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cs.LG2025
Metalic: Meta-Learning In-Context with Protein Language Models
Jacob Beck, Shikha Surana, Manus McAuliffe +4
Predicting the biophysical and functional properties of proteins is essential for in silico protein design. Machine learning has emerged as a promising technique for such predictio…
cs.LG2025
Overconfident Oracles: Limitations of In Silico Sequence Design Benchmarking
Shikha Surana, Nathan Grinsztajn, Timothy Atkinson +2
Machine learning methods can automate the in silico design of biological sequences, aiming to reduce costs and accelerate medical research. Given the limited access to wet labs, in…
cs.LG2024
Combinatorial Optimization with Policy Adaptation using Latent Space Search
Felix Chalumeau, Shikha Surana, Clement Bonnet +4
Combinatorial Optimization underpins many real-world applications and yet, designing performant algorithms to solve these complex, typically NP-hard, problems remains a significant…