Marc Deisenroth
Marc Deisenroth
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2023
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2004
Suman Ravuri
,
Melanie Rey
,
Shakir Mohamed
,
Marc P. Deisenroth
(2023).
Understanding Deep Generative Models with Generalized Empirical Likelihoods
.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
.
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Yicheng Luo
,
Zhengyao Jiang
,
Samuel Cohen
,
Edward Grefenstette
,
Marc P. Deisenroth
(2023).
Optimal Transport for Offline Imitation Learning
.
Proceedings of the International Conference on Learning Representations (ICLR)
.
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Jake Cunningham
,
Daniel de Souza
,
So Takao
,
Marc van der Wilk
,
Marc P. Deisenroth
(2023).
Actually Sparse Variational Gaussian Processes
.
Proceedings of the International Conference on Artificial Intelligence and Statistics (AISTATS)
.
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So Takao
,
Sean Nassimiha
,
Peter Dudfield
,
Jack Kelly
,
Marc P. Deisenroth
(2022).
Short-term Prediction and Filtering of Solar Power Using State-Space Gaussian Processes
.
NeurIPS Workshop on Tackling Climate Change with Machine Learning
.
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Yicheng Luo
,
Zhengyao Jiang
,
Samuel Cohen
,
Edward Grefenstette
,
Marc P. Deisenroth
(2022).
Optimal Transport for Offline Imitation Learning
.
NeurIPS Workshop on Offline Reinforcement Learning
.
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Denis Hadjivelichkov
,
Sicelukwanda Zwane
,
Lourdes Agapito
,
Marc P. Deisenroth
,
Dimitrios Kanoulas
(2022).
One-Shot Transfer of Affordance Regions? AffCorrs!
.
Proceedings of the Conference on Robot Learning (CoRL)
.
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Zuka Murvanidze
,
Marc P. Deisenroth
,
Yasemin Bekiroglu
(2022).
Enhanced GPIS Learning Based on Local and Global Focus Areas
.
IEEE Robotics and Automation Letters
.
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Michelangelo Conserva
,
Marc P. Deisenroth
,
K. S. Sesh Kumar
(2022).
The Graph Cut Kernel for Ranked Data
.
Transactions on Machine Learning Research
.
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Sanket Kamthe
,
So Takao
,
Shakir Mohamed
,
Marc P. Deisenroth
(2022).
Iterative State Estimation in Non-linear Dynamical Systems Using Approximate Expectation Propagation
.
Transactions on Machine Learning Research
.
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Linh Tran
,
Maja Pantic
,
Marc P. Deisenroth
(2022).
Cauchy-Schwarz Regularized Autoencoder
.
Journal of Machine Learning Research
.
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Hadi Hajieghrary
,
Marc P. Deisenroth
,
Yasemin Bekiroglu
(2022).
Bayesian Optimization based Nonlinear Adaptive PID Design for Robust Control of the Joints at Mobile Manipulators
.
Proceedings of the IEEE International Conference on Automation Science and Engineering
.
Michael J. Hutchinson
,
Alexander Terenin
,
Viacheslav Borovitskiy
,
So Takao
,
Yee Whye Teh
,
Marc P. Deisenroth
(2021).
Vector-valued Gaussian Processes on Riemannian Manifolds via Gauge Independent Projected Kernels
.
Advances in Neural Information Processing Systems (NeurIPS)
.
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James T. Wilson
,
Viacheslav Borovitskiy
,
Alexander Terenin
,
Peter Mostowsky
,
Marc P. Deisenroth
(2021).
Pathwise Conditioning of Gaussian Processes
.
Journal of Machine Learning Research
.
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Viacheslav Borovitskiy
,
Iskander Azangulov
,
Alexander Terenin
,
Peter Mostowsky
,
Marc P. Deisenroth
,
Nicolas Durrande
(2021).
Matérn Gaussian Processes on Graphs
.
Proceedings of the International Conference on Artificial Intelligence and Statistics (AISTATS)
.
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Andreas Hochlehnert
,
Alexander Terenin
,
Steindór Sæmundsson
,
Marc P. Deisenroth
(2021).
