Marc Peter Deisenroth

ORCID

Publication Activity (10 Years)

Years Active: 2006-2023
Publications (10 Years): 115

Top Venues

Karlsruhe Institute of Technology (PHD)

Education History

Karlsruhe Institute of Technology

PHD

Publications

Sicelukwanda Zwane, Denis Hadjivelichkov, Yicheng Luo, Yasemin Bekiroglu, Dimitrios Kanoulas, Marc Peter Deisenroth
Safe Trajectory Sampling in Model-Based Reinforcement Learning. CASE (2023)
Yicheng Luo, Jackie Kay, Edward Grefenstette, Marc Peter Deisenroth
Finetuning from Offline Reinforcement Learning: Challenges, Trade-offs and Practical Solutions. CoRR (2023)
Sean Nassimiha, Peter Dudfield, Jack Kelly, Marc Peter Deisenroth, So Takao
Short-term Prediction and Filtering of Solar Power Using State-Space Gaussian Processes. CoRR (2023)
Vignesh Gopakumar, Stanislas Pamela, Lorenzo Zanisi, Zongyi Li, Ander Gray, Daniel Brennand, Nitesh Bhatia, Gregory Stathopoulos, Matt Kusner, Marc Peter Deisenroth, Anima Anandkumar, JOREK Team, MAST Team
Plasma Surrogate Modelling using Fourier Neural Operators. CoRR (2023)
Lucas Cosier, Rares Iordan, Sicelukwanda Zwane, Giovanni Franzese, James T. Wilson, Marc Peter Deisenroth, Alexander Terenin, Yasemin Bekiroglu
A Unifying Variational Framework for Gaussian Process Motion Planning. CoRR (2023)
Suman V. Ravuri, Mélanie Rey, Shakir Mohamed, Marc Peter Deisenroth
Understanding Deep Generative Models with Generalized Empirical Likelihoods. CoRR (2023)
Yicheng Luo, Zhengyao Jiang, Samuel Cohen, Edward Grefenstette, Marc Peter Deisenroth
Optimal Transport for Offline Imitation Learning. CoRR (2023)
Yicheng Luo, Zhengyao Jiang, Samuel Cohen, Edward Grefenstette, Marc Peter Deisenroth
Optimal Transport for Offline Imitation Learning. ICLR (2023)
Mihaela Rosca, Marc Peter Deisenroth
Implicit regularisation in stochastic gradient descent: from single-objective to two-player games. CoRR (2023)
Harry Jake Cunningham, Daniel Augusto de Souza, So Takao, Mark van der Wilk, Marc Peter Deisenroth
Actually Sparse Variational Gaussian Processes. CoRR (2023)
Suman V. Ravuri, Mélanie Rey, Shakir Mohamed, Marc Peter Deisenroth
Understanding Deep Generative Models with Generalized Empirical Likelihoods. CVPR (2023)
Ahmet Ercan Tekden, Marc Peter Deisenroth, Yasemin Bekiroglu
Grasp Transfer based on Self-Aligning Implicit Representations of Local Surfaces. CoRR (2023)
Ahmet Ercan Tekden, Marc Peter Deisenroth, Yasemin Bekiroglu
Grasp Transfer Based on Self-Aligning Implicit Representations of Local Surfaces. IEEE Robotics Autom. Lett. 8 (10) (2023)
Yiting Chen, Ahmet Ercan Tekden, Marc Peter Deisenroth, Yasemin Bekiroglu
Sliding Touch-Based Exploration for Modeling Unknown Object Shape with Multi-Fingered Hands. IROS (2023)
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
Queer In AI: A Case Study in Community-Led Participatory AI. FAccT (2023)
Harry Jake Cunningham, Daniel Augusto de Souza, So Takao, Mark van der Wilk, Marc Peter Deisenroth
Actually Sparse Variational Gaussian Processes. AISTATS (2023)
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
Queer In AI: A Case Study in Community-Led Participatory AI. CoRR (2023)
Ahmet Ercan Tekden, Marc Peter Deisenroth, Yasemin Bekiroglu
