Marc Peter Deisenroth
Identifiers
- name variant Marc Peter Deisenroth 0.60 · backfill
Papers (29)
- Learning Physical Operators using Neural Operators cs.LG · 2026 · author #8
- Mat\'ern Gaussian Processes on Graphs stat.ML · 2020 · author #5
- Deep Gaussian Processes with Importance-Weighted Variational Inference stat.ML · 2019 · author #4
- Differentially Private Empirical Risk Minimization with Sparsity-Inducing Norms cs.LG · 2019 · author #2
- GPdoemd: a Python package for design of experiments for model discrimination cs.MS · 2018 · author #4
- Maximizing acquisition functions for Bayesian optimization stat.ML · 2018 · author #3
- Meta Reinforcement Learning with Latent Variable Gaussian Processes stat.ML · 2018 · author #3
- Design of Experiments for Model Discrimination Hybridising Analytical and Data-Driven Approaches stat.AP · 2018 · author #2
- The reparameterization trick for acquisition functions stat.ML · 2017 · author #4
- A Brief Survey of Deep Reinforcement Learning cs.LG · 2017 · author #2
- Data-Efficient Reinforcement Learning with Probabilistic Model Predictive Control cs.SY · 2017 · author #2
- Identification of Gaussian Process State Space Models stat.ML · 2017 · author #3
- Neural Embeddings of Graphs in Hyperbolic Space stat.ML · 2017 · author #3
- Customer Lifetime Value Prediction Using Embeddings cs.LG · 2017 · author #5
- Accelerating the BSM interpretation of LHC data with machine learning hep-ph · 2016 · author #2
- Probabilistic Inference of Twitter Users' Age based on What They Follow cs.SI · 2016 · author #3
- Real-Time Community Detection in Large Social Networks on a Laptop cs.SI · 2016 · author #4
- Bayesian Optimization with Dimension Scheduling: Application to Biological Systems stat.ML · 2015 · author #4
- Data-Efficient Learning of Feedback Policies from Image Pixels using Deep Dynamical Models cs.AI · 2015 · author #4
- Gaussian Processes for Data-Efficient Learning in Robotics and Control stat.ML · 2015 · author #1
- Distributed Gaussian Processes stat.ML · 2015 · author #1
- From Pixels to Torques: Policy Learning with Deep Dynamical Models stat.ML · 2015 · author #3
- Hierarchical Mixture-of-Experts Model for Large-Scale Gaussian Process Regression stat.ML · 2014 · author #2
- Learning deep dynamical models from image pixels stat.ML · 2014 · author #3
- Manifold Gaussian Processes for Regression stat.ML · 2014 · author #4
- Multi-Task Policy Search stat.ML · 2013 · author #1
- Expectation Propagation in Gaussian Process Dynamical Systems: Extended Version stat.ML · 2012 · author #1
- Robust Filtering and Smoothing with Gaussian Processes cs.SY · 2012 · author #1
- A Probabilistic Perspective on Gaussian Filtering and Smoothing stat.ME · 2010 · author #1
Mentions
- 1410.7550 #3 · backfill · confidence 0.70 Marc Peter Deisenroth
- 1402.5876 #4 · backfill · confidence 0.70 Marc Peter Deisenroth
- 1307.0813 #1 · backfill · confidence 0.70 Marc Peter Deisenroth
- 1207.2940 #1 · backfill · confidence 0.70 Marc Peter Deisenroth
- 1203.4345 #1 · backfill · confidence 0.70 Marc Peter Deisenroth
- 2010.15538 #5 · arxiv_oai · confidence 0.70 Marc Peter Deisenroth
- 1006.2165 #1 · backfill · confidence 0.70 Marc Peter Deisenroth
Frequent Coauthors
- Benjamin Paul Chamberlain 4 shared papers
- Carl Edward Rasmussen 3 shared papers
- Niklas Wahlstr\"om 3 shared papers
- Ruth Misener 3 shared papers
- Thomas B. Sch\"on 3 shared papers
- Clive Humby 2 shared papers
- Dieter Fox 2 shared papers
- Frank Hutter 2 shared papers
- James Hensman 2 shared papers
- James T. Wilson 2 shared papers
- Jan Peters 2 shared papers
- Jun Wei Ng 2 shared papers
- Simon Olofsson 2 shared papers
- Alexander Terenin 1 shared papers
- Ander Gray 1 shared papers
- Angelo Cardoso 1 shared papers
- Anil Anthony Bharath 1 shared papers
- Benoit Chachuat 1 shared papers
- Caroline Baroukh 1 shared papers
- C.H. Bryan Liu 1 shared papers