Learning Contact Dynamics using Physically Structured Neural Networks
.
Proceedings of the International Conference on Artificial Intelligence and Statistics (AISTATS)
.
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Samuel Cohen
,
Giulia Luise
,
Alexander Terenin
,
Brandon Amos
,
Marc P. Deisenroth
(2021).
Aligning Time Series on Incomparable Spaces
.
Proceedings of the International Conference on Artificial Intelligence and Statistics (AISTATS)
.
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Code
Vincent Dutordoir
,
Hugh Salimbeni
,
Eric Hambro
,
John McLeod
,
Felix Leibfried
,
Artem Artemev
,
Mark van der Wilk
,
James Hensman
,
Marc P. Deisenroth
,
ST John
(2021).
GPflux: A Library for Deep Gaussian Processes
.
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Viacheslav Borovitskiy
,
Alexander Terenin
,
Peter Mostowsky
,
Marc P. Deisenroth
(2020).
Matérn Gaussian Processes on Riemannian Manifolds
. Advances in Neural Information Processing Systems (NeurIPS).
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Riccardo Moriconi
,
Marc P. Deisenroth
,
K. S. Sesh Kumar
(2020).
High-Dimensional Bayesian Optimization with Manifold Gaussian Processes
.
Machine Learning
.
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Janith Petangoda
,
Nick A. M. Monk
,
Marc P. Deisenroth
(2020).
A Foliated View of Transfer Learning
. arXiv:2008.00546.
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Jean Kaddour
,
Steindór Sæmundsson
,
Marc P. Deisenroth
(2020).
Probabilistic Active Meta-Learning
. Advances in Neural Information Processing Systems (NeurIPS).
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Samuel Cohen
,
Michael Arbel
,
Marc P. Deisenroth
(2020).
Estimating Barycenters of Measures in High Dimensions
.
arXiv:2007.07105
.
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Martin Jørgensen
,
Marc P. Deisenroth
,
Hugh Salimbeni
(2020).
Stochastic Differential Equations with Variational Wishart Diffusions
.
Proceedings of the International Conference on Machine Learning (ICML)
.
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Code
James T. Wilson
,
Viacheslav Borovitskiy
,
Alexander Terenin
,
Peter Mostowsky
,
Marc P. Deisenroth
(2020).
Efficiently Sampling Functions from Gaussian Process Posteriors
.
Proceedings of the International Conference on Machine Learning (ICML)
.
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Code
Samuel Cohen
,
Giulia Luise
,
Alexander Terenin
,
Brandon Amos
,
Marc P. Deisenroth
(2020).
Aligning Time Series on Incomparable Spaces
.
arXiv:2006.12648
.
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Code
Steindór Sæmundsson
,
Alexander Terenin
,
Katja Hofmann
,
Marc P. Deisenroth
(2020).
Variational Integrator Networks for Physically Structured Embeddings
.
Proceedings of the International Conference on Artificial Intelligence and Statistics (AISTATS)
.
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Code
Marc P. Deisenroth
,
A. Aldo Faisal
,
Cheng Soon Ong
(2020).
Mathematics for Machine Learning
.
Cambridge University Press
.
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Riccardo Moriconi
,
K. S. Sesh Kumar
,
Marc P. Deisenroth
(2020).
High-Dimensional Bayesian Optimization with Projections using Quantile Gaussian Processes
.
Optimization Letters
.
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DOI
Samuel Cohen
,
Rendani Mbuvha
,
Tshilidzi Marwala
,
Marc P. Deisenroth
(2020).
Healing Products of Gaussian Process Experts
.
Proceedings of the International Conference on Machine Learning (ICML)
.
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Code
K. S. Sesh Kumar
,
Marc P. Deisenroth
(2019).
Differentially Private Empirical Risk Minimization with Sparsity-Inducing Norms
.
arXiv:1905.04873
.
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Hugh Salimbeni
,
Vincent Dutordoir
,
James Hensman
,
Marc P. Deisenroth
(2019).
Deep Gaussian Processes with Importance-Weighted Variational Inference
.
