marc deisenroth - Robuta Search

https://www.deisenroth.cc/publication/ Publications | Marc Deisenroth Google DeepMind Chair of Machine Learning and Artificial Intelligence marc deisenroth publications https://www.deisenroth.cc/authors/diego-mesquita/ Diego Mesquita | Marc Deisenroth Google DeepMind Chair of Machine Learning and Artificial Intelligence marc deisenroth diego mesquita https://www.deisenroth.cc/authors/lucas-cosier/ Lucas Cosier | Marc Deisenroth Google DeepMind Chair of Machine Learning and Artificial Intelligence marc deisenroth lucas https://www.deisenroth.cc/ Marc Deisenroth Google DeepMind Chair of Machine Learning and Artificial Intelligence marc deisenroth https://www.deisenroth.cc/publication/gopakumar-2026/ Uncertainty Quantification of Surrogate Models Using Conformal Prediction | Marc Deisenroth Feb 3, 2026 - Data-driven surrogate models offer fast, inexpensive approximations to complex numerical and experimental systems but typically lack uncertainty... marc deisenroth uncertainty quantification surrogate models https://www.deisenroth.cc/authors/james-hensman/ James Hensman | Marc Deisenroth Google DeepMind Chair of Machine Learning and Artificial Intelligence marc deisenroth james https://www.deisenroth.cc/authors/ognjen-rudovic/ Ognjen Rudovic | Marc Deisenroth Google DeepMind Chair of Machine Learning and Artificial Intelligence marc deisenroth https://www.deisenroth.cc/authors/rendani-mbuvha/ Rendani Mbuvha | Marc Deisenroth Google DeepMind Chair of Machine Learning and Artificial Intelligence marc deisenroth https://www.deisenroth.cc/authors/william-agnew/ William Agnew | Marc Deisenroth Google DeepMind Chair of Machine Learning and Artificial Intelligence marc deisenroth william https://www.deisenroth.cc/talk/ Talks | Marc Deisenroth Google DeepMind Chair of Machine Learning and Artificial Intelligence marc deisenroth talks https://www.deisenroth.cc/publication/hadjivelichkov-2025/ Semantic Cross-Pose Correspondence from a Single Example | Marc Deisenroth Feb 3, 2025 - This article focuses on predicting how an object can be transformed to a semantically meaningful pose relative to another object, given only one or few... marc deisenroth semantic cross pose correspondence https://www.deisenroth.cc/authors/josh-levy-kramer/ Josh Levy-Kramer | Marc Deisenroth Google DeepMind Chair of Machine Learning and Artificial Intelligence marc deisenroth josh levy kramer https://www.deisenroth.cc/authors/matt-kusner/ Matt Kusner | Marc Deisenroth Google DeepMind Chair of Machine Learning and Artificial Intelligence marc deisenroth matt https://www.deisenroth.cc/authors/dieter-fox/ Dieter Fox | Marc Deisenroth Google DeepMind Chair of Machine Learning and Artificial Intelligence marc deisenroth dieter fox https://www.deisenroth.cc/authors/timothy-nunn/ Timothy Nunn | Marc Deisenroth Google DeepMind Chair of Machine Learning and Artificial Intelligence marc deisenroth timothy nunn