	`conf`	Aligning Time Series on Incomparable Spaces. AISTATS Samuel Cohen, Giulia Luise, Alexander Terenin, Brandon Amos, Marc Peter Deisenroth
2021	J	`jnl`	Cauchy-Schwarz Regularized Autoencoder. CoRR Linh Tran, Maja Pantic, Marc Peter Deisenroth
2021	J	`jnl`	Copula Flows for Synthetic Data Generation. CoRR Sanket Kamthe, Samuel Assefa, Marc Peter Deisenroth
2021	J	`jnl`	Design of Dynamic Experiments for Black-Box Model Discrimination. CoRR Simon Olofsson, Eduardo S. Schultz, Adel Mhamdi, Alexander Mitsos, Marc Peter Deisenroth, Ruth Misener
2021	J	`jnl`	GPflux: A Library for Deep Gaussian Processes. CoRR Vincent Dutordoir, Hugh Salimbeni, Eric Hambro, John McLeod, Felix Leibfried, Artem Artemev, Mark van der Wilk, James Hensman, Marc Peter Deisenroth, S. T. John
2021	J	`jnl`	Gaussian Process Sampling and Optimization with Approximate Upper and Lower Bounds. CoRR Vu Nguyen, Marc Peter Deisenroth, Michael A. Osborne
2021	J	`jnl`	Healing Products of Gaussian Processes. CoRR Samuel Cohen, Rendani Mbuvha, Tshilidzi Marwala, Marc Peter Deisenroth
2021	A	`conf`	Learning Contact Dynamics using Physically Structured Neural Networks. AISTATS Andreas Hochlehnert, Alexander Terenin, Steindór Sæmundsson, Marc Peter Deisenroth
2021	J	`jnl`	Learning Contact Dynamics using Physically Structured Neural Networks. CoRR Andreas Hochlehnert, Alexander Terenin, Steindór Sæmundsson, Marc Peter Deisenroth
2021	J	`jnl`	Learning to Transfer: A Foliated Theory. CoRR Janith C. Petangoda, Marc Peter Deisenroth, Nicholas A. M. Monk
2021	A	`conf`	Matérn Gaussian Processes on Graphs. AISTATS Viacheslav Borovitskiy, Iskander Azangulov, Alexander Terenin, Peter Mostowsky, Marc Peter Deisenroth, Nicolas Durrande
2021	J	`jnl`	Pathwise Conditioning of Gaussian Processes. J. Mach. Learn. Res. James T. Wilson, Viacheslav Borovitskiy, Alexander Terenin, Peter Mostowsky, Marc Peter Deisenroth
2021	J	`jnl`	Sliced Multi-Marginal Optimal Transport. CoRR Samuel Cohen, K. S. Sesh Kumar, Marc Peter Deisenroth
2021	J	`jnl`	Submodular Kernels for Efficient Rankings. CoRR Michelangelo Conserva, Marc Peter Deisenroth, K. S. Sesh Kumar
2021	J	`jnl`	Vector-valued Gaussian Processes on Riemannian Manifolds via Gauge Equivariant Projected Kernels. CoRR Michael J. Hutchinson, Alexander Terenin, Viacheslav Borovitskiy, So Takao, Yee Whye Teh, Marc Peter Deisenroth
2021	A*	`conf`	Vector-valued Gaussian Processes on Riemannian Manifolds via Gauge Independent Projected Kernels. NeurIPS Michael J. Hutchinson, Alexander Terenin, Viacheslav Borovitskiy, So Takao, Yee Whye Teh, Marc Peter Deisenroth
2020	J	`jnl`	A Foliated View of Transfer Learning. CoRR Janith C. Petangoda, Nick A. M. Monk, Marc Peter Deisenroth
2020	J	`jnl`	Aligning Time Series on Incomparable Spaces. CoRR Samuel Cohen, Giulia Luise, Alexander Terenin, Brandon Amos, Marc Peter Deisenroth
2020	A*	`conf`	Efficiently sampling functions from Gaussian process posteriors. ICML James T. Wilson, Viacheslav Borovitskiy, Alexander Terenin, Peter Mostowsky, Marc Peter Deisenroth