Proceedings of the International Conference on Machine Learning (ICML)
.
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Code
Gianfranco Bertone
,
Marc P. Deisenroth
,
Jong S. Kim
,
Sebastian Liem
,
Roberto Ruiz de Austri
,
Max Welling
(2019).
Accelerating the BSM Interpretation of LHC Data with Machine Learning
.
Physics of the Dark Universe
.
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DOI
Steindór Sæmundsson
,
Katja Hofmann
,
Marc P. Deisenroth
(2019).
Variational Integrator Networks
.
Bayesian Deep Learning Workshop at NeurIPS
.
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Riccardo Moriconi
,
Marc P. Deisenroth
,
K. S. Sesh Kumar
(2019).
High-Dimensional Bayesian Optimization Using Low-Dimensional Feature Spaces
.
Bayesian Deep Learning Workshop at NeurIPS
.
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Simon Olofsson
,
Lukas Hebing
,
Sebastian Niedenfuehr
,
Marc P. Deisenroth
,
Ruth Misener
(2019).
GPdoemd: A Python Package for Design of Experiments for Model Discrimination
.
Computers and Chemical Engineering
.
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Code
Hugh Salimbeni
,
Ching-An Cheng
,
Byron Boots
,
Marc P. Deisenroth
(2018).
Orthogonally Decoupled Variational Gaussian Processes
.
Advances in Neural Information Processing Systems (NeurIPS)
.
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Code
James T. Wilson
,
Frank Hutter
,
Marc P. Deisenroth
(2018).
Maximizing Acquisition Functions for Bayesian Optimization
.
Advances in Neural Information Processing Systems (NeurIPS)
.
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Code
Steindór Sæmundsson
,
Katja Hofmann
,
Marc P. Deisenroth
(2018).
Meta Reinforcement Learning with Latent Variable Gaussian Processes
.
Proceedings of the Conference on Uncertainty in Artificial Intelligence (UAI)
.
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Code
Sanket Kamthe
,
Marc P. Deisenroth
(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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Code
Benjamin P. Chamberlain
,
Josh Levy-Kramer
,
Clive Humby
,
Marc P. Deisenroth
(2018).
Real-Time Community Detection in Full Social Networks on a Laptop
.
PLOS ONE
.
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Code
Vincent Dutordoir
,
Hugh Salimbeni
,
Marc P. Deisenroth
,
James Hensman
(2018).
Gaussian Process Conditional Density Estimation
.
Advances in Neural Information Processing Systems (NeurIPS)
.
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Simon Olofsson
,
Marc P. Deisenroth
,
Ruth Misener
(2018).
Design of Experiments for Model Discrimination Hybridising Analytical and Data-Driven Approaches
.
Proceedings of the International Conference on Machine Learning
.
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Simon Olofsson
,
Mohammad Mehrian
,
Roberto Calandra
,
Liesbet Geris
,
Marc P. Deisenroth
,
Ruth Misener
(2018).
Bayesian Multi-Objective Optimisation with Mixed Analytical and Black-Box Functions: Application to Tissue Engineering
.
IEEE Transactions on Biomedical Engineering
.
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DOI
Hugh Salimbeni
,
Marc P. Deisenroth
(2017).
Doubly Stochastic Variational Inference for Deep Gaussian Processes
.
Advances in Neural Information Processing Systems (NIPS)
.
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Code
James T. Wilson
,
Riccardo Moriconi
,
Frank Hutter
,
Marc P. Deisenroth
(2017).
The Reparameterization Trick for Acquisition Functions
.
NIPS Workshop on Bayesian Optimization
.
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Benjamin P. Chamberlain
,
Clive Humby
,
Marc P. Deisenroth
(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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Code
Benjamin P. Chamberlain
,
James Clough
,
Marc P. Deisenroth
(2017).
Neural Embeddings of Graphs in Hyperbolic Space
.
International Workshop on Mining and Learning with Graphs
.
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Code
Andras Kupcsik
,
Marc P. Deisenroth
,
Jan Peters
,
Loh Ai Poha
,
Prahlad Vadakkepata
,
Gerhard Neumann
(2017).
