Ankesh Anand - RankMe

24 papers A* 6A 2B 1Journal 13Unranked 2

Year	Rank	Type	Title / Venue / Authors
2024	J	`jnl`	Beyond Human Data: Scaling Self-Training for Problem-Solving with Language Models. Trans. Mach. Learn. Res. 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
2024	J	`jnl`	Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context. CoRR 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.
2024	A*	`conf`	Many-Shot In-Context Learning. NeurIPS Rishabh Agarwal, Avi Singh, Lei Zhang, Bernd Bohnet, Luis Rosias, Stephanie C. Y. Chan, Biao Zhang, Ankesh Anand, Zaheer Abbas, Azade Nova, John D. Co-Reyes, Eric Chu, Feryal M. P. Behbahani, Aleksandra Faust, Hugo Larochelle
2024	J	`jnl`	Many-Shot In-Context Learning. CoRR 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
2023	J	`jnl`	Beyond Human Data: Scaling Self-Training for Problem-Solving with Language Models. CoRR 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
2023	A*	`conf`	Investigating the Role of Model-Based Learning in Exploration and Transfer. ICML Jacob C. Walker, Eszter Vértes, Yazhe Li, Gabriel Dulac-Arnold, Ankesh Anand, Theophane Weber, Jessica B. Hamrick
2023	J	`jnl`	Investigating the role of model-based learning in exploration and transfer. CoRR Jacob C. Walker, Eszter Vértes, Yazhe Li, Gabriel Dulac-Arnold, Ankesh Anand, Théophane Weber, Jessica B. Hamrick
2022	A*	`conf`	Procedural generalization by planning with self-supervised world models. ICLR Ankesh Anand, Jacob C. Walker, Yazhe Li, Eszter Vértes, Julian Schrittwieser, Sherjil Ozair, Theophane Weber, Jessica B. Hamrick
2021	A*	`conf`	Data-Efficient Reinforcement Learning with Self-Predictive Representations. ICLR Max Schwarzer, Ankesh Anand, Rishab Goel, R. Devon Hjelm, Aaron C. Courville, Philip Bachman
2021	A*	`conf`	Pretraining Representations for Data-Efficient Reinforcement Learning. NeurIPS Max Schwarzer, Nitarshan Rajkumar, Michael Noukhovitch, Ankesh Anand, Laurent Charlin, R. Devon Hjelm, Philip Bachman, Aaron C. Courville
2021	J	`jnl`	Pretraining Representations for Data-Efficient Reinforcement Learning. CoRR Max Schwarzer, Nitarshan Rajkumar, Michael Noukhovitch, Ankesh Anand, Laurent Charlin, R. Devon Hjelm, Philip Bachman, Aaron C. Courville
2021	J	`jnl`	Procedural Generalization by Planning with Self-Supervised World Models. CoRR Ankesh Anand, Jacob C. Walker, Yazhe Li, Eszter Vértes, Julian Schrittwieser, Sherjil Ozair, Théophane Weber, Jessica B. Hamrick
2020	J	`jnl`	Data-Efficient Reinforcement Learning with Momentum Predictive Representations. CoRR Max Schwarzer, Ankesh Anand, Rishab Goel, R. Devon Hjelm, Aaron C. Courville, Philip Bachman
2019	A*	`conf`	Unsupervised State Representation Learning in Atari. NeurIPS Ankesh Anand, Evan Racah, Sherjil Ozair, Yoshua Bengio, Marc-Alexandre Côté, R. Devon Hjelm
2019	J	`jnl`	Unsupervised State Representation Learning in Atari. CoRR Ankesh Anand, Evan Racah, Sherjil Ozair, Yoshua Bengio, Marc-Alexandre Côté, R. Devon Hjelm
2018	J	`jnl`	Blindfold Baselines for Embodied QA. CoRR Ankesh Anand, Eugene Belilovsky, Kyle Kastner, Hugo Larochelle, Aaron C. Courville
2018	—	`conf`	HoME: a Household Multimodal Environment. ICLR (Workshop) Simon Brodeur, Ethan Perez, Ankesh Anand, Florian Golemo, Luca Celotti, Florian Strub, Jean Rouat, Hugo Larochelle, Aaron C. Courville
2018	B	`conf`	MMGAN: Manifold-Matching Generative Adversarial Networks. ICPR Noseong Park, Ankesh Anand, Joel Ruben Antony Moniz, Kookjin Lee, Jaegul Choo, David Keetae Park, Tanmoy Chakraborty, Hongkyu Park, Youngmin Kim
2018	—	`conf`	Phishing URL Detection with Oversampling based on Text Generative Adversarial Networks. IEEE BigData Ankesh Anand, Kshitij Gorde, Joel Ruben Antony Moniz, Noseong Park, Tanmoy Chakraborty, Bei-Tseng Chu
2017	A	`conf`	FairScholar: Balancing Relevance and Diversity for Scientific Paper Recommendation. ECIR Ankesh Anand, Tanmoy Chakraborty, Amitava Das
2017	J	`jnl`	HoME: a Household Multimodal Environment. CoRR Simon Brodeur, Ethan Perez, Ankesh Anand, Florian Golemo, Luca Celotti, Florian Strub, Jean Rouat, Hugo Larochelle, Aaron C. Courville
2017	J	`jnl`	MMGAN: Manifold Matching Generative Adversarial Network for Generating Images. CoRR Noseong Park, Ankesh Anand, Joel Ruben Antony Moniz, Kookjin Lee, Tanmoy Chakraborty, Jaegul Choo, Hongkyu Park, Youngmin Kim
2017	A	`conf`	We Used Neural Networks to Detect Clickbaits: You Won't Believe What Happened Next! ECIR Ankesh Anand, Tanmoy Chakraborty, Noseong Park
2016	J	`jnl`	We used Neural Networks to Detect Clickbaits: You won't believe what happened Next! CoRR Ankesh Anand, Tanmoy Chakraborty, Noseong Park