2020	J	`jnl`	Efficiently sampling functions from Gaussian process posteriors. CoRR James T. Wilson, Viacheslav Borovitskiy, Alexander Terenin, Peter Mostowsky, Marc Peter Deisenroth
2020	J	`jnl`	Estimating Barycenters of Measures in High Dimensions. CoRR Samuel Cohen, Michael Arbel, Marc Peter Deisenroth
2020	J	`jnl`	GENNI: Visualising the Geometry of Equivalences for Neural Network Identifiability. CoRR Daniel Lengyel, Janith C. Petangoda, Isak Falk, Kate Highnam, Michalis Lazarou, Arinbjörn Kolbeinsson, Marc Peter Deisenroth, Nicholas R. Jennings
2020	A*	`conf`	Healing Products of Gaussian Process Experts. ICML Samuel Cohen, Rendani Mbuvha, Tshilidzi Marwala, Marc Peter Deisenroth
2020	J	`jnl`	High-dimensional Bayesian optimization using low-dimensional feature spaces. Mach. Learn. Riccardo Moriconi, Marc Peter Deisenroth, K. S. Sesh Kumar
2020	J	`jnl`	High-dimensional Bayesian optimization with projections using quantile Gaussian processes. Optim. Lett. Riccardo Moriconi, K. S. Sesh Kumar, Marc Peter Deisenroth
2020	J	`jnl`	Matern Gaussian Processes on Graphs. CoRR Viacheslav Borovitskiy, Iskander Azangulov, Alexander Terenin, Peter Mostowsky, Marc Peter Deisenroth, Nicolas Durrande
2020	J	`jnl`	Matern Gaussian processes on Riemannian manifolds. CoRR Viacheslav Borovitskiy, Alexander Terenin, Peter Mostowsky, Marc Peter Deisenroth
2020	A*	`conf`	Matérn Gaussian Processes on Riemannian Manifolds. NeurIPS Viacheslav Borovitskiy, Alexander Terenin, Peter Mostowsky, Marc Peter Deisenroth
2020	J	`jnl`	Pathwise Conditioning of Gaussian Processes. CoRR James T. Wilson, Viacheslav Borovitskiy, Alexander Terenin, Peter Mostowsky, Marc Peter Deisenroth
2020	A*	`conf`	Probabilistic Active Meta-Learning. NeurIPS Jean Kaddour, Steindór Sæmundsson, Marc Peter Deisenroth
2020	J	`jnl`	Probabilistic Active Meta-Learning. CoRR Jean Kaddour, Steindór Sæmundsson, Marc Peter Deisenroth
2020	A*	`conf`	Stochastic Differential Equations with Variational Wishart Diffusions. ICML Martin Jørgensen, Marc Peter Deisenroth, Hugh Salimbeni
2020	J	`jnl`	Stochastic Differential Equations with Variational Wishart Diffusions. CoRR Martin Jørgensen, Marc Peter Deisenroth, Hugh Salimbeni
2020	A	`conf`	Variational Integrator Networks for Physically Structured Embeddings. AISTATS Steindór Sæmundsson, Alexander Terenin, Katja Hofmann, Marc Peter Deisenroth
2019	J	`jnl`	Bayesian Multiobjective Optimisation With Mixed Analytical and Black-Box Functions: Application to Tissue Engineering. IEEE Trans. Biomed. Eng. Simon Olofsson, Mohammad Mehrian, Roberto Calandra, Liesbet Geris, Marc Peter Deisenroth, Ruth Misener
2019	A*	`conf`	Deep Gaussian Processes with Importance-Weighted Variational Inference. ICML Hugh Salimbeni, Vincent Dutordoir, James Hensman, Marc Peter Deisenroth
2019	J	`jnl`	Deep Gaussian Processes with Importance-Weighted Variational Inference. CoRR Hugh Salimbeni, Vincent Dutordoir, James Hensman, Marc Peter Deisenroth
2019	J	`jnl`	Differentially Private Empirical Risk Minimization with Sparsity-Inducing Norms. CoRR K. S. Sesh Kumar, Marc Peter Deisenroth
2019	J	`jnl`	GPdoemd: A Python package for design of experiments for model discrimination. Comput. Chem. Eng. Simon Olofsson, Lukas Hebing, Sebastian Niedenführ, Marc Peter Deisenroth, Ruth Misener
