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Pierre H. Richemond
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2020 – today
- 2024
- [c8]Daniele Calandriello, Zhaohan Daniel Guo, Rémi Munos, Mark Rowland, Yunhao Tang, Bernardo Ávila Pires, Pierre Harvey Richemond, Charline Le Lan, Michal Valko, Tianqi Liu, Rishabh Joshi, Zeyu Zheng, Bilal Piot:
Human Alignment of Large Language Models through Online Preference Optimisation. ICML 2024 - [c7]Yunhao Tang, Zhaohan Daniel Guo, Zeyu Zheng, Daniele Calandriello, Rémi Munos, Mark Rowland, Pierre Harvey Richemond, Michal Valko, Bernardo Ávila Pires, Bilal Piot:
Generalized Preference Optimization: A Unified Approach to Offline Alignment. ICML 2024 - [i19]Yunhao Tang, Zhaohan Daniel Guo, Zeyu Zheng, Daniele Calandriello, Rémi Munos, Mark Rowland, Pierre Harvey Richemond, Michal Valko, Bernardo Ávila Pires, Bilal Piot:
Generalized Preference Optimization: A Unified Approach to Offline Alignment. CoRR abs/2402.05749 (2024) - [i18]Daniele Calandriello, Daniel Guo, Rémi Munos, Mark Rowland, Yunhao Tang, Bernardo Ávila Pires, Pierre Harvey Richemond, Charline Le Lan, Michal Valko, Tianqi Liu, Rishabh Joshi, Zeyu Zheng, Bilal Piot:
Human Alignment of Large Language Models through Online Preference Optimisation. CoRR abs/2403.08635 (2024) - [i17]SIMA Team, Maria Abi Raad, Arun Ahuja, Catarina Barros, Frederic Besse, Andrew Bolt, Adrian Bolton, Bethanie Brownfield, Gavin Buttimore, Max Cant, Sarah Chakera, Stephanie C. Y. Chan, Jeff Clune, Adrian Collister, Vikki Copeman, Alex Cullum, Ishita Dasgupta, Dario de Cesare, Julia Di Trapani, Yani Donchev, Emma Dunleavy, Martin Engelcke, Ryan Faulkner, Frankie Garcia, Charles Gbadamosi, Zhitao Gong, Lucy Gonzalez, Kshitij Gupta, Karol Gregor, Arne Olav Hallingstad, Tim Harley, Sam Haves, Felix Hill, Ed Hirst, Drew A. Hudson, Jony Hudson, Steph Hughes-Fitt, Danilo J. Rezende, Mimi Jasarevic, Laura Kampis, Nan Rosemary Ke, Thomas Keck, Junkyung Kim, Oscar Knagg, Kavya Kopparapu, Andrew K. Lampinen, Shane Legg, Alexander Lerchner, Marjorie Limont, Yulan Liu, Maria Loks-Thompson, Joseph Marino, Kathryn Martin Cussons, Loic Matthey, Siobhan Mcloughlin, Piermaria Mendolicchio, Hamza Merzic, Anna Mitenkova, Alexandre Moufarek, Valéria Oliveira, Yanko Gitahy Oliveira, Hannah Openshaw, Renke Pan, Aneesh Pappu, Alex Platonov, Ollie Purkiss, David P. Reichert, John Reid, Pierre Harvey Richemond, Tyson Roberts, Giles Ruscoe, Jaume Sanchez Elias, Tasha Sandars, Daniel P. Sawyer, Tim Scholtes, Guy Simmons, Daniel Slater, Hubert Soyer, Heiko Strathmann, Peter Stys, Allison C. Tam, Denis Teplyashin, Tayfun Terzi, Davide Vercelli, Bojan Vujatovic, Marcus Wainwright, Jane X. Wang, Zhengdong Wang, Daan Wierstra, Duncan Williams, Nathaniel Wong, Sarah York, Nick Young:
Scaling Instructable Agents Across Many Simulated Worlds. CoRR abs/2404.10179 (2024) - [i16]Pierre Harvey Richemond, Yunhao Tang, Daniel Guo, Daniele Calandriello, Mohammad Gheshlaghi Azar, Rafael Rafailov, Bernardo Ávila Pires, Eugene Tarassov, Lucas Spangher, Will Ellsworth, Aliaksei Severyn, Jonathan Mallinson, Lior Shani, Gil Shamir, Rishabh Joshi, Tianqi Liu, Rémi Munos, Bilal Piot:
Offline Regularised Reinforcement Learning for Large Language Models Alignment. CoRR abs/2405.19107 (2024) - 2023
- [c6]Matko Bosnjak, Pierre Harvey Richemond, Nenad Tomasev, Florian Strub, Jacob C. Walker, Felix Hill, Lars Holger Buesing, Razvan Pascanu, Charles Blundell, Jovana Mitrovic:
SemPPL: Predicting Pseudo-Labels for Better Contrastive Representations. ICLR 2023 - [c5]Pierre Harvey Richemond, Allison C. Tam, Yunhao Tang, Florian Strub, Bilal Piot, Felix Hill:
The Edge of Orthogonality: A Simple View of What Makes BYOL Tick. ICML 2023: 29063-29081 - [c4]Yunhao Tang, Zhaohan Daniel Guo, Pierre Harvey Richemond, Bernardo Ávila Pires, Yash Chandak, Rémi Munos, Mark Rowland, Mohammad Gheshlaghi Azar, Charline Le Lan, Clare Lyle, András György, Shantanu Thakoor, Will Dabney, Bilal Piot, Daniele Calandriello, Michal Valko:
