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Found 3 papers, 2 papers with code
Iterative SE(3)-Transformers
Motivated by this application, we implement an iterative version of the SE(3)-Transformer, an SE(3)-equivariant attention-based model for graph data.
Unified framework for modeling multivariate distributions in biological sequences
Revealing the functional sites of biological sequences, such as evolutionary conserved, structurally interacting or co-evolving protein sites, is a fundamental, and yet challenging task.
Quantitative Methods
Depth and nonlinearity induce implicit exploration for RL
The question of how to explore, i. e., take actions with uncertain outcomes to learn about possible future rewards, is a key question in reinforcement learning (RL).
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