2019	J	`jnl`	High-Dimensional Bayesian Optimization with Manifold Gaussian Processes. CoRR Riccardo Moriconi, K. S. Sesh Kumar, Marc Peter Deisenroth
2019	J	`jnl`	Variational Integrator Networks for Physically Meaningful Embeddings. CoRR Steindór Sæmundsson, Alexander Terenin, Katja Hofmann, Marc Peter Deisenroth
2018	A	`conf`	Data-Efficient Reinforcement Learning with Probabilistic Model Predictive Control. AISTATS Sanket Kamthe, Marc Peter Deisenroth
2018	A*	`conf`	Design of Experiments for Model Discrimination Hybridising Analytical and Data-Driven Approaches. ICML Simon Olofsson, Marc Peter Deisenroth, Ruth Misener
2018	A*	`conf`	Gaussian Process Conditional Density Estimation. NeurIPS Vincent Dutordoir, Hugh Salimbeni, James Hensman, Marc Peter Deisenroth
2018	J	`jnl`	Gaussian Process Conditional Density Estimation. CoRR Vincent Dutordoir, Hugh Salimbeni, Marc Peter Deisenroth, James Hensman
2018	A*	`conf`	Maximizing acquisition functions for Bayesian optimization. NeurIPS James T. Wilson, Frank Hutter, Marc Peter Deisenroth
2018	J	`jnl`	Maximizing acquisition functions for Bayesian optimization. CoRR James T. Wilson, Frank Hutter, Marc Peter Deisenroth
2018	A	`conf`	Meta Reinforcement Learning with Latent Variable Gaussian Processes. UAI Steindór Sæmundsson, Katja Hofmann, Marc Peter Deisenroth
2018	J	`jnl`	Meta Reinforcement Learning with Latent Variable Gaussian Processes. CoRR Steindór Sæmundsson, Katja Hofmann, Marc Peter Deisenroth
2018	A*	`conf`	Orthogonally Decoupled Variational Gaussian Processes. NeurIPS Hugh Salimbeni, Ching-An Cheng, Byron Boots, Marc Peter Deisenroth
2018	J	`jnl`	Orthogonally Decoupled Variational Gaussian Processes. CoRR Hugh Salimbeni, Ching-An Cheng, Byron Boots, Marc Peter Deisenroth
2017	J	`jnl`	A Brief Survey of Deep Reinforcement Learning. CoRR Kai Arulkumaran, Marc Peter Deisenroth, Miles Brundage, Anil Anthony Bharath
2017	J	`jnl`	Customer Life Time Value Prediction Using Embeddings. CoRR Benjamin Paul Chamberlain, Ângelo Cardoso, C. H. Bryan Liu, Roberto Pagliari, Marc Peter Deisenroth
2017	A*	`conf`	Customer Lifetime Value Prediction Using Embeddings. KDD Benjamin Paul Chamberlain, Ângelo Cardoso, C. H. Bryan Liu, Roberto Pagliari, Marc Peter Deisenroth
2017	J	`jnl`	Data-Efficient Reinforcement Learning with Probabilistic Model Predictive Control. CoRR Sanket Kamthe, Marc Peter Deisenroth
2017	J	`jnl`	Deep Reinforcement Learning: A Brief Survey. IEEE Signal Process. Mag. Kai Arulkumaran, Marc Peter Deisenroth, Miles Brundage, Anil Anthony Bharath
2017	—	`conf`	Doubly Stochastic Variational Inference for Deep Gaussian Processes. NIPS Hugh Salimbeni, Marc Peter Deisenroth
2017	J	`jnl`	Gaussian Process Domain Experts for Modeling of Facial Affect. IEEE Trans. Image Process. Stefanos Eleftheriadis, Ognjen Rudovic, Marc Peter Deisenroth, Maja Pantic
2017	—	`conf`	Identification of Gaussian Process State Space Models. NIPS Stefanos Eleftheriadis, Tom Nicholson, Marc Peter Deisenroth, James Hensman
