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2020 – today
- 2024
[j1]Avi Singh, John D. Co-Reyes, Rishabh Agarwal, Ankesh Anand, Piyush Patil, Xavier Garcia, Peter J. Liu, James Harrison, Jaehoon Lee, Kelvin Xu, Aaron T. Parisi, Abhishek Kumar, Alexander A. Alemi, Alex Rizkowsky, Azade Nova, Ben Adlam, Bernd Bohnet, Gamaleldin Fathy Elsayed, Hanie Sedghi, Igor Mordatch, Isabelle Simpson, Izzeddin Gur, Jasper Snoek, Jeffrey Pennington, Jiri Hron, Kathleen Kenealy, Kevin Swersky, Kshiteej Mahajan, Laura Culp, Lechao Xiao, Maxwell L. Bileschi, Noah Constant, Roman Novak, Rosanne Liu, Tris Warkentin, Yundi Qian, Yamini Bansal, Ethan Dyer, Behnam Neyshabur, Jascha Sohl-Dickstein, Noah Fiedel:
Beyond Human Data: Scaling Self-Training for Problem-Solving with Language Models. Trans. Mach. Learn. Res. 2024 (2024)- [i12]Machel Reid, Nikolay Savinov, Denis Teplyashin, Dmitry Lepikhin, Timothy P. Lillicrap, Jean-Baptiste Alayrac, Radu Soricut, Angeliki Lazaridou, Orhan Firat, Julian Schrittwieser, Ioannis Antonoglou, Rohan Anil, Sebastian Borgeaud, Andrew M. Dai, Katie Millican, Ethan Dyer, Mia Glaese, Thibault Sottiaux, Benjamin Lee, Fabio Viola, Malcolm Reynolds, Yuanzhong Xu, James Molloy, Jilin Chen, Michael Isard, Paul Barham, Tom Hennigan, Ross McIlroy, Melvin Johnson, Johan Schalkwyk, Eli Collins, Eliza Rutherford, Erica Moreira, Kareem Ayoub, Megha Goel, Clemens Meyer, Gregory Thornton, Zhen Yang, Henryk Michalewski, Zaheer Abbas, Nathan Schucher, Ankesh Anand, Richard Ives, James Keeling, Karel Lenc, Salem Haykal, Siamak Shakeri, Pranav Shyam, Aakanksha Chowdhery, Roman Ring, Stephen Spencer, Eren Sezener, et al.:
Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context. CoRR abs/2403.05530 (2024) - [i11]Rishabh Agarwal, Avi Singh, Lei M. Zhang, Bernd Bohnet, Stephanie Chan, Ankesh Anand, Zaheer Abbas, Azade Nova, John D. Co-Reyes, Eric Chu, Feryal M. P. Behbahani, Aleksandra Faust, Hugo Larochelle:
Many-Shot In-Context Learning. CoRR abs/2404.11018 (2024) - 2023
- [c10]Jacob C. Walker, Eszter Vértes, Yazhe Li, Gabriel Dulac-Arnold, Ankesh Anand, Theophane Weber, Jessica B. Hamrick:
Investigating the Role of Model-Based Learning in Exploration and Transfer. ICML 2023: 35368-35383 - [i10]Jacob C. Walker, Eszter Vértes, Yazhe Li, Gabriel Dulac-Arnold, Ankesh Anand, Théophane Weber, Jessica B. Hamrick:
Investigating the role of model-based learning in exploration and transfer. CoRR abs/2302.04009 (2023) - [i9]Avi Singh, John D. Co-Reyes, Rishabh Agarwal, Ankesh Anand, Piyush Patil, Xavier Garcia, Peter J. Liu, James Harrison, Jaehoon Lee, Kelvin Xu, Aaron Parisi, Abhishek Kumar, Alex Alemi, Alex Rizkowsky, Azade Nova, Ben Adlam, Bernd Bohnet, Gamaleldin F. Elsayed, Hanie Sedghi, Igor Mordatch, Isabelle Simpson, Izzeddin Gur, Jasper Snoek, Jeffrey Pennington, Jiri Hron, Kathleen Kenealy, Kevin Swersky, Kshiteej Mahajan, Laura Culp, Lechao Xiao, Maxwell L. Bileschi, Noah Constant, Roman Novak, Rosanne Liu, Tris Warkentin, Yundi Qian, Yamini Bansal, Ethan Dyer, Behnam Neyshabur, Jascha Sohl-Dickstein, Noah Fiedel:
Beyond Human Data: Scaling Self-Training for Problem-Solving with Language Models. CoRR abs/2312.06585 (2023) - 2022
- [c9]Ankesh Anand, Jacob C. Walker, Yazhe Li, Eszter Vértes, Julian Schrittwieser, Sherjil Ozair, Theophane Weber, Jessica B. Hamrick:
Procedural generalization by planning with self-supervised world models. ICLR 2022 - 2021
