Ruoss, Anian

18 publications

ICML 2025 Compression via Pre-Trained Transformers: A Study on Byte-Level Multimodal Data David Heurtel-Depeiges, Anian Ruoss, Joel Veness, Tim Genewein

ICML 2025 LMAct: A Benchmark for In-Context Imitation Learning with Long Multimodal Demonstrations Anian Ruoss, Fabio Pardo, Harris Chan, Bonnie Li, Volodymyr Mnih, Tim Genewein

ICLRW 2025 LMAct: A Benchmark for In-Context Imitation Learning with Long Multimodal Demonstrations Anian Ruoss, Fabio Pardo, Harris Chan, Bonnie Li, Volodymyr Mnih, Tim Genewein

ICML 2025 Mastering Board Games by External and Internal Planning with Language Models John Schultz, Jakub Adamek, Matej Jusup, Marc Lanctot, Michael Kaisers, Sarah Perrin, Daniel Hennes, Jeremy Shar, Cannada A. Lewis, Anian Ruoss, Tom Zahavy, Petar Veličković, Laurel Prince, Satinder Singh, Eric Malmi, Nenad Tomasev

NeurIPS 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

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

ICML 2024 Distributional Bellman Operators over Mean Embeddings Li Kevin Wenliang, Gregoire Deletang, Matthew Aitchison, Marcus Hutter, Anian Ruoss, Arthur Gretton, Mark Rowland

IJCAI 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, Bernardino Romera-Paredes, Petar Velickovic, Laurent Orseau, Joonkyung Lee, Anurag Murty Naredla, Doina Precup, Adam Zsolt Wagner

ICLR 2024 Language Modeling Is Compression Gregoire Deletang, 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

ICML 2024 Learning Universal Predictors Jordi Grau-Moya, Tim Genewein, Marcus Hutter, Laurent Orseau, Gregoire Deletang, Elliot Catt, Anian Ruoss, Li Kevin Wenliang, Christopher Mattern, Matthew Aitchison, Joel Veness

NeurIPSW 2023 Finding Increasingly Large Extremal Graphs with AlphaZero and Tabu Search Abbas Mehrabian, Ankit Anand, Hyunjik Kim, Nicolas Sonnerat, Tudor Berariu, Matej Balog, Gheorghe Comanici, Andrew Lee, Anian Ruoss, Anna Bulanova, Daniel Toyama, Sam Blackwell, Bernardino Romera Paredes, Laurent Orseau, Petar Veličković, Anurag Murty Naredla, Joonkyung Lee, Adam Zsolt Wagner, Doina Precup

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

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

ICLR 2022 Fair Normalizing Flows Mislav Balunovic, Anian Ruoss, Martin Vechev

ECCV 2022 Latent Space Smoothing for Individually Fair Representations Momchil Peychev, Anian Ruoss, Mislav Balunović, Maximilian Baader, Martin Vechev

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

ICCV 2021 Robustness Certification for Point Cloud Models Tobias Lorenz, Anian Ruoss, Mislav Balunović, Gagandeep Singh, Martin Vechev

NeurIPS 2020 Learning Certified Individually Fair Representations Anian Ruoss, Mislav Balunovic, Marc Fischer, Martin Vechev