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Marc Deisenroth
Marc Deisenroth
Другие именаMarc Peter Deisenroth, Marc P. Deisenroth
University College London
Подтвержден адрес электронной почты в домене ucl.ac.uk - Главная страница
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Процитировано
Процитировано
Год
Deep reinforcement learning: A brief survey
K Arulkumaran, MP Deisenroth, M Brundage, AA Bharath
IEEE Signal Processing Magazine 34 (6), 26-38, 2017
4822*2017
PILCO: A model-based and data-efficient approach to policy search
MP Deisenroth, CE Rasmussen
International Conference on Machine Learning (ICML), 465-472, 2011
20912011
A Survey on Policy Search for Robotics
MP Deisenroth, G Neumann, J Peters
Foundations and Trends in Robotics 2 (1-2), 1-142, 2013
12852013
Mathematics for Machine Learning
MP Deisenroth, AA Faisal, CS Ong
Cambridge University Press, 2020
8922020
Gaussian Processes for Data-Efficient Learning in Robotics and Control
MP Deisenroth, D Fox, CE Rasmussen
Transactions on Pattern Analysis and Machine Intelligence 37 (2), 408-423, 2015
8812015
Doubly Stochastic Variational Inference for Deep Gaussian Processes
H Salimbeni, M Deisenroth
Advances in Neural Information Processing Systems (NeurIPS), 2017
5012017
Distributed Gaussian Processes
MP Deisenroth, JW Ng
International Conference on Machine Learning (ICML), 2015
4412015
Bayesian optimization for learning gaits under uncertainty: An experimental comparison on a dynamic bipedal walker
R Calandra, A Seyfarth, J Peters, MP Deisenroth
Annals of Mathematics and Artificial Intelligence 76, 5-23, 2016
3912016
Manifold Gaussian processes for regression
R Calandra, J Peters, CE Rasmussen, MP Deisenroth
2016 International joint conference on neural networks (IJCNN), 3338-3345, 2016
3632016
Learning to Control a Low-Cost Manipulator using Data-Efficient Reinforcement Learning
MP Deisenroth, CE Rasmussen, D Fox
Robotics: Science & Systems (RSS), 2011
3232011
Maximizing acquisition functions for Bayesian optimization
JT Wilson, F Hutter, MP Deisenroth
Neural Information Processing Systems (NeurIPS), 2018
3072018
Data-Efficient Reinforcement Learning with Probabilistic Model Predictive Control
S Kamthe, MP Deisenroth
International Conference on Artificial Intelligence and Statistics (AISTATS), 2018
3062018
Gaussian process dynamic programming
MP Deisenroth, CE Rasmussen, J Peters
Neurocomputing 72 (7-9), 1508-1524, 2009
2872009
Efficient reinforcement learning using Gaussian processes
MP Deisenroth
KIT Scientific Publishing, 2010
2832010
From pixels to torques: Policy learning with deep dynamical models
N Wahlström, TB Schön, MP Deisenroth
arXiv preprint arXiv:1502.02251, 2015
2342015
Neural embeddings of graphs in hyperbolic space
BP Chamberlain, J Clough, MP Deisenroth
arXiv preprint arXiv:1705.10359, 2017
2092017
Probabilistic Movement Modeling for Intention Inference in Human-Robot Interaction
Z Wang, K Mülling, MP Deisenroth, HB Amor, D Vogt, B Schölkopf, ...
International Journal of Robotics Research, 2013
2012013
Analytic moment-based Gaussian process filtering
MP Deisenroth, MF Huber, UD Hanebeck
International Conference on Machine Learning (ICML), 225-232, 2009
1852009
Meta Reinforcement Learning with Latent Variable Gaussian Processes
S Sæmundsson, K Hofmann, MP Deisenroth
Uncertainty in Artificial Intelligence (UAI), 2018
1812018
Efficiently Sampling Functions from Gaussian Process Posteriors
JT Wilson, V Borovitskiy, A Terenin, P Mostowsky, MP Deisenroth
International Conference on Machine Learning (ICML), 2020
1732020
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