Neural Field Movement Primitives for Joint Modelling of Scenes and Motions. IROS (2023)
Daniel Augusto de Souza, Alexander Nikitin, ST John, Magnus Ross, Mauricio A. Álvarez, Marc Peter Deisenroth, João Paulo Pordeus Gomes, Diego Mesquita, César C. Lincoln Mattos
Thin and deep Gaussian processes. NeurIPS (2023)
Yiting Chen, Ahmet Ercan Tekden, Marc Peter Deisenroth, Yasemin Bekiroglu
Sliding Touch-based Exploration for Modeling Unknown Object Shape with Multi-fingered Hands. CoRR (2023)
Mathieu Alain, So Takao, Brooks Paige, Marc Peter Deisenroth
Gaussian Processes on Cellular Complexes. CoRR (2023)
Ahmet Ercan Tekden, Marc Peter Deisenroth, Yasemin Bekiroglu
Neural Field Movement Primitives for Joint Modelling of Scenes and Motions. CoRR (2023)
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
Thin and Deep Gaussian Processes. CoRR (2023)
Rares Iordan, Marc Peter Deisenroth, Mihaela Rosca
Investigating the Edge of Stability Phenomenon in Reinforcement Learning. CoRR (2023)
Ilana Sebag, Samuel Cohen, Marc Peter Deisenroth
On Combining Expert Demonstrations in Imitation Learning via Optimal Transport. CoRR (2023)
Alexander Norcliffe, Marc Peter Deisenroth
Faster Training of Neural ODEs Using Gauß-Legendre Quadrature. CoRR (2023)
Hadi Hajieghrary, Marc Peter Deisenroth, Yasemin Bekiroglu
Bayesian Optimization-based Nonlinear Adaptive PID Controller Design for Robust Mobile Manipulation. CoRR (2022)
Hadi Hajieghrary, Marc Peter Deisenroth, Yasemin Bekiroglu
Bayesian Optimization-based Nonlinear Adaptive PID Controller Design for Robust Mobile Manipulation. CASE (2022)
Linh Tran, Maja Pantic, Marc Peter Deisenroth
Cauchy-Schwarz Regularized Autoencoder. J. Mach. Learn. Res. 23 (2022)
Sanket Kamthe, So Takao, Shakir Mohamed, Marc Peter Deisenroth
Iterative State Estimation in Non-linear Dynamical Systems Using Approximate Expectation Propagation. Trans. Mach. Learn. Res. 2022 (2022)
Zuka Murvanidze, Marc Peter Deisenroth, Yasemin Bekiroglu
Enhanced GPIS Learning Based on Local and Global Focus Areas. IEEE Robotics Autom. Lett. 7 (4) (2022)
Michelangelo Conserva, Marc Peter Deisenroth, K. S. Sesh Kumar
The Graph Cut Kernel for Ranked Data. Trans. Mach. Learn. Res. 2022 (2022)
Denis Hadjivelichkov, Sicelukwanda Zwane, Lourdes Agapito, Marc Peter Deisenroth, Dimitrios Kanoulas
One-Shot Transfer of Affordance Regions? AffCorrs! CoRL (2022)
Denis Hadjivelichkov, Sicelukwanda Zwane, Marc Peter Deisenroth, Lourdes Agapito, Dimitrios Kanoulas
One-Shot Transfer of Affordance Regions? AffCorrs! CoRR (2022)
Viacheslav Borovitskiy, Iskander Azangulov, Alexander Terenin, Peter Mostowsky, Marc Peter Deisenroth, Nicolas Durrande
Matérn Gaussian Processes on Graphs. AISTATS (2021)
Sanket Kamthe, Samuel Assefa, Marc Peter Deisenroth
Copula Flows for Synthetic Data Generation. CoRR (2021)
Samuel Cohen, Rendani Mbuvha, Tshilidzi Marwala, Marc Peter Deisenroth
Healing Products of Gaussian Processes. CoRR (2021)
Samuel Cohen, K. S. Sesh Kumar, Marc Peter Deisenroth
Sliced Multi-Marginal Optimal Transport. CoRR (2021)
Michael Hutchinson, Alexander Terenin, Viacheslav Borovitskiy, So Takao, Yee Whye Teh, Marc Peter Deisenroth