2017	J	`jnl`	Model-based contextual policy search for data-efficient generalization of robot skills. Artif. Intell. Andras Gabor Kupcsik, Marc Peter Deisenroth, Jan Peters, Ai Poh Loh, Prahlad Vadakkepat, Gerhard Neumann
2017	J	`jnl`	Neural Embeddings of Graphs in Hyperbolic Space. CoRR Benjamin Paul Chamberlain, James R. Clough, Marc Peter Deisenroth
2017	—	`conf`	Probabilistic Inference of Twitter Users' Age Based on What They Follow. ECML/PKDD (3) Benjamin Paul Chamberlain, Clive Humby, Marc Peter Deisenroth
2017	J	`jnl`	The reparameterization trick for acquisition functions. CoRR James T. Wilson, Riccardo Moriconi, Frank Hutter, Marc Peter Deisenroth
2016	J	`jnl`	Bayesian optimization for learning gaits under uncertainty - An experimental comparison on a dynamic bipedal walker. Ann. Math. Artif. Intell. Roberto Calandra, André Seyfarth, Jan Peters, Marc Peter Deisenroth
2016	J	`jnl`	Detecting the Age of Twitter Users. CoRR Benjamin Paul Chamberlain, Clive Humby, Marc Peter Deisenroth
2016	—	`conf`	Gaussian Process Domain Experts for Model Adaptation in Facial Behavior Analysis. CVPR Workshops Stefanos Eleftheriadis, Ognjen Rudovic, Marc Peter Deisenroth, Maja Pantic
2016	J	`jnl`	Gaussian Process Domain Experts for Model Adaptation in Facial Behavior Analysis. CoRR Stefanos Eleftheriadis, Ognjen Rudovic, Marc Peter Deisenroth, Maja Pantic
2016	Misc	`conf`	Knowledge Transfer in Automatic Optimisation of Reconfigurable Designs. FCCM Maciej Kurek, Marc Peter Deisenroth, Wayne Luk, Timothy John Todman
2016	B	`conf`	Manifold Gaussian Processes for regression. IJCNN Roberto Calandra, Jan Peters, Carl Edward Rasmussen, Marc Peter Deisenroth
2016	J	`jnl`	Real-Time Association Mining in Large Social Networks. CoRR Benjamin Paul Chamberlain, Josh Levy-Kramer, Clive Humby, Marc Peter Deisenroth
2016	A*	`conf`	Social and Affective Robotics Tutorial. ACM Multimedia Maja Pantic, Vanessa Evers, Marc Peter Deisenroth, Luis Merino, Björn W. Schuller
2016	—	`conf`	Variational Gaussian Process Auto-Encoder for Ordinal Prediction of Facial Action Units. ACCV (2) Stefanos Eleftheriadis, Ognjen Rudovic, Marc Peter Deisenroth, Maja Pantic
2016	J	`jnl`	Variational Gaussian Process Auto-Encoder for Ordinal Prediction of Facial Action Units. CoRR Stefanos Eleftheriadis, Ognjen Rudovic, Marc Peter Deisenroth, Maja Pantic
2015	J	`jnl`	Bayesian Optimization with Dimension Scheduling: Application to Biological Systems. CoRR Doniyor Ulmasov, Caroline Baroukh, Benoît Chachuat, Marc Peter Deisenroth, Ruth Misener
2015	J	`jnl`	Data-Efficient Learning of Feedback Policies from Image Pixels using Deep Dynamical Models. CoRR John-Alexander M. Assael, Niklas Wahlström, Thomas B. Schön, Marc Peter Deisenroth
2015	A*	`conf`	Distributed Gaussian Processes. ICML Marc Peter Deisenroth, Jun Wei Ng
2015	J	`jnl`	From Pixels to Torques: Policy Learning with Deep Dynamical Models. CoRR Niklas Wahlström, Thomas B. Schön, Marc Peter Deisenroth
2015	J	`jnl`	Gaussian Processes for Data-Efficient Learning in Robotics and Control. CoRR Marc Peter Deisenroth, Dieter Fox, Carl Edward Rasmussen
