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In offline model-based optimization, we strive to maximize a black