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Marc Peter Deisenroth

Identifiers

  • name variant Marc Peter Deisenroth 0.60 · backfill

Papers (29)

  1. Learning Physical Operators using Neural Operators cs.LG · 2026 · author #8
  2. Mat\'ern Gaussian Processes on Graphs stat.ML · 2020 · author #5
  3. Deep Gaussian Processes with Importance-Weighted Variational Inference stat.ML · 2019 · author #4
  4. Differentially Private Empirical Risk Minimization with Sparsity-Inducing Norms cs.LG · 2019 · author #2
  5. GPdoemd: a Python package for design of experiments for model discrimination cs.MS · 2018 · author #4
  6. Maximizing acquisition functions for Bayesian optimization stat.ML · 2018 · author #3
  7. Meta Reinforcement Learning with Latent Variable Gaussian Processes stat.ML · 2018 · author #3
  8. Design of Experiments for Model Discrimination Hybridising Analytical and Data-Driven Approaches stat.AP · 2018 · author #2
  9. The reparameterization trick for acquisition functions stat.ML · 2017 · author #4
  10. A Brief Survey of Deep Reinforcement Learning cs.LG · 2017 · author #2
  11. Data-Efficient Reinforcement Learning with Probabilistic Model Predictive Control cs.SY · 2017 · author #2
  12. Identification of Gaussian Process State Space Models stat.ML · 2017 · author #3
  13. Neural Embeddings of Graphs in Hyperbolic Space stat.ML · 2017 · author #3
  14. Customer Lifetime Value Prediction Using Embeddings cs.LG · 2017 · author #5
  15. Accelerating the BSM interpretation of LHC data with machine learning hep-ph · 2016 · author #2
  16. Probabilistic Inference of Twitter Users' Age based on What They Follow cs.SI · 2016 · author #3
  17. Real-Time Community Detection in Large Social Networks on a Laptop cs.SI · 2016 · author #4
  18. Bayesian Optimization with Dimension Scheduling: Application to Biological Systems stat.ML · 2015 · author #4
  19. Data-Efficient Learning of Feedback Policies from Image Pixels using Deep Dynamical Models cs.AI · 2015 · author #4
  20. Gaussian Processes for Data-Efficient Learning in Robotics and Control stat.ML · 2015 · author #1
  21. Distributed Gaussian Processes stat.ML · 2015 · author #1
  22. From Pixels to Torques: Policy Learning with Deep Dynamical Models stat.ML · 2015 · author #3
  23. Hierarchical Mixture-of-Experts Model for Large-Scale Gaussian Process Regression stat.ML · 2014 · author #2
  24. Learning deep dynamical models from image pixels stat.ML · 2014 · author #3
  25. Manifold Gaussian Processes for Regression stat.ML · 2014 · author #4
  26. Multi-Task Policy Search stat.ML · 2013 · author #1
  27. Expectation Propagation in Gaussian Process Dynamical Systems: Extended Version stat.ML · 2012 · author #1
  28. Robust Filtering and Smoothing with Gaussian Processes cs.SY · 2012 · author #1
  29. 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