2024
Adaptive teachers for amortized samplers.
CoRR, 2024

Were RNNs All We Needed?
CoRR, 2024

Attention as an RNN.
CoRR, 2024

Generative Active Learning for the Search of Small-molecule Protein Binders.
CoRR, 2024

Memory Efficient Neural Processes via Constant Memory Attention Block.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

Tree Cross Attention.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

2023
Constant Memory Attention Block.
CoRR, 2023

Constant Memory Attentive Neural Processes.
CoRR, 2023

Latent Bottlenecked Attentive Neural Processes.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

Towards Better Selective Classification.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

2022
Designing Biological Sequences via Meta-Reinforcement Learning and Bayesian Optimization.
CoRR, 2022

Stop Overcomplicating Selective Classification: Use Max-Logit.
CoRR, 2022

Continuous-Time Meta-Learning with Forward Mode Differentiation.
Proceedings of the Tenth International Conference on Learning Representations, 2022

2021
VariBAD: Variational Bayes-Adaptive Deep RL via Meta-Learning.
J. Mach. Learn. Res., 2021

Exploration in Approximate Hyper-State Space for Meta Reinforcement Learning.
Proceedings of the 38th International Conference on Machine Learning, 2021

2020
Exploration in Approximate Hyper-State Space for Meta Reinforcement Learning.
CoRR, 2020

2019
VIABLE: Fast Adaptation via Backpropagating Learned Loss.
CoRR, 2019