Model-based Contextual Policy Search for Data-Efficient Generalization of Robot Skills
.
Artificial Intelligence
.
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DOI
Stefanos Eleftheriadis
,
Thomas F. W. Nicholson
,
Marc P. Deisenroth
,
James Hensman
(2017).
Identification of Gaussian Process State Space Models
.
Advances in Neural Information Processing Systems (NIPS)
.
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Stefanos Eleftheriadis
,
Ognjen Rudovic
,
Marc P. Deisenroth
,
Maja Pantic
(2017).
Gaussian Process Domain Experts for Modeling of Facial Affect
.
IEEE Transactions on Image Processing
.
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DOI
Hugh Salimbeni
,
Marc P. Deisenroth
(2017).
Deeply Non-Stationary Gaussian Processes
.
NIPS Workshop on Bayesian Deep Learning
.
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Benjamin P. Chamberlain
,
Angelo Cardoso
,
C. H. Bryan Liu
,
Roberto Pagliari
,
Marc P. Deisenroth
(2017).
Customer Life Time Value Prediction Using Embeddings
.
Proceedings of the International Conference on Knowledge Discovery and Data Mining (KDD)
.
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Simon Olofsson
,
Mohammad Mehrian
,
Liesbet Geris
,
Roberto Calandra
,
Marc P. Deisenroth
,
Ruth Misener
(2017).
Bayesian Multi-Objective Optimisation of Neotissue Growth in a Perfusion Bioreactor Set-up
.
Proceedings of the European Symposium on Computer Aided Process Engineering (ESCAPE)
.
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Kai Arulkumaran
,
Marc P. Deisenroth
,
Miles Brundage
,
Anil A. Barath
(2017).
A Brief Survey of Deep Reinforcement Learning
.
IEEE Signal Processing Magazine
.
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Kshitij Tiwari
,
Valentin Honore
,
Sungmoon Jeong
,
Nak Young Chong
,
Marc P. Deisenroth
(2016).
Resource-Constrained Decentralized Active Sensing using Distributed Gaussian Processes for Multi-Robots
.
Proceedings of the International Conference on Control, Automation and Systems (ICCAS)
.
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Stefanos Eleftheriadis
,
Ognjen Rudovic
,
Marc P. Deisenroth
,
Maja Pantic
(2016).
Variational Gaussian Process Auto-Encoder for Ordinal Prediction of Facial Action Units
.
Proceedings of the Asian Conference on Computer Vision (ACCV)
.
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Benjamin P. Chamberlain
,
Josh Levy-Kramer
,
Clive Humby
,
Marc P. Deisenroth
(2016).
Real-Time Community Detection in Large Social Networks on a Laptop
.
International Workshop on Mining and Learning with Graphs
.
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Matthew C. H. Lee
,
Hugh Salimbeni
,
Marc P. Deisenroth
,
Ben Glocker
(2016).
Patch Kernels for Gaussian Processes in High-Dimensional Imaging Problems
.
NIPS Workshop on Practical Bayesian Nonparametrics
.
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Roberto Calandra
,
Jan Peters
,
Carl E. Rasmussen
,
Marc P. Deisenroth
(2016).
Manifold Gaussian Processes for Regression
.
Proceedings of the IEEE International Joint Conference on Neural Networks (IJCNN)
.
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Maciej Kurek
,
Marc P. Deisenroth
,
Wayne Luk
,
Timothy Todman
(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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Hugh Salimbeni
,
Marc P. Deisenroth
(2016).
Gaussian Process Multiclass Classification with Dirichlet Priors for Imbalanced Data
.
NIPS Workshop on Practical Bayesian Nonparametrics
.
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Doniyor Ulmasov
,
Caroline Baroukh
,
Benoit Chachuat
,
Marc P. Deisenroth
,
Ruth Misener
(2016).
Bayesian Optimization with Dimension Scheduling: Application to Biological Systems
.
Proceedings of the European Symposium on Computer Aided Process Engineering (ESCAPE)
.
