Rank Distance Aggregation as a Fixed Classifier Combining Rule for Text Categorization. - Liviu Petrisor Dinu; Andrei A. Rusu (CICLing, 2010)

HyperNEAT for Locomotion Control in Modular Robots. - Evert Haasdijk; Andrei A. Rusu; A. E. Eiben (ICES, 2010)

Human-level control through deep reinforcement learning. - Volodymyr Mnih; Koray Kavukcuoglu; David Silver; Andrei A. Rusu; Joel Veness; Marc G. Bellemare; Alex Graves; Martin A. Riedmiller; Andreas Fidjeland; Georg Ostrovski; Stig Petersen; Charles Beattie; et al. (Nat., 2015)

Overcoming catastrophic forgetting in neural networks. - James Kirkpatrick; Razvan Pascanu; Neil C. Rabinowitz; Joel Veness; Guillaume Desjardins; Andrei A. Rusu; Kieran Milan; John Quan; Tiago Ramalho; Agnieszka Grabska-Barwinska; Demis Hassabis; Claudia Clopath; et al. (CoRR, 2016)

Policy Distillation. - Andrei A. Rusu; Sergio Gomez Colmenarejo; Çaglar Gülçehre; Guillaume Desjardins; James Kirkpatrick; Razvan Pascanu; Volodymyr Mnih; Koray Kavukcuoglu; Raia Hadsell (ICLR (Poster), 2016)

Progressive Neural Networks. - Andrei A. Rusu; Neil C. Rabinowitz; Guillaume Desjardins; Hubert Soyer; James Kirkpatrick; Koray Kavukcuoglu; Razvan Pascanu; Raia Hadsell (CoRR, 2016)

Sim-to-Real Robot Learning from Pixels with Progressive Nets. - Andrei A. Rusu; Matej Vecerík; Thomas Rothörl; Nicolas Heess; Razvan Pascanu; Raia Hadsell (CoRL, 2017)

DARLA: Improving Zero-Shot Transfer in Reinforcement Learning. - Irina Higgins; Arka Pal; Andrei A. Rusu; Loïc Matthey; Christopher P. Burgess; Alexander Pritzel; Matthew M. Botvinick; Charles Blundell; Alexander Lerchner (ICML, 2017)

PathNet: Evolution Channels Gradient Descent in Super Neural Networks. - Chrisantha Fernando; Dylan Banarse; Charles Blundell; Yori Zwols; David Ha; Andrei A. Rusu; Alexander Pritzel; Daan Wierstra (CoRR, 2017)

Meta-learning by the baldwin effect. - Chrisantha Fernando; Jakub Sygnowski; Simon Osindero; Jane Wang 001; Tom Schaul; Denis Teplyashin; Pablo Sprechmann; Alexander Pritzel; Andrei A. Rusu (GECCO (Companion), 2018)

Reinforcement and Imitation Learning for Diverse Visuomotor Skills. - Yuke Zhu; Ziyu Wang 001; Josh Merel; Andrei A. Rusu; Tom Erez; Serkan Cabi; Saran Tunyasuvunakool; János Kramár; Raia Hadsell; Nando de Freitas; Nicolas Heess (Robotics: Science and Systems, 2018)

Meta-Learning with Latent Embedding Optimization. - Andrei A. Rusu; Dushyant Rao; Jakub Sygnowski; Oriol Vinyals; Razvan Pascanu; Simon Osindero; Raia Hadsell (ICLR (Poster), 2019)

Continual Unsupervised Representation Learning. - Dushyant Rao; Francesco Visin; Andrei A. Rusu; Razvan Pascanu; Yee Whye Teh; Raia Hadsell (NeurIPS, 2019)

Task Agnostic Continual Learning via Meta Learning. - Xu He; Jakub Sygnowski; Alexandre Galashov; Andrei A. Rusu; Yee Whye Teh; Razvan Pascanu (CoRR, 2019)

Meta-Learning with Warped Gradient Descent. - Sebastian Flennerhag; Andrei A. Rusu; Razvan Pascanu; Hujun Yin; Raia Hadsell (CoRR, 2019)

Meta-Learning with Warped Gradient Descent. - Sebastian Flennerhag; Andrei A. Rusu; Razvan Pascanu; Francesco Visin; Hujun Yin; Raia Hadsell (ICLR, 2020)

Probing Transfer in Deep Reinforcement Learning without Task Engineering. - Andrei Alex Rusu; Sebastian Flennerhag; Dushyant Rao; Razvan Pascanu; Raia Hadsell (CoLLAs, 2022)

Hindering Adversarial Attacks with Implicit Neural Representations. - Andrei A. Rusu; Dan Andrei Calian; Sven Gowal; Raia Hadsell (ICML, 2022)

NEVIS'22: A Stream of 100 Tasks Sampled from 30 Years of Computer Vision Research. - Jörg Bornschein; Alexandre Galashov; Ross Hemsley; Amal Rannen-Triki; Yutian Chen 001; Arslan Chaudhry; Xu Owen He; Arthur Douillard; Massimo Caccia; Qixuang Feng; Jiajun Shen; Sylvestre-Alvise Rebuffi; et al. (CoRR, 2022)

Prospective Learning: Principled Extrapolation to the Future. - Ashwin De Silva; Rahul Ramesh; Lyle H. Ungar; Marshall G. Hussain Shuler; Noah J. Cowan; Michael L. Platt; Chen Li; Leyla Isik; Seung-Eon Roh; Adam S. Charles; Archana Venkataraman; Brian Caffo; et al. (CoLLAs, 2023)

DiLoCo: Distributed Low-Communication Training of Language Models. - Arthur Douillard; Qixuang Feng; Andrei A. Rusu; Rachita Chhaparia; Yani Donchev; Adhiguna Kuncoro; Marc'Aurelio Ranzato; Arthur Szlam; Jiajun Shen (CoRR, 2023)

Nevis'22: A Stream of 100 Tasks Sampled from 30 Years of Computer Vision Research. - Jörg Bornschein; Alexandre Galashov; Ross Hemsley; Amal Rannen-Triki; Yutian Chen 001; Arslan Chaudhry; Xu Owen He; Arthur Douillard; Massimo Caccia; Qixuan Feng; Jiajun Shen; Sylvestre-Alvise Rebuffi; et al. (J. Mach. Learn. Res., 2023)

Asynchronous Local-SGD Training for Language Modeling. - Bo Liu; Rachita Chhaparia; Arthur Douillard; Satyen Kale; Andrei A. Rusu; Jiajun Shen; Arthur Szlam; Marc'Aurelio Ranzato (CoRR, 2024)

DiPaCo: Distributed Path Composition. - Arthur Douillard; Qixuan Feng; Andrei A. Rusu; Adhiguna Kuncoro; Yani Donchev; Rachita Chhaparia; Ionel Gog; Marc'Aurelio Ranzato; Jiajun Shen; Arthur Szlam (CoRR, 2024)