2015	J	`jnl`	Gaussian Processes for Data-Efficient Learning in Robotics and Control. IEEE Trans. Pattern Anal. Mach. Intell. Marc Peter Deisenroth, Dieter Fox, Carl Edward Rasmussen
2015	A*	`conf`	Learning inverse dynamics models with contacts. ICRA Roberto Calandra, Serena Ivaldi, Marc Peter Deisenroth, Elmar Rueckert, Jan Peters
2015	—	`conf`	Learning torque control in presence of contacts using tactile sensing from robot skin. Humanoids Roberto Calandra, Serena Ivaldi, Marc Peter Deisenroth, Jan Peters
2014	A*	`conf`	An experimental comparison of Bayesian optimization for bipedal locomotion. ICRA Roberto Calandra, André Seyfarth, Jan Peters, Marc Peter Deisenroth
2014	A	`conf`	Analytic Long-Term Forecasting with Periodic Gaussian Processes. AISTATS Nooshin HajiGhassemi, Marc Peter Deisenroth
2014	—	`conf`	Bayesian Gait Optimization for Bipedal Locomotion. LION Roberto Calandra, Nakul Gopalan, André Seyfarth, Jan Peters, Marc Peter Deisenroth
2014	J	`jnl`	Hierarchical Mixture-of-Experts Model for Large-Scale Gaussian Process Regression. CoRR Jun Wei Ng, Marc Peter Deisenroth
2014	J	`jnl`	Learning deep dynamical models from image pixels. CoRR Niklas Wahlström, Thomas B. Schön, Marc Peter Deisenroth
2014	J	`jnl`	Manifold Gaussian Processes for Regression. CoRR Roberto Calandra, Jan Peters, Carl Edward Rasmussen, Marc Peter Deisenroth
2014	Misc	`conf`	Multi-modal filtering for non-linear estimation. ICASSP Sanket Kamthe, Jan Peters, Marc Peter Deisenroth
2014	J	`jnl`	Multi-modal filtering for non-linear estimation. CoRR Sanket Kamthe, Jan Peters, Marc Peter Deisenroth
2014	A*	`conf`	Multi-task policy search for robotics. ICRA Marc Peter Deisenroth, Peter Englert, Jan Peters, Dieter Fox
2014	A*	`conf`	Policy search for learning robot control using sparse data. ICRA Bastian Bischoff, Duy Nguyen-Tuong, Herke van Hoof, Andrew McHutchon, Carl E. Rasmussen, Alois C. Knoll, Jan Peters, Marc Peter Deisenroth
2013	J	`jnl`	A Survey on Policy Search for Robotics. Found. Trends Robotics Marc Peter Deisenroth, Gerhard Neumann, Jan Peters
2013	A*	`conf`	Data-Efficient Generalization of Robot Skills with Contextual Policy Search. AAAI Andras Gabor Kupcsik, Marc Peter Deisenroth, Jan Peters, Gerhard Neumann
2013	A*	`conf`	Feedback error learning for rhythmic motor primitives. ICRA Nakul Gopalan, Marc Peter Deisenroth, Jan Peters
2013	A*	`conf`	Model-based imitation learning by probabilistic trajectory matching. ICRA Peter Englert, Alexandros Paraschos, Jan Peters, Marc Peter Deisenroth
2013	J	`jnl`	Multi-Task Policy Search. CoRR Marc Peter Deisenroth, Peter Englert, Jan Peters, Dieter Fox
2013	J	`jnl`	Probabilistic model-based imitation learning. Adapt. Behav. Peter Englert, Alexandros Paraschos, Marc Peter Deisenroth, Jan Peters
2013	J	`jnl`	Probabilistic movement modeling for intention inference in human-robot interaction. Int. J. Robotics Res. Zhikun Wang, Katharina Mülling, Marc Peter Deisenroth, Heni Ben Amor, David Vogt, Bernhard Schölkopf, Jan Peters
2012	J	`jnl`	Expectation Propagation in Gaussian Process Dynamical Systems CoRR Marc Peter Deisenroth, Shakir Mohamed
2012	—	`conf`	Expectation Propagation in Gaussian Process Dynamical Systems. NIPS Marc Peter Deisenroth, Shakir Mohamed