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Roberto Calandra
,
André Seyfarth
,
Jan Peters
,
Marc P. Deisenroth
(2016).
Bayesian Optimization for Learning Gaits under Uncertainty
.
Annals in Mathematics and Artificial Intelligence
.
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DOI
Marc P. Deisenroth
,
Jun W. Ng
(2015).
Robust Bayesian Committee Machine for Large-Scale Gaussian Processes
.
Large-Scale Kernel Machines Workshop at ICML 2015
.
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Roberto Calandra
,
Serena Ivaldi
,
Marc P. Deisenroth
,
Jan Peters
(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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Roberto Calandra
,
Serena Ivaldi
,
Marc P. Deisenroth
,
Elmar Rueckert
,
Jan Peters
(2015).
Learning Inverse Dynamics Models with Contacts
.
Proceedings of the IEEE International Conference on Robotics and Automation
.
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Niklas Wahlström
,
Thomas B. Schön
,
Marc P. Deisenroth
(2015).
Learning Deep Dynamical Models From Image Pixels
.
Proceedings of the IFAC Symposium on System Identification (SYSID)
.
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Marc P. Deisenroth
,
Dieter Fox
,
Carl E. Rasmussen
(2015).
Gaussian Processes for Data-Efficient Learning in Robotics and Control
.
IEEE Transactions on Pattern Analysis and Machine Intelligence
.
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Code
DOI
Niklas Wahlström
,
Thomas B. Schön
,
Marc P. Deisenroth
(2015).
From Pixels to Torques: Policy Learning with Deep Dynamical Models
.
Deep Learning Workshop at ICML 2015
.
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Marc P. Deisenroth
,
Jun W. Ng
(2015).
Distributed Gaussian Processes
.
Proceedings of the International Conference on Machine Learning (ICML)
.
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John-Alexander M. Assael
,
Niklas Wahlström
,
Thomas B. Schön
,
Marc P. Deisenroth
(2015).
Data-efficient Learning of Feedback Policies from Image Pixels using Deep Dynamical Models
.
arXiv:1510.02173
.
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Bastian Bischoff
,
Duy Nguyen-Tuong
,
Herke van Hoof
,
Andrew McHutchon
,
Carl E. Rasmussen
,
Alois Knoll
,
Jan Peters
,
Marc P. Deisenroth
(2014).
Policy Search For Learning Robot Control Using Sparse Data
.
Proceedings of the IEEE International Conference on Robotics and Automation (ICRA)
.
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Roberto Calandra
,
Jan Peters
,
Marc P. Deisenroth
(2014).
Pareto Front Modeling for Sensitivity Analysis in Multi-Objective Bayesian Optimization
.
Workshop on Bayesian Optimization in Academia and Industry at NIPS 2014
.
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Marc P. Deisenroth
,
Peter Englert
,
Jan Peters
,
Dieter Fox
(2014).
Multi-Task Policy Search for Robotics
.
Proceedings of the IEEE International Conference on Robotics and Automation (ICRA)
.
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Sanket Kamthe
,
Jan Peters
,
Marc P. Deisenroth
(2014).
Multi-Modal Filtering for Non-linear Estimation
.
International Conference on Acoustics, Speech, and Signal Processing (ICASSP)
.
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Arunkumar Byravan
,
Diete Fox
,
Marc P. Deisenroth
(2014).
Model-based Inverse Reinforcement Learning
.
Workshop on Autonomously Learning Robots at NIPS 2014
.
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Niklas Wahlström
,
Thomas B. Schön
,
Marc P. Deisenroth
(2014).
Learning Deep Dynamical Models From Image Pixels
.
arXiv:1410.7550
.
PDF
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Roberto Calandra
,
Nakul Gopalan
,
André Seyfarth
,
Jan Peters
,
Marc P. Deisenroth
(2014).
Bayesian Gait Optimization for Bipedal Locomotion
.
Proceedings of the International Conference on Learning and Intelligent Optimization (LION)
.
