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ORCIDAndrei A. Rusu
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2020 – today
- 2024
[i17]Bo Liu, Rachita Chhaparia, Arthur Douillard, Satyen Kale, Andrei A. Rusu, Jiajun Shen, Arthur Szlam, Marc'Aurelio Ranzato:
Asynchronous Local-SGD Training for Language Modeling. CoRR abs/2401.09135 (2024)- [i16]Arthur Douillard, Qixuan Feng, Andrei A. Rusu, Adhiguna Kuncoro, Yani Donchev, Rachita Chhaparia, Ionel Gog, Marc'Aurelio Ranzato, Jiajun Shen, Arthur Szlam:
DiPaCo: Distributed Path Composition. CoRR abs/2403.10616 (2024) - 2023
- [j2]Jörg Bornschein, Alexandre Galashov, Ross Hemsley, Amal Rannen-Triki, Yutian Chen, Arslan Chaudhry, Xu Owen He, Arthur Douillard, Massimo Caccia, Qixuan Feng, Jiajun Shen, Sylvestre-Alvise Rebuffi, Kitty Stacpoole, Diego de Las Casas, Will Hawkins, Angeliki Lazaridou, Yee Whye Teh, Andrei A. Rusu, Razvan Pascanu, Marc'Aurelio Ranzato:
Nevis'22: A Stream of 100 Tasks Sampled from 30 Years of Computer Vision Research. J. Mach. Learn. Res. 24: 308:1-308:77 (2023) - [c14]Ashwin De Silva, Rahul Ramesh, Lyle H. Ungar, Marshall G. Hussain Shuler, Noah J. Cowan, Michael Platt, Chen Li, Leyla Isik, Seung-Eon Roh, Adam Charles, Archana Venkataraman, Brian Caffo, Javier J. How, Justus M. Kebschull, John W. Krakauer, Maxim Bichuch, Kaleab Alemayehu Kinfu, Eva Yezerets, Dinesh Jayaraman
, Jong M. Shin, Soledad Villar, Ian Phillips, Carey E. Priebe, Thomas Hartung, Michael I. Miller, Jayanta Dey, Ningyuan Huang, Eric Eaton, Ralph Etienne-Cummings, Elizabeth L. Ogburn, Randal C. Burns, Onyema Osuagwu, Brett Mensh, Alysson R. Muotri, Julia Brown, Chris White, Weiwei Yang, Andrei A. Rusu, Timothy D. Verstynen, Konrad P. Kording, Pratik Chaudhari, Joshua T. Vogelstein:
Prospective Learning: Principled Extrapolation to the Future. CoLLAs 2023: 347-357 - [i15]Arthur Douillard, Qixuang Feng, Andrei A. Rusu, Rachita Chhaparia, Yani Donchev, Adhiguna Kuncoro, Marc'Aurelio Ranzato, Arthur Szlam, Jiajun Shen:
DiLoCo: Distributed Low-Communication Training of Language Models. CoRR abs/2311.08105 (2023) - 2022
- [c13]Andrei Alex Rusu, Sebastian Flennerhag, Dushyant Rao, Razvan Pascanu, Raia Hadsell:
Probing Transfer in Deep Reinforcement Learning without Task Engineering. CoLLAs 2022: 1231-1254 - [c12]Andrei A. Rusu, Dan Andrei Calian, Sven Gowal, Raia Hadsell:
Hindering Adversarial Attacks with Implicit Neural Representations. ICML 2022: 18910-18934 - [i14]Andrei A. Rusu, Sebastian Flennerhag, Dushyant Rao, Razvan Pascanu, Raia Hadsell:
Probing Transfer in Deep Reinforcement Learning without Task Engineering. CoRR abs/2210.12448 (2022) - [i13]Andrei A. Rusu, Dan A. Calian, Sven Gowal, Raia Hadsell:
Hindering Adversarial Attacks with Implicit Neural Representations. CoRR abs/2210.13982 (2022) - [i12]Jörg Bornschein, Alexandre Galashov, Ross Hemsley, Amal Rannen-Triki, Yutian Chen, Arslan Chaudhry, Xu Owen He, Arthur Douillard, Massimo Caccia, Qixuang Feng, Jiajun Shen, Sylvestre-Alvise Rebuffi, Kitty Stacpoole, Diego de Las Casas, Will Hawkins, Angeliki Lazaridou, Yee Whye Teh, Andrei A. Rusu, Razvan Pascanu, Marc'Aurelio Ranzato:
NEVIS'22: A Stream of 100 Tasks Sampled from 30 Years of Computer Vision Research. CoRR abs/2211.11747 (2022) - 2020
- [c11]Sebastian Flennerhag, Andrei A. Rusu, Razvan Pascanu, Francesco Visin, Hujun Yin, Raia Hadsell:
Meta-Learning with Warped Gradient Descent. ICLR 2020
2010 – 2019
- 2019
- [c10]Andrei A. Rusu, Dushyant Rao, Jakub Sygnowski, Oriol Vinyals, Razvan Pascanu, Simon Osindero, Raia Hadsell:
Meta-Learning with Latent Embedding Optimization. ICLR (Poster) 2019 - [c9]Dushyant Rao, Francesco Visin, Andrei A. Rusu, Razvan Pascanu, Yee Whye Teh, Raia Hadsell:
Continual Unsupervised Representation Learning. NeurIPS 2019: 7645-7655 - [i11]Xu He, Jakub Sygnowski, Alexandre Galashov, Andrei A. Rusu, Yee Whye Teh, Razvan Pascanu:
Task Agnostic Continual Learning via Meta Learning. CoRR abs/1906.05201 (2019) - [i10]Sebastian Flennerhag, Andrei A. Rusu, Razvan Pascanu, Hujun Yin, Raia Hadsell:
