Leo Feng

According to our database, Leo Feng authored at least 17 papers between 2019 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Adaptive teachers for amortized samplers.

Minsu Kim, Sanghyeok Choi, Taeyoung Yun, Emmanuel Bengio, Leo Feng, Jarrid Rector-Brooks, Sungsoo Ahn, Jinkyoo Park, Nikolay Malkin, Yoshua Bengio

CoRR, 2024

Were RNNs All We Needed?

Leo Feng, Frederick Tung, Mohamed Osama Ahmed, Yoshua Bengio, Hossein Hajimirsadeghi

CoRR, 2024

Attention as an RNN.

Leo Feng, Frederick Tung, Hossein Hajimirsadeghi, Mohamed Osama Ahmed, Yoshua Bengio, Greg Mori

CoRR, 2024

Generative Active Learning for the Search of Small-molecule Protein Binders.

Maksym Korablyov, Cheng-Hao Liu, Moksh Jain, Almer M. van der Sloot, Eric Jolicoeur, Edward Ruediger, Andrei Cristian Nica, Emmanuel Bengio, Kostiantyn Lapchevskyi, Daniel St-Cyr, Doris Alexandra Schuetz, Victor Ion Butoi, Jarrid Rector-Brooks, Simon Blackburn, Leo Feng, Hadi Nekoei, Sai Krishna Gottipati, Priyesh Vijayan, Prateek Gupta, Ladislav Rampásek, Sasikanth Avancha, Pierre-Luc Bacon, William L. Hamilton, Brooks Paige, Sanchit Misra, Stanislaw Kamil Jastrzebski, Bharat Kaul, Doina Precup, José Miguel Hernández-Lobato, Marwin H. S. Segler, Michael M. Bronstein, Anne Marinier, Mike Tyers, Yoshua Bengio

CoRR, 2024

Memory Efficient Neural Processes via Constant Memory Attention Block.

Leo Feng, Frederick Tung, Hossein Hajimirsadeghi, Yoshua Bengio, Mohamed Osama Ahmed

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Tree Cross Attention.

Leo Feng, Frederick Tung, Hossein Hajimirsadeghi, Yoshua Bengio, Mohamed Osama Ahmed

Proceedings of the Twelfth International Conference on Learning Representations, 2024

2023

Constant Memory Attention Block.

Leo Feng, Frederick Tung, Hossein Hajimirsadeghi, Yoshua Bengio, Mohamed Osama Ahmed

CoRR, 2023

Constant Memory Attentive Neural Processes.

Leo Feng, Frederick Tung, Hossein Hajimirsadeghi, Yoshua Bengio, Mohamed Osama Ahmed

CoRR, 2023

Latent Bottlenecked Attentive Neural Processes.

Leo Feng, Hossein Hajimirsadeghi, Yoshua Bengio, Mohamed Osama Ahmed

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Towards Better Selective Classification.

Leo Feng, Mohamed Osama Ahmed, Hossein Hajimirsadeghi, Amir H. Abdi

Proceedings of the Eleventh International Conference on Learning Representations, 2023

2022

Designing Biological Sequences via Meta-Reinforcement Learning and Bayesian Optimization.

Leo Feng, Padideh Nouri, Aneri Muni, Yoshua Bengio, Pierre-Luc Bacon

CoRR, 2022

Stop Overcomplicating Selective Classification: Use Max-Logit.

Leo Feng, Mohamed Osama Ahmed, Hossein Hajimirsadeghi, Amir H. Abdi

CoRR, 2022

Continuous-Time Meta-Learning with Forward Mode Differentiation.

Tristan Deleu, David Kanaa, Leo Feng, Giancarlo Kerg, Yoshua Bengio, Guillaume Lajoie, Pierre-Luc Bacon

Proceedings of the Tenth International Conference on Learning Representations, 2022

2021

VariBAD: Variational Bayes-Adaptive Deep RL via Meta-Learning.

Luisa M. Zintgraf, Sebastian Schulze, Cong Lu, Leo Feng, Maximilian Igl, Kyriacos Shiarlis, Yarin Gal, Katja Hofmann, Shimon Whiteson

J. Mach. Learn. Res., 2021

Exploration in Approximate Hyper-State Space for Meta Reinforcement Learning.

Luisa M. Zintgraf, Leo Feng, Cong Lu, Maximilian Igl, Kristian Hartikainen, Katja Hofmann, Shimon Whiteson

Proceedings of the 38th International Conference on Machine Learning, 2021

2020

Exploration in Approximate Hyper-State Space for Meta Reinforcement Learning.

Luisa M. Zintgraf, Leo Feng, Maximilian Igl, Kristian Hartikainen, Katja Hofmann, Shimon Whiteson

CoRR, 2020

2019

VIABLE: Fast Adaptation via Backpropagating Learned Loss.

Leo Feng, Luisa M. Zintgraf, Bei Peng, Shimon Whiteson

CoRR, 2019