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Nooshin HajiGhassemi
,
Marc P. Deisenroth
(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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Roberto Calandra
,
Jan Peters
,
André Seyfarth
,
Marc P. Deisenroth
(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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Zhikun Wang
,
Katharina Mülling
,
Marc P. Deisenroth
,
Heni Ben Amor
,
David Vogt
,
Bernhard Schölkopf
,
Jan Peters
(2013).
Probabilistic Movement Modeling for Intention-based Decision Making
.
International Journal of Robotics Research (IJRR)
.
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Peter Englert
,
Alexandros Paraschos
,
Jan Peters
,
Marc P. Deisenroth
(2013).
Probabilistic Model-based Imitation Learning
.
Adaptive Behavior
.
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DOI
Peter Englert
,
Alexandros Paraschos
,
Jan Peters
,
Marc P. Deisenroth
(2013).
Model-based Imitation Learning by Probabilistic Trajectory Matching
.
Proceedings of the IEEE International Conference on Robotics and Automation (ICRA)
.
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Marc P. Deisenroth
,
Peter Engert
,
Alexandros Paraschos
,
Jan Peters
(2013).
Imitation Learning by Model-based Probabilistic Trajectory Matching
.
Workshop on Machine Learning and Cognitive Science
.
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Gerhard Neumann
,
Christian Daniel
,
Andras Kupcsik
,
Marc P. Deisenroth
,
Jan Peters
(2013).
Hierarchical Learning of Motor Skills with Information-Theoretic Policy Search
.
European Workshop on Reinforcement Learning (EWRL)
.
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Nakul Gopalan
,
Marc P. Deisenroth
,
Jan Peters
(2013).
Feedback Error Learning for Rhythmic Motor Primitives
.
Proceedings of the IEEE International Conference on Robotics and Automation (ICRA)
.
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Andras Kupcsik
,
Marc P. Deisenroth
,
Jan Peters
,
Gerhard Neumann
(2013).
Data-Efficient Generalization of Robot Skills with Contextual Policy Search
.
Proceedings of the AAAI Conference on Artificial Intelligence
.
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Roberto Calandra
,
Jan Peters
,
André Seyfarth
,
Marc P. Deisenroth
(2013).
An Experimental Evaluation of Bayesian Optimization on Bipedal Locomotion
.
Workshop on Bayesian Optimization at NIPS 2013
.
Cite
Peter Englert
,
Alexandros Paraschos
,
Jan Peters
,
Marc P. Deisenroth
(2013).
Addressing the Correspondence Problem by Model-based Imitation Learning
.
ICRA Workshop on Autonomous Learning
.
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Marc P. Deisenroth
,
Gerhard Neumann
,
Jan Peters
(2013).
A Survey on Policy Search for Robotics
.
Foundations and Trends in Robotics
.
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DOI
Marc P. Deisenroth
,
Shakir Mohamed
(2012).
Expectation Propagation in Gaussian Process Dynamical Systems
.
Advances in Neural Information Processing Systems (NIPS)
.
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Code
Marc P. Deisenroth
,
Roberto Calandra
,
André Seyfarth
,
Jan Peters
(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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Marc P. Deisenroth
,
Jan Peters
(2012).
Solving Nonlinear Continuous State-Action-Observation POMDPs for Mechanical Systems with Gaussian Noise
.
European Workshop on Reinforcement Learning (EWRL)
.
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Marc P. Deisenroth
,
Ryan Turner
,
Marco Huber
,
Uwe D. Hanebeck
,
Carl E. Rasmussen
(2012).
Robust Filtering and Smoothing with Gaussian Processes
.
IEEE Transactions on Automatic Control (IEEE-TAC)
.
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DOI
Marc P. Deisenroth
,
Csaba Szepesvári
,
Jan Peters
(2012).
Proceedings of the 10th European Workshop on Reinforcement Learning
.
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Zhikun Wang
,
Marc P. Deisenroth
,
Heni Ben Amor
,
David Vogt
,
Bernhard Schölkopf
,
Jan Peters
(2012).
Probabilistic Modeling of Human Dynamics for Intention Inference
.
Proceedings of Robotics: Science & Systems (RSS)
.
