Ankesh Anand

PhD student, Mila, University of Montreal

Joined

October 2017

Names

Ankesh Anand

Emails

****@gmail.com (Confirmed)

****@umontreal.ca (Confirmed)

****@mila.quebec (Confirmed)

****@deepmind.com (Confirmed)

Personal Links

Homepage

Career & Education History

PhD student

Mila, University of Montreal (umontreal.ca)

2017 – Present

Advisors, Relations & Conflicts

PhD Advisor

Aaron Courville

2017 – Present

Expertise

Reinforcement Learning

Present

Representation Learning

Present

Self-Supervised Learning

Present

Publications

Many-Shot In-Context Learning
Rishabh Agarwal, Avi Singh, Lei M Zhang, Bernd Bohnet, Luis Rosias, Stephanie C.Y. Chan, Biao Zhang, Ankesh Anand, Zaheer Abbas, Azade Nova, John D Co-Reyes, Eric Chu, Feryal Behbahani, Aleksandra Faust, Hugo Larochelle
- LCFM 2024
- Readers: Everyone
Many-Shot In-Context Learning
Rishabh Agarwal, Avi Singh, Lei M Zhang, Bernd Bohnet, Luis Rosias, Stephanie C.Y. Chan, Biao Zhang, Ankesh Anand, Zaheer Abbas, Azade Nova, John D Co-Reyes, Eric Chu, Feryal Behbahani, Aleksandra Faust, Hugo Larochelle
- NeurIPS 2024 spotlight
- Readers: Everyone
Beyond Human Data: Scaling Self-Training for Problem-Solving with Language Models
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 et al. (20 additional authors not shown)
- Accepted by TMLR
- Readers: Everyone
Investigating the Role of Model-Based Learning in Exploration and Transfer
Jacob C Walker, Eszter Vértes, Yazhe Li, Gabriel Dulac-Arnold, Ankesh Anand, Theophane Weber, Jessica B Hamrick
- ICML 2023 Poster
- Readers: Everyone
Procedural generalization by planning with self-supervised world models
Ankesh Anand, Jacob C Walker, Yazhe Li, Eszter Vértes, Julian Schrittwieser, Sherjil Ozair, Theophane Weber, Jessica B Hamrick
- Published: 28 Jan 2022, Last Modified: 13 Feb 2023
- ICLR 2022 Poster
- Readers: Everyone
Pretraining Representations for Data-Efficient Reinforcement Learning
Max Schwarzer, Nitarshan Rajkumar, Michael Noukhovitch, Ankesh Anand, Laurent Charlin, R Devon Hjelm, Philip Bachman, Aaron Courville
- Published: 09 Nov 2021, Last Modified: 26 May 2025
- NeurIPS 2021 Poster
- Readers: Everyone
Data-Efficient Reinforcement Learning with Self-Predictive Representations
Max Schwarzer, Ankesh Anand, Rishab Goel, R. Devon Hjelm, Aaron C. Courville, Philip Bachman
- 2021 (modified: 28 Apr 2022)
- ICLR 2021
- Readers: Everyone
Pretraining Representations for Data-Efficient Reinforcement Learning
Max Schwarzer, Nitarshan Rajkumar, Michael Noukhovitch, Ankesh Anand, Laurent Charlin, R. Devon Hjelm, Philip Bachman, Aaron C. Courville
- 2021 (modified: 28 Apr 2022)
- CoRR 2021
- Readers: Everyone
Procedural Generalization by Planning with Self-Supervised World Models
Ankesh Anand, Jacob Walker, Yazhe Li, Eszter Vértes, Julian Schrittwieser, Sherjil Ozair, Théophane Weber, Jessica B. Hamrick
- 2021 (modified: 28 Apr 2022)
- CoRR 2021
- Readers: Everyone
Data-Efficient Reinforcement Learning with Self-Predictive Representations
Max Schwarzer, Ankesh Anand, Rishab Goel, R Devon Hjelm, Aaron Courville, Philip Bachman
- Published: 12 Jan 2021, Last Modified: 12 Oct 2025
- ICLR 2021 Spotlight
- Readers: Everyone

View all 11 publications

Co-Authors

View all 72 co-authors