Understanding Self-Predictive Learning for Reinforcement Learning. ICML 2023: 33632-33656 - [i15]Matko Bosnjak, Pierre H. Richemond, Nenad Tomasev, Florian Strub, Jacob C. Walker, Felix Hill, Lars Holger Buesing, Razvan Pascanu, Charles Blundell, Jovana Mitrovic:
SemPPL: Predicting pseudo-labels for better contrastive representations. CoRR abs/2301.05158 (2023) - [i14]Pierre H. Richemond, Allison C. Tam, Yunhao Tang, Florian Strub, Bilal Piot, Felix Hill:
The Edge of Orthogonality: A Simple View of What Makes BYOL Tick. CoRR abs/2302.04817 (2023) - 2022
- [c3]Stephanie C. Y. Chan, Andrew Kyle Lampinen, Pierre Harvey Richemond, Felix Hill:
Zipfian Environments for Reinforcement Learning. CoLLAs 2022: 406-429 - [c2]Stephanie C. Y. Chan, Adam Santoro, Andrew K. Lampinen, Jane X. Wang, Aaditya K. Singh, Pierre H. Richemond, James L. McClelland, Felix Hill:
Data Distributional Properties Drive Emergent In-Context Learning in Transformers. NeurIPS 2022 - [i13]Stephanie C. Y. Chan, Andrew K. Lampinen, Pierre H. Richemond, Felix Hill:
Zipfian environments for Reinforcement Learning. CoRR abs/2203.08222 (2022) - [i12]Stephanie C. Y. Chan, Adam Santoro, Andrew K. Lampinen, Jane X. Wang, Aaditya K. Singh, Pierre H. Richemond, Jay McClelland, Felix Hill:
Data Distributional Properties Drive Emergent In-Context Learning in Transformers. CoRR abs/2205.05055 (2022) - [i11]Pierre H. Richemond, Sander Dieleman, Arnaud Doucet:
Categorical SDEs with Simplex Diffusion. CoRR abs/2210.14784 (2022) - [i10]Sander Dieleman, Laurent Sartran, Arman Roshannai, Nikolay Savinov, Yaroslav Ganin, Pierre H. Richemond, Arnaud Doucet, Robin Strudel, Chris Dyer, Conor Durkan, Curtis Hawthorne, Rémi Leblond, Will Grathwohl, Jonas Adler:
Continuous diffusion for categorical data. CoRR abs/2211.15089 (2022) - [i9]Yunhao Tang, Zhaohan Daniel Guo, Pierre Harvey Richemond, Bernardo Ávila Pires, Yash Chandak, Rémi Munos, Mark Rowland, Mohammad Gheshlaghi Azar, Charline Le Lan, Clare Lyle, András György, Shantanu Thakoor, Will Dabney, Bilal Piot, Daniele Calandriello, Michal Valko:
Understanding Self-Predictive Learning for Reinforcement Learning. CoRR abs/2212.03319 (2022) - 2020
- [c1]Jean-Bastien Grill, Florian Strub, Florent Altché, Corentin Tallec, Pierre H. Richemond, Elena Buchatskaya, Carl Doersch, Bernardo Ávila Pires, Zhaohan Guo, Mohammad Gheshlaghi Azar, Bilal Piot, Koray Kavukcuoglu, Rémi Munos, Michal Valko:
Bootstrap Your Own Latent - A New Approach to Self-Supervised Learning. NeurIPS 2020 - [i8]Jean-Bastien Grill, Florian Strub, Florent Altché, Corentin Tallec, Pierre H. Richemond, Elena Buchatskaya, Carl Doersch, Bernardo Ávila Pires, Zhaohan Daniel Guo, Mohammad Gheshlaghi Azar, Bilal Piot, Koray Kavukcuoglu, Rémi Munos, Michal Valko:
Bootstrap Your Own Latent: A New Approach to Self-Supervised Learning. CoRR abs/2006.07733 (2020) - [i7]Pierre H. Richemond, Jean-Bastien Grill, Florent Altché, Corentin Tallec, Florian Strub, Andrew Brock, Samuel L. Smith, Soham De, Razvan Pascanu, Bilal Piot, Michal Valko:
BYOL works even without batch statistics. CoRR abs/2010.10241 (2020)
2010 – 2019
- 2019
- [i6]Pierre H. Richemond, Yike Guo:
Combining learning rate decay and weight decay with complexity gradient descent - Part I. CoRR abs/1902.02881 (2019) - [i5]Pierre H. Richemond, Yike Guo:
Static Activation Function Normalization. CoRR abs/1905.01369 (2019) - [i4]Pierre H. Richemond, Arinbjörn Kolbeinsson, Yike Guo:
Biologically inspired architectures for sample-efficient deep reinforcement learning. CoRR abs/1911.11285 (2019) - 2017
- [i3]Brendan Maginnis, Pierre H. Richemond:
Efficiently applying attention to sequential data with the Recurrent Discounted Attention unit. CoRR abs/1705.08480 (2017) - [i2]Pierre H. Richemond, Brendan Maginnis:
On Wasserstein Reinforcement Learning and the Fokker-Planck equation. CoRR abs/1712.07185 (2017) - [i1]Pierre H. Richemond, Brendan Maginnis:
A short variational proof of equivalence between policy gradients and soft Q learning. CoRR abs/1712.08650 (2017)
Coauthor Index
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