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06/21/2023
Constant Memory Attention Block
Modern foundation model architectures rely on attention mechanisms to ef...
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05/23/2023
Constant Memory Attentive Neural Processes
Neural Processes (NPs) are efficient methods for estimating predictive u...
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11/15/2022
Latent Bottlenecked Attentive Neural Processes
Neural Processes (NPs) are popular methods in meta-learning that can est...
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09/13/2022
Designing Biological Sequences via Meta-Reinforcement Learning and Bayesian Optimization
The ability to accelerate the design of biological sequences can have a ...
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06/17/2022
Stop Overcomplicating Selective Classification: Use Max-Logit
We tackle the problem of Selective Classification where the goal is to a...
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03/02/2022
Continuous-Time Meta-Learning with Forward Mode Differentiation
Drawing inspiration from gradient-based meta-learning methods with infin...
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10/02/2020
Exploration in Approximate Hyper-State Space for Meta Reinforcement Learning
Meta-learning is a powerful tool for learning policies that can adapt ef...
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11/29/2019