Vector-valued Gaussian Processes on Riemannian Manifolds via Gauge Independent Projected Kernels. NeurIPS (2021)
Vu Nguyen, Marc Peter Deisenroth, Michael A. Osborne
Gaussian Process Sampling and Optimization with Approximate Upper and Lower Bounds. CoRR (2021)
Michelangelo Conserva, Marc Peter Deisenroth, K. S. Sesh Kumar
Submodular Kernels for Efficient Rankings. CoRR (2021)
Linh Tran, Maja Pantic, Marc Peter Deisenroth
Cauchy-Schwarz Regularized Autoencoder. CoRR (2021)
Samuel Cohen, Giulia Luise, Alexander Terenin, Brandon Amos, Marc Peter Deisenroth
Aligning Time Series on Incomparable Spaces. AISTATS (2021)
Vincent Dutordoir, Hugh Salimbeni, Eric Hambro, John McLeod, Felix Leibfried, Artem Artemev, Mark van der Wilk, James Hensman, Marc Peter Deisenroth, S. T. John
GPflux: A Library for Deep Gaussian Processes. CoRR (2021)
Simon Olofsson, Eduardo S. Schultz, Adel Mhamdi, Alexander Mitsos, Marc Peter Deisenroth, Ruth Misener
Design of Dynamic Experiments for Black-Box Model Discrimination. CoRR (2021)
Andreas Hochlehnert, Alexander Terenin, Steindór Sæmundsson, Marc Peter Deisenroth
Learning Contact Dynamics using Physically Structured Neural Networks. CoRR (2021)
James T. Wilson, Viacheslav Borovitskiy, Alexander Terenin, Peter Mostowsky, Marc Peter Deisenroth
Pathwise Conditioning of Gaussian Processes. J. Mach. Learn. Res. 22 (2021)
Janith C. Petangoda, Marc Peter Deisenroth, Nicholas A. M. Monk
Learning to Transfer: A Foliated Theory. CoRR (2021)
Michael Hutchinson, Alexander Terenin, Viacheslav Borovitskiy, So Takao, Yee Whye Teh, Marc Peter Deisenroth
Vector-valued Gaussian Processes on Riemannian Manifolds via Gauge Equivariant Projected Kernels. CoRR (2021)
Andreas Hochlehnert, Alexander Terenin, Steindór Sæmundsson, Marc Peter Deisenroth
Learning Contact Dynamics using Physically Structured Neural Networks. AISTATS (2021)
Martin Jørgensen, Marc Peter Deisenroth, Hugh Salimbeni
Stochastic Differential Equations with Variational Wishart Diffusions. ICML (2020)
James T. Wilson, Viacheslav Borovitskiy, Alexander Terenin, Peter Mostowsky, Marc Peter Deisenroth
Efficiently sampling functions from Gaussian process posteriors. CoRR (2020)
James T. Wilson, Viacheslav Borovitskiy, Alexander Terenin, Peter Mostowsky, Marc Peter Deisenroth
Pathwise Conditioning of Gaussian Processes. CoRR (2020)
Janith C. Petangoda, Nick A. M. Monk, Marc Peter Deisenroth
A Foliated View of Transfer Learning. CoRR (2020)
Riccardo Moriconi, Marc Peter Deisenroth, K. S. Sesh Kumar
High-dimensional Bayesian optimization using low-dimensional feature spaces. Mach. Learn. 109 (9-10) (2020)
Jean Kaddour, Steindór Sæmundsson, Marc Peter Deisenroth
Probabilistic Active Meta-Learning. NeurIPS (2020)
Viacheslav Borovitskiy, Alexander Terenin, Peter Mostowsky, Marc Peter Deisenroth
Matern Gaussian processes on Riemannian manifolds. CoRR (2020)
Samuel Cohen, Giulia Luise, Alexander Terenin, Brandon Amos, Marc Peter Deisenroth
Aligning Time Series on Incomparable Spaces. CoRR (2020)
Steindór Sæmundsson, Alexander Terenin, Katja Hofmann, Marc Peter Deisenroth
Variational Integrator Networks for Physically Structured Embeddings. AISTATS (2020)
Jean Kaddour, Steindór Sæmundsson, Marc Peter Deisenroth