Meta-Learning with Warped Gradient Descent. CoRR abs/1909.00025 (2019) - [i9]Dushyant Rao, Francesco Visin, Andrei A. Rusu, Yee Whye Teh, Razvan Pascanu, Raia Hadsell:
Continual Unsupervised Representation Learning. CoRR abs/1910.14481 (2019) - 2018
- [c8]Chrisantha Fernando, Jakub Sygnowski, Simon Osindero, Jane Wang, Tom Schaul, Denis Teplyashin, Pablo Sprechmann, Alexander Pritzel, Andrei A. Rusu:
Meta-learning by the baldwin effect. GECCO (Companion) 2018: 109-110 - [c7]Chrisantha Fernando, Jakub Sygnowski, Simon Osindero, Jane Wang, Tom Schaul, Denis Teplyashin, Pablo Sprechmann, Alexander Pritzel, Andrei A. Rusu:
Meta-learning by the Baldwin effect. GECCO (Companion) 2018: 1313-1320 - [c6]Yuke Zhu, Ziyu Wang, Josh Merel, Andrei A. Rusu, Tom Erez, Serkan Cabi, Saran Tunyasuvunakool, János Kramár, Raia Hadsell, Nando de Freitas, Nicolas Heess:
Reinforcement and Imitation Learning for Diverse Visuomotor Skills. Robotics: Science and Systems 2018 - [i8]Yuke Zhu, Ziyu Wang, Josh Merel, Andrei A. Rusu, Tom Erez, Serkan Cabi, Saran Tunyasuvunakool, János Kramár, Raia Hadsell, Nando de Freitas, Nicolas Heess:
Reinforcement and Imitation Learning for Diverse Visuomotor Skills. CoRR abs/1802.09564 (2018) - [i7]Chrisantha Thomas Fernando, Jakub Sygnowski, Simon Osindero, Jane Wang, Tom Schaul, Denis Teplyashin, Pablo Sprechmann, Alexander Pritzel, Andrei A. Rusu:
Meta-Learning by the Baldwin Effect. CoRR abs/1806.07917 (2018) - [i6]Andrei A. Rusu, Dushyant Rao, Jakub Sygnowski, Oriol Vinyals, Razvan Pascanu, Simon Osindero, Raia Hadsell:
Meta-Learning with Latent Embedding Optimization. CoRR abs/1807.05960 (2018) - 2017
- [c5]Andrei A. Rusu, Matej Vecerík, Thomas Rothörl, Nicolas Heess, Razvan Pascanu, Raia Hadsell:
Sim-to-Real Robot Learning from Pixels with Progressive Nets. CoRL 2017: 262-270 - [c4]Irina Higgins, Arka Pal, Andrei A. Rusu, Loïc Matthey, Christopher P. Burgess, Alexander Pritzel, Matthew M. Botvinick, Charles Blundell, Alexander Lerchner:
DARLA: Improving Zero-Shot Transfer in Reinforcement Learning. ICML 2017: 1480-1490 - [i5]Chrisantha Fernando, Dylan Banarse, Charles Blundell, Yori Zwols, David Ha, Andrei A. Rusu, Alexander Pritzel, Daan Wierstra:
PathNet: Evolution Channels Gradient Descent in Super Neural Networks. CoRR abs/1701.08734 (2017) - [i4]Irina Higgins, Arka Pal, Andrei A. Rusu, Loïc Matthey, Christopher P. Burgess, Alexander Pritzel, Matthew M. Botvinick, Charles Blundell, Alexander Lerchner:
DARLA: Improving Zero-Shot Transfer in Reinforcement Learning. CoRR abs/1707.08475 (2017) - 2016
- [c3]Andrei A. Rusu, Sergio Gomez Colmenarejo, Çaglar Gülçehre, Guillaume Desjardins, James Kirkpatrick, Razvan Pascanu, Volodymyr Mnih, Koray Kavukcuoglu, Raia Hadsell:
Policy Distillation. ICLR (Poster) 2016 - [i3]Andrei A. Rusu, Neil C. Rabinowitz, Guillaume Desjardins, Hubert Soyer, James Kirkpatrick, Koray Kavukcuoglu, Razvan Pascanu, Raia Hadsell:
Progressive Neural Networks. CoRR abs/1606.04671 (2016) - [i2]Andrei A. Rusu, Matej Vecerík, Thomas Rothörl, Nicolas Heess, Razvan Pascanu, Raia Hadsell:
Sim-to-Real Robot Learning from Pixels with Progressive Nets. CoRR abs/1610.04286 (2016) - [i1]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, Dharshan Kumaran, Raia Hadsell:
Overcoming catastrophic forgetting in neural networks. CoRR abs/1612.00796 (2016) - 2015
- [j1]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, Amir Sadik, Ioannis Antonoglou, Helen King, Dharshan Kumaran, Daan Wierstra, Shane Legg, Demis Hassabis:
Human-level control through deep reinforcement learning. Nat. 518(7540): 529-533 (2015) - 2010
- [c2]Liviu Petrisor Dinu, Andrei A. Rusu:
Rank Distance Aggregation as a Fixed Classifier Combining Rule for Text Categorization. CICLing 2010: 638-647 - [c1]Evert Haasdijk, Andrei A. Rusu, A. E. Eiben:
HyperNEAT for Locomotion Control in Modular Robots. ICES 2010: 169-180
Coauthor Index
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