- [c8]Max Schwarzer, Ankesh Anand, Rishab Goel, R. Devon Hjelm, Aaron C. Courville, Philip Bachman:
Data-Efficient Reinforcement Learning with Self-Predictive Representations. ICLR 2021 - [c7]Max Schwarzer, Nitarshan Rajkumar, Michael Noukhovitch, Ankesh Anand, Laurent Charlin, R. Devon Hjelm, Philip Bachman, Aaron C. Courville:
Pretraining Representations for Data-Efficient Reinforcement Learning. NeurIPS 2021: 12686-12699 - [i8]Max Schwarzer, Nitarshan Rajkumar, Michael Noukhovitch, Ankesh Anand, Laurent Charlin, R. Devon Hjelm, Philip Bachman, Aaron C. Courville:
Pretraining Representations for Data-Efficient Reinforcement Learning. CoRR abs/2106.04799 (2021) - [i7]Ankesh Anand, Jacob C. Walker, Yazhe Li, Eszter Vértes, Julian Schrittwieser, Sherjil Ozair, Théophane Weber, Jessica B. Hamrick:
Procedural Generalization by Planning with Self-Supervised World Models. CoRR abs/2111.01587 (2021) - 2020
- [i6]Max Schwarzer, Ankesh Anand, Rishab Goel, R. Devon Hjelm, Aaron C. Courville, Philip Bachman:
Data-Efficient Reinforcement Learning with Momentum Predictive Representations. CoRR abs/2007.05929 (2020)
2010 – 2019
- 2019
- [c6]Ankesh Anand, Evan Racah, Sherjil Ozair, Yoshua Bengio, Marc-Alexandre Côté, R. Devon Hjelm:
Unsupervised State Representation Learning in Atari. NeurIPS 2019: 8766-8779 - [i5]Ankesh Anand, Evan Racah, Sherjil Ozair, Yoshua Bengio, Marc-Alexandre Côté, R. Devon Hjelm:
Unsupervised State Representation Learning in Atari. CoRR abs/1906.08226 (2019) - 2018
- [c5]Ankesh Anand, Kshitij Gorde, Joel Ruben Antony Moniz, Noseong Park, Tanmoy Chakraborty
, Bei-Tseng Chu:
Phishing URL Detection with Oversampling based on Text Generative Adversarial Networks. IEEE BigData 2018: 1168-1177 - [c4]Simon Brodeur, Ethan Perez, Ankesh Anand, Florian Golemo, Luca Celotti, Florian Strub, Jean Rouat, Hugo Larochelle, Aaron C. Courville:
HoME: a Household Multimodal Environment. ICLR (Workshop) 2018 - [c3]Noseong Park, Ankesh Anand, Joel Ruben Antony Moniz, Kookjin Lee, Jaegul Choo, David Keetae Park, Tanmoy Chakraborty, Hongkyu Park, Youngmin Kim:
MMGAN: Manifold-Matching Generative Adversarial Networks. ICPR 2018: 1343-1348 - [i4]Ankesh Anand, Eugene Belilovsky, Kyle Kastner, Hugo Larochelle, Aaron C. Courville:
Blindfold Baselines for Embodied QA. CoRR abs/1811.05013 (2018) - 2017
- [c2]Ankesh Anand, Tanmoy Chakraborty, Noseong Park:
We Used Neural Networks to Detect Clickbaits: You Won't Believe What Happened Next! ECIR 2017: 541-547 - [c1]Ankesh Anand, Tanmoy Chakraborty, Amitava Das:
FairScholar: Balancing Relevance and Diversity for Scientific Paper Recommendation. ECIR 2017: 753-757 - [i3]Noseong Park, Ankesh Anand, Joel Ruben Antony Moniz, Kookjin Lee, Tanmoy Chakraborty, Jaegul Choo, Hongkyu Park, Youngmin Kim:
MMGAN: Manifold Matching Generative Adversarial Network for Generating Images. CoRR abs/1707.08273 (2017) - [i2]Simon Brodeur, Ethan Perez, Ankesh Anand, Florian Golemo, Luca Celotti, Florian Strub, Jean Rouat, Hugo Larochelle, Aaron C. Courville:
HoME: a Household Multimodal Environment. CoRR abs/1711.11017 (2017) - 2016
- [i1]Ankesh Anand, Tanmoy Chakraborty, Noseong Park:
We used Neural Networks to Detect Clickbaits: You won't believe what happened Next! CoRR abs/1612.01340 (2016)
Coauthor Index
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last updated on 2024-08-25 19:11 CEST by the dblp team
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