Choosing the Infrastructure for Entertainment and Serious Computer Games - a Whiteroom Benchmark for Game Engine Selection. - Eike Falk Anderson; Leigh McLoughlin; Joe Watson; Sam Holmes; Peter Jones; Hayden Pallett; Brendan Smith (VS-GAMES, 2013)

Real-World, Real-Time Robotic Grasping with Convolutional Neural Networks. - Joe Watson; Josie Hughes; Fumiya Iida (TAROS, 2017)

Stochastic Optimal Control as Approximate Input Inference. - Joe Watson; Hany Abdulsamad; Jan Peters 001 (CoRL, 2019)

Active Inference or Control as Inference? A Unifying View. - Abraham Imohiosen; Joe Watson; Jan Peters 001 (IWAI, 2020)

A Differentiable Newton Euler Algorithm for Multi-body Model Learning. - Michael Lutter; Johannes Silberbauer; Joe Watson; Jan Peters 001 (CoRR, 2020)

Latent Derivative Bayesian Last Layer Networks. - Joe Watson; Jihao Andreas Lin; Pascal Klink; Joni Pajarinen; Jan Peters 001 (AISTATS, 2021)

Advancing Trajectory Optimization with Approximate Inference: Exploration, Covariance Control and Adaptive Risk. - Joe Watson; Jan Peters 001 (ACC, 2021)

Differentiable Physics Models for Real-world Offline Model-based Reinforcement Learning. - Michael Lutter; Johannes Silberbauer; Joe Watson; Jan Peters 001 (ICRA, 2021)

Real Robot Challenge: A Robotics Competition in the Cloud. - Stefan Bauer; Manuel Wüthrich; Felix Widmaier; Annika Buchholz; Sebastian Stark; Anirudh Goyal; Thomas Steinbrenner; Joel Akpo; Shruti Joshi; Vincent Berenz; Vaibhav Agrawal; Niklas Funk; et al. (NeurIPS (Competition and Demos), 2021)

The relationship between educational television and mathematics capability in Tanzania. - Joe Watson; Sara Hennessy; Anna Vignoles (Br. J. Educ. Technol., 2021)

Stochastic Control through Approximate Bayesian Input Inference. - Joe Watson; Hany Abdulsamad; Rolf Findeisen; Jan Peters 001 (CoRR, 2021)

A Robot Cluster for Reproducible Research in Dexterous Manipulation. - Stefan Bauer; Felix Widmaier; Manuel Wüthrich; Niklas Funk; Julen Urain De Jesus; Jan Peters 001; Joe Watson; Claire Chen; Krishnan Srinivasan; Junwu Zhang; Jeffrey Zhang 005; Matthew R. Walter; et al. (CoRR, 2021)

A Differentiable Newton-Euler Algorithm for Real-World Robotics. - Michael Lutter; Johannes Silberbauer; Joe Watson; Jan Peters 001 (CoRR, 2021)

Inferring Smooth Control: Monte Carlo Posterior Policy Iteration with Gaussian Processes. - Joe Watson; Jan Peters 001 (CoRL, 2022)

Benchmarking Structured Policies and Policy Optimization for Real-World Dexterous Object Manipulation. - Niklas Funk; Charles B. Schaff; Rishabh Madan; Takuma Yoneda; Julen Urain De Jesus; Joe Watson; Ethan K. Gordon; Felix Widmaier; Stefan Bauer; Siddhartha S. Srinivasa; Tapomayukh Bhattacharjee; Matthew R. Walter; et al. (IEEE Robotics Autom. Lett., 2022)

RFDesign: Protein hallucination and inpainting with RosettaFold. - Jue Wang; Sidney Lisanza; David Juergens; Doug Tischer; Joe Watson (Zenodo, 2022)

RFDesign: Protein hallucination and inpainting with RosettaFold. - Jue Wang; Sidney Lisanza; David Juergens; Doug Tischer; Joe Watson; Ivan Anishchenko; Minkyung Baek; Justas Dauparas; Sergey Ovchinnikov (Zenodo, 2022)

Coherent Soft Imitation Learning. - Joe Watson; Sandy H. Huang; Nicolas Heess (NeurIPS, 2023)

Function-Space Regularization for Deep Bayesian Classification. - Jihao Andreas Lin; Joe Watson; Pascal Klink; Jan Peters 001 (CoRR, 2023)

Using machine learning to create a repository of judgments concerning a new practice area: a case study in animal protection law. - Joe Watson; Guy Aglionby; Samuel March (Artif. Intell. Law, 2023)

An exploratory investigation into the factors related to EdTech use among Kenyan girls. - Joe Watson; Jasmin Baier; Winnie Mughogho; Mark Millrine (Br. J. Educ. Technol., 2023)

Global Tensor Motion Planning. - An T. Le 001; Kay Hansel; João Carvalho; Joe Watson; Julen Urain; Armin Biess; Georgia Chalvatzaki; Jan Peters 001 (CoRR, 2024)

Machine Learning with Physics Knowledge for Prediction: A Survey. - Joe Watson; Chen Song; Oliver Weeger; Theo Gruner; An Thai Le 001; Kay Hansel; Ahmed Hendawy; Oleg Arenz; Will Trojak; Miles D. Cranmer; Carlo D'Eramo; Fabian Bülow; et al. (Trans. Mach. Learn. Res., 2025)

Towards Safe Robot Foundation Models. - Maximilian Tölle; Theo Gruner; Daniel Palenicek; Jonas Günster; Puze Liu; Joe Watson; Davide Tateo; Jan Peters 001 (CoRR, 2025)

Towards Safe Robot Foundation Models Using Inductive Biases. - Maximilian Tölle; Theo Gruner; Daniel Palenicek; Tim Schneider; Jonas Günster; Joe Watson; Davide Tateo; Puze Liu; Jan Peters 001 (CoRR, 2025)

Global Tensor Motion Planning. - An T. Le 001; Kay Pompetzki; João Carvalho; Joe Watson; Julen Urain; Armin Biess; Georgia Chalvatzaki; Jan Peters 001 (IEEE Robotics Autom. Lett., 2025)