2012	—	`conf`	Learning Deep Belief Networks from Non-stationary Streams. ICANN (2) Roberto Calandra, Tapani Raiko, Marc Peter Deisenroth, Federico Montesino-Pouzols
2012	—	`conf`	Preface. EWRL Marc Peter Deisenroth, Csaba Szepesvári, Jan Peters
2012	—	`conf`	Probabilistic Modeling of Human Movements for Intention Inference. Robotics: Science and Systems Zhikun Wang, Marc Peter Deisenroth, Heni Ben Amor, David Vogt, Bernhard Schölkopf, Jan Peters
2012	—	`ed.`	Proceedings of the Tenth European Workshop on Reinforcement Learning, EWRL 2012, Edinburgh, Scotland, UK, June, 2012 EWRL Marc Peter Deisenroth, Csaba Szepesvári, Jan Peters
2012	J	`jnl`	Robust Filtering and Smoothing with Gaussian Processes CoRR Marc Peter Deisenroth, Ryan D. Turner, Marco F. Huber, Uwe D. Hanebeck, Carl Edward Rasmussen
2012	J	`jnl`	Robust Filtering and Smoothing with Gaussian Processes. IEEE Trans. Autom. Control. Marc Peter Deisenroth, Ryan D. Turner, Marco F. Huber, Uwe D. Hanebeck, Carl Edward Rasmussen
2012	A	`conf`	Toward fast policy search for learning legged locomotion. IROS Marc Peter Deisenroth, Roberto Calandra, André Seyfarth, Jan Peters
2011	C	`conf`	A general perspective on Gaussian filtering and smoothing: Explaining current and deriving new algorithms. ACC Marc Peter Deisenroth, Henrik Ohlsson
2011	A*	`conf`	Gambit: An autonomous chess-playing robotic system. ICRA Cynthia Matuszek, Brian Mayton, Roberto Aimi, Marc Peter Deisenroth, Liefeng Bo, Robert Chu, Mike Kung, Louis Legrand, Joshua R. Smith, Dieter Fox
2011	—	`conf`	Learning to Control a Low-Cost Manipulator using Data-Efficient Reinforcement Learning. Robotics: Science and Systems Marc Peter Deisenroth, Carl Edward Rasmussen, Dieter Fox
2011	A*	`conf`	PILCO: A Model-Based and Data-Efficient Approach to Policy Search. ICML Marc Peter Deisenroth, Carl Edward Rasmussen
2010	J	`jnl`	A Probabilistic Perspective on Gaussian Filtering and Smoothing CoRR Marc Peter Deisenroth, Henrik Ohlsson
2010	—	`—`	Efficient reinforcement learning using Gaussian processes. Marc Peter Deisenroth
2010	A	`conf`	State-Space Inference and Learning with Gaussian Processes. AISTATS Ryan D. Turner, Marc Peter Deisenroth, Carl Edward Rasmussen
2009	A*	`conf`	Analytic moment-based Gaussian process filtering. ICML Marc Peter Deisenroth, Marco F. Huber, Uwe D. Hanebeck
2009	J	`jnl`	Gaussian process dynamic programming. Neurocomputing Marc Peter Deisenroth, Carl Edward Rasmussen, Jan Peters
2008	C	`conf`	Approximate dynamic programming with Gaussian processes. ACC Marc Peter Deisenroth, Jan Peters, Carl E. Rasmussen
2008	B	`conf`	Model-Based Reinforcement Learning with Continuous States and Actions. ESANN Marc Peter Deisenroth, Carl Edward Rasmussen, Jan Peters
2008	—	`conf`	Probabilistic Inference for Fast Learning in Control. EWRL Carl Edward Rasmussen, Marc Peter Deisenroth
2006	—	`conf`	Finite-Horizon Optimal State-Feedback Control of Nonlinear Stochastic Systems Based on a Minimum Principle. MFI Marc Peter Deisenroth, Toshiyuki Ohtsuka, Florian Weissel, Dietrich Brunn, Uwe D. Hanebeck