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Roberto Calandra
,
Tapani Raiko
,
Marc P. Deisenroth
,
Federico Montesino Pouzols
(2012).
Learning Deep Belief Networks from Non-Stationary Streams
.
Proceedings of International Conference on Artificial Neural Networks (ICANN)
.
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Marc P. Deisenroth
,
Peter Englert
,
Alexandros Paraschos
,
Jan Peters
,
Carl E. Rasmussen
,
Dieter Fox
(2012).
Autonomous Planning and Control with Bayesian Nonparametric Models
.
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Marc P. Deisenroth
,
Carl E. Rasmussen
(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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Code
Marc P. Deisenroth
,
Dieter Fox
(2011).
Multiple-Target Reinforcement Learning with a Single Policy
.
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Marc P. Deisenroth
,
Carl E. Rasmussen
,
Dieter Fox
(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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Marc P. Deisenroth
,
Dieter Fox
,
Carl E. Rasmussen
(2011).
Learning in Robotics using Bayesian Nonparametrics
.
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Cynthia Matuszek
,
Brian Mayton
,
Roberto Aimi
,
Marc P. Deisenroth
,
Liefeng Bo
,
Robert Chu
,
Michael Kung
,
Louis LeGrand
,
Joshua R. Smith
,
Dieter Fox
(2011).
Gambit: An Autonomous Chess-Playing Robotic System
.
Proceedings of the International Conference on Robotics and Automation (ICRA)
.
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Marc P. Deisenroth
,
Henrik Ohlsson
(2011).
A General Perspective on Gaussian Filtering and Smoothing: Explaining Current and Deriving New Algorithms
.
Proceedings of the American Control Conference (ACC)
.
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Marc P. Deisenroth
(2010).
Efficient Reinforcement Learning using Gaussian Processes
.
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Ryan Turner
,
Marc P. Deisenroth
,
Carl E. Rasmussen
(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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Marc P. Deisenroth
,
Carl E. Rasmussen
,
Jan Peters
(2009).
Gaussian Process Dynamic Programming
.
Neurocomputing
.
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DOI
Marc P. Deisenroth
(2009).
Efficient Reinforcement Learning using Gaussian Processes
.
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Marc P. Deisenroth
,
Carl E. Rasmussen
(2009).
Efficient Reinforcement Learning for Motor Control
.
Proceedings of the 10th International Workshop on Systems and Control
.
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Marc P. Deisenroth
,
Carl E. Rasmussen
(2009).
Bayesian Inference for Efficient Learning in Control
.
Multidisciplinary Symposium on Reinforcement Learning (MSRL)
.
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Marc P. Deisenroth
,
Marco F. Huber
,
Uwe D. Hanebeck
(2009).
Analytic Moment-based Gaussian Process Filtering
.
Proceedings of the 26th International Conference on Machine Learning (ICML)
.
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Carl E. Rasmussen
,
Marc P. Deisenroth
(2008).
Probabilistic Inference for Fast Learning in Control
.
European Workshop on Reinforcement Learning
.
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Marc P. Deisenroth
,
Carl E. Rasmussen
,
Jan Peters
(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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Marc P. Deisenroth
,
Jan Peters
,
Carl E. Rasmussen
(2008).
Approximate Dynamic Programming with Gaussian Processes
.
Proceedings of the 2008 American Control Conference (ACC)
.
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Marc P. Deisenroth
,
Florian Weissel
,
Toshiyuki Ohtsuka
,
Uwe D. Hanebeck
(2007).
Online-Computation Approach to Optimal Control of Noise-Affected Nonlinear Systems with Continuous State and Control Spaces
.
Proceedings of the European Control Conference 2007 (ECC)
.
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Marc P. Deisenroth
,
Toshiyuki Ohtsuka
,
Florian Weissel
,
Dietrich Brunn
,
Uwe D. Hanebeck
(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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DOI
Marc P. Deisenroth
(2006).
An Online Computation Approach to Optimal Finite-Horizon Control of Nonlinear Stochastic Systems
.
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Marc P. Deisenroth
(2004).
Toward Optimal Control of Nonlinear Systems with Continuous State Spaces
.
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