Learning Certified Individually Fair Representations. - Anian Ruoss; Mislav Balunovic; Marc Fischer 002; Martin T. Vechev (NeurIPS, 2020)

Efficient Certification of Spatial Robustness. - Anian Ruoss; Maximilian Baader; Mislav Balunovic; Martin T. Vechev (AAAI, 2021)

Robustness Certification for Point Cloud Models. - Tobias Lorenz 002; Anian Ruoss; Mislav Balunovic; Gagandeep Singh 001; Martin T. Vechev (ICCV, 2021)

Latent Space Smoothing for Individually Fair Representations. - Momchil Peychev; Anian Ruoss; Mislav Balunovic; Maximilian Baader; Martin T. Vechev (ECCV (13), 2022)

Fair Normalizing Flows. - Mislav Balunovic; Anian Ruoss; Martin T. Vechev (ICLR, 2022)

Neural Networks and the Chomsky Hierarchy. - Grégoire Delétang; Anian Ruoss; Jordi Grau-Moya; Tim Genewein; Li Kevin Wenliang; Elliot Catt; Marcus Hutter; Shane Legg; Pedro A. Ortega (CoRR, 2022)

Beyond Bayes-optimality: meta-learning what you know you don't know. - Jordi Grau-Moya; Grégoire Delétang; Markus Kunesch; Tim Genewein; Elliot Catt; Kevin Li; Anian Ruoss; Chris Cundy; Joel Veness; Jane X. Wang; Marcus Hutter; Christopher Summerfield; et al. (CoRR, 2022)

Randomized Positional Encodings Boost Length Generalization of Transformers. - Anian Ruoss; Grégoire Delétang; Tim Genewein; Jordi Grau-Moya; Róbert Csordás; Mehdi Bennani; Shane Legg; Joel Veness (ACL (2), 2023)

Neural Networks and the Chomsky Hierarchy. - Grégoire Delétang; Anian Ruoss; Jordi Grau-Moya; Tim Genewein; Li Kevin Wenliang; Elliot Catt; Chris Cundy; Marcus Hutter; Shane Legg; Joel Veness; Pedro A. Ortega (ICLR, 2023)

Memory-Based Meta-Learning on Non-Stationary Distributions. - Tim Genewein; Grégoire Delétang; Anian Ruoss; Li Kevin Wenliang; Elliot Catt; Vincent Dutordoir; Jordi Grau-Moya; Laurent Orseau; Marcus Hutter; Joel Veness (ICML, 2023)

Language Modeling Is Compression. - Grégoire Delétang; Anian Ruoss; Paul-Ambroise Duquenne; Elliot Catt; Tim Genewein; Christopher Mattern; Jordi Grau-Moya; Li Kevin Wenliang; Matthew Aitchison; Laurent Orseau; Marcus Hutter; Joel Veness (ICLR, 2024)

Learning Universal Predictors. - Jordi Grau-Moya; Tim Genewein; Marcus Hutter; Laurent Orseau; Grégoire Delétang; Elliot Catt; Anian Ruoss; Li Kevin Wenliang; Christopher Mattern; Matthew Aitchison; Joel Veness (ICML, 2024)

Distributional Bellman Operators over Mean Embeddings. - Li Kevin Wenliang; Grégoire Delétang; Matthew Aitchison; Marcus Hutter; Anian Ruoss; Arthur Gretton; Mark Rowland 001 (ICML, 2024)

Finding Increasingly Large Extremal Graphs with AlphaZero and Tabu Search. - Abbas Mehrabian; Ankit Anand; Hyunjik Kim; Nicolas Sonnerat; Matej Balog; Gheorghe Comanici; Tudor Berariu; Andrew Lee; Anian Ruoss; Anna Bulanova; Daniel Toyama; Sam Blackwell; et al. (IJCAI, 2024)

Amortized Planning with Large-Scale Transformers: A Case Study on Chess. - Anian Ruoss; Grégoire Delétang; Sourabh Medapati; Jordi Grau-Moya; Kevin Li; Elliot Catt; John Reid; Cannada Lewis; Joel Veness; Tim Genewein (NeurIPS, 2024)

Grandmaster-Level Chess Without Search. - Anian Ruoss; Grégoire Delétang; Sourabh Medapati; Jordi Grau-Moya; Li Kevin Wenliang; Elliot Catt; John Reid; Tim Genewein (CoRR, 2024)

Evaluating Frontier Models for Dangerous Capabilities. - Mary Phuong; Matthew Aitchison; Elliot Catt; Sarah Cogan; Alexandre Kaskasoli; Victoria Krakovna; David Lindner; Matthew Rahtz; Yannis Assael; Sarah Hodkinson; Heidi Howard; Tom Lieberum; et al. (CoRR, 2024)

Compression via Pre-trained Transformers: A Study on Byte-Level Multimodal Data. - David Heurtel-Depeiges; Anian Ruoss; Joel Veness; Tim Genewein (CoRR, 2024)

LMAct: A Benchmark for In-Context Imitation Learning with Long Multimodal Demonstrations. - Anian Ruoss; Fabio Pardo; Harris Chan; Bonnie Li; Volodymyr Mnih; Tim Genewein (CoRR, 2024)

Mastering Board Games by External and Internal Planning with Language Models. - John Schultz; Jakub Adámek; Matej Jusup; Marc Lanctot; Michael Kaisers; Sarah Perrin; Daniel Hennes; Jeremy Shar; Cannada Lewis; Anian Ruoss; Tom Zahavy; Petar Velickovic; et al. (CoRR, 2024)

Why is prompting hard? Understanding prompts on binary sequence predictors. - Li Kevin Wenliang; Anian Ruoss; Jordi Grau-Moya; Marcus Hutter; Tim Genewein (CoRR, 2025)

Understanding Prompt Tuning and In-Context Learning via Meta-Learning. - Tim Genewein; Li Kevin Wenliang; Jordi Grau-Moya; Anian Ruoss; Laurent Orseau; Marcus Hutter (CoRR, 2025)