Kanervisto, Anssi

11 publications

ICLR 2025 Zero-Shot Whole-Body Humanoid Control via Behavioral Foundation Models Andrea Tirinzoni, Ahmed Touati, Jesse Farebrother, Mateusz Guzek, Anssi Kanervisto, Yingchen Xu, Alessandro Lazaric, Matteo Pirotta
ICMLW 2024 BEDD: The MineRL BASALT Evaluation and Demonstrations Dataset for Training and Benchmarking Agents That Solve Fuzzy Tasks Stephanie Milani, Anssi Kanervisto, Karolis Jucys, Sander V Schulhoff, Brandon Houghton, Rohin Shah
NeurIPS 2024 Diffusion for World Modeling: Visual Details Matter in Atari Eloi Alonso, Adam Jelley, Vincent Micheli, Anssi Kanervisto, Amos Storkey, Tim Pearce, François Fleuret
NeurIPSW 2024 Zero-Shot Whole-Body Humanoid Control via Behavioral Foundation Models Andrea Tirinzoni, Ahmed Touati, Jesse Farebrother, Mateusz Guzek, Anssi Kanervisto, Yingchen Xu, Alessandro Lazaric, Matteo Pirotta
NeurIPS 2023 BEDD: The MineRL BASALT Evaluation and Demonstrations Dataset for Training and Benchmarking Agents That Solve Fuzzy Tasks Stephanie Milani, Anssi Kanervisto, Karolis Ramanauskas, Sander Schulhoff, Brandon Houghton, Rohin Shah
ICLR 2023 Imitating Human Behaviour with Diffusion Models Tim Pearce, Tabish Rashid, Anssi Kanervisto, Dave Bignell, Mingfei Sun, Raluca Georgescu, Sergio Valcarcel Macua, Shan Zheng Tan, Ida Momennejad, Katja Hofmann, Sam Devlin
NeurIPSW 2022 Imitating Human Behaviour with Diffusion Models Tim Pearce, Tabish Rashid, Anssi Kanervisto, David Bignell, Mingfei Sun, Raluca Georgescu, Sergio Valcarcel Macua, Shan Zheng Tan, Ida Momennejad, Katja Hofmann, Sam Devlin
NeurIPSW 2021 General Characterization of Agents by States They Visit Anssi Kanervisto, Tomi Kinnunen, Ville Hautamaki
CVPRW 2021 Multi-Task Learning with Attention for End-to-End Autonomous Driving Keishi Ishihara, Anssi Kanervisto, Jun Miura, Ville Hautamäki
MLOSS 2021 Stable-Baselines3: Reliable Reinforcement Learning Implementations Antonin Raffin, Ashley Hill, Adam Gleave, Anssi Kanervisto, Maximilian Ernestus, Noah Dormann
ICML 2017 Image-to-Markup Generation with Coarse-to-Fine Attention Yuntian Deng, Anssi Kanervisto, Jeffrey Ling, Alexander M. Rush