Probabilistic Active Meta-Learning. CoRR (2020)
Riccardo Moriconi, K. S. Sesh Kumar, Marc Peter Deisenroth
High-dimensional Bayesian optimization with projections using quantile Gaussian processes. Optim. Lett. 14 (1) (2020)
Viacheslav Borovitskiy, Iskander Azangulov, Alexander Terenin, Peter Mostowsky, Marc Peter Deisenroth, Nicolas Durrande
Matern Gaussian Processes on Graphs. CoRR (2020)
Samuel Cohen, Rendani Mbuvha, Tshilidzi Marwala, Marc Peter Deisenroth
Healing Products of Gaussian Process Experts. ICML (2020)
Samuel Cohen, Michael Arbel, Marc Peter Deisenroth
Estimating Barycenters of Measures in High Dimensions. CoRR (2020)
James T. Wilson, Viacheslav Borovitskiy, Alexander Terenin, Peter Mostowsky, Marc Peter Deisenroth
Efficiently sampling functions from Gaussian process posteriors. ICML (2020)
Martin Jørgensen, Marc Peter Deisenroth, Hugh Salimbeni
Stochastic Differential Equations with Variational Wishart Diffusions. CoRR (2020)
Daniel Lengyel, Janith C. Petangoda, Isak Falk, Kate Highnam, Michalis Lazarou, Arinbjörn Kolbeinsson, Marc Peter Deisenroth, Nicholas R. Jennings
GENNI: Visualising the Geometry of Equivalences for Neural Network Identifiability. CoRR (2020)
Viacheslav Borovitskiy, Alexander Terenin, Peter Mostowsky, Marc Peter Deisenroth
Matérn Gaussian Processes on Riemannian Manifolds. NeurIPS (2020)
Hugh Salimbeni, Vincent Dutordoir, James Hensman, Marc Peter Deisenroth
Deep Gaussian Processes with Importance-Weighted Variational Inference. ICML (2019)
Riccardo Moriconi, K. S. Sesh Kumar, Marc Peter Deisenroth
High-Dimensional Bayesian Optimization with Manifold Gaussian Processes. CoRR (2019)
K. S. Sesh Kumar, Marc Peter Deisenroth
Differentially Private Empirical Risk Minimization with Sparsity-Inducing Norms. CoRR (2019)
Simon Olofsson, Lukas Hebing, Sebastian Niedenführ, Marc Peter Deisenroth, Ruth Misener
GPdoemd: A Python package for design of experiments for model discrimination. Comput. Chem. Eng. 125 (2019)
Steindór Sæmundsson, Alexander Terenin, Katja Hofmann, Marc Peter Deisenroth
Variational Integrator Networks for Physically Meaningful Embeddings. CoRR (2019)
Hugh Salimbeni, Vincent Dutordoir, James Hensman, Marc Peter Deisenroth
Deep Gaussian Processes with Importance-Weighted Variational Inference. CoRR (2019)
Simon Olofsson, Mohammad Mehrian, Roberto Calandra, Liesbet Geris, Marc Peter Deisenroth, Ruth Misener
Bayesian Multiobjective Optimisation With Mixed Analytical and Black-Box Functions: Application to Tissue Engineering. IEEE Trans. Biomed. Eng. 66 (3) (2019)
Sanket Kamthe, Marc Peter Deisenroth
Data-Efficient Reinforcement Learning with Probabilistic Model Predictive Control. AISTATS (2018)
Vincent Dutordoir, Hugh Salimbeni, James Hensman, Marc Peter Deisenroth
Gaussian Process Conditional Density Estimation. NeurIPS (2018)
Steindór Sæmundsson, Katja Hofmann, Marc Peter Deisenroth
Meta Reinforcement Learning with Latent Variable Gaussian Processes. CoRR (2018)
Simon Olofsson, Marc Peter Deisenroth, Ruth Misener
Design of Experiments for Model Discrimination Hybridising Analytical and Data-Driven Approaches. ICML (2018)
Vincent Dutordoir, Hugh Salimbeni, Marc Peter Deisenroth, James Hensman
Gaussian Process Conditional Density Estimation. CoRR (2018)
James T. Wilson, Frank Hutter, Marc Peter Deisenroth
Maximizing acquisition functions for Bayesian optimization. NeurIPS (2018)
Hugh Salimbeni, Ching-An Cheng, Byron Boots, Marc Peter Deisenroth
Orthogonally Decoupled Variational Gaussian Processes. CoRR (2018)
Steindór Sæmundsson, Katja Hofmann, Marc Peter Deisenroth
Meta Reinforcement Learning with Latent Variable Gaussian Processes. UAI (2018)
Hugh Salimbeni, Ching-An Cheng, Byron Boots, Marc Peter Deisenroth
Orthogonally Decoupled Variational Gaussian Processes. NeurIPS (2018)
James T. Wilson, Frank Hutter, Marc Peter Deisenroth
Maximizing acquisition functions for Bayesian optimization. CoRR (2018)
Kai Arulkumaran, Marc Peter Deisenroth, Miles Brundage, Anil Anthony Bharath
A Brief Survey of Deep Reinforcement Learning. CoRR (2017)
James T. Wilson, Riccardo Moriconi, Frank Hutter, Marc Peter Deisenroth
The reparameterization trick for acquisition functions. CoRR (2017)
Kai Arulkumaran, Marc Peter Deisenroth, Miles Brundage, Anil Anthony Bharath
Deep Reinforcement Learning: A Brief Survey. IEEE Signal Process. Mag. 34 (6) (2017)
Andras Gabor Kupcsik, Marc Peter Deisenroth, Jan Peters, Ai Poh Loh, Prahlad Vadakkepat, Gerhard Neumann
Model-based contextual policy search for data-efficient generalization of robot skills. Artif. Intell. 247 (2017)
Benjamin Paul Chamberlain, Clive Humby, Marc Peter Deisenroth
Probabilistic Inference of Twitter Users' Age Based on What They Follow. ECML/PKDD (3) (2017)
Hugh Salimbeni, Marc Peter Deisenroth
Doubly Stochastic Variational Inference for Deep Gaussian Processes. NIPS (2017)
Stefanos Eleftheriadis, Ognjen Rudovic, Marc Peter Deisenroth, Maja Pantic
Gaussian Process Domain Experts for Modeling of Facial Affect. IEEE Trans. Image Process. 26 (10) (2017)
Benjamin Paul Chamberlain, James R. Clough, Marc Peter Deisenroth
Neural Embeddings of Graphs in Hyperbolic Space. CoRR (2017)
Benjamin Paul Chamberlain, Ângelo Cardoso, C. H. Bryan Liu, Roberto Pagliari, Marc Peter Deisenroth
Customer Life Time Value Prediction Using Embeddings. CoRR (2017)
Benjamin Paul Chamberlain, Ângelo Cardoso, C. H. Bryan Liu, Roberto Pagliari, Marc Peter Deisenroth
Customer Lifetime Value Prediction Using Embeddings. KDD (2017)
Stefanos Eleftheriadis, Tom Nicholson, Marc Peter Deisenroth, James Hensman
Identification of Gaussian Process State Space Models. NIPS (2017)
Sanket Kamthe, Marc Peter Deisenroth
Data-Efficient Reinforcement Learning with Probabilistic Model Predictive Control. CoRR (2017)
Roberto Calandra, Jan Peters, Carl Edward Rasmussen, Marc Peter Deisenroth
Manifold Gaussian Processes for regression. IJCNN (2016)
Stefanos Eleftheriadis, Ognjen Rudovic, Marc Peter Deisenroth, Maja Pantic
Variational Gaussian Process Auto-Encoder for Ordinal Prediction of Facial Action Units. ACCV (2) (2016)
Stefanos Eleftheriadis, Ognjen Rudovic, Marc Peter Deisenroth, Maja Pantic
Gaussian Process Domain Experts for Model Adaptation in Facial Behavior Analysis. CVPR Workshops (2016)

Marc Peter Deisenroth.css-eqlu8i{font-size:small;padding-left:4px;}

Publication Activity (10 Years)

Top Topics

Top Venues

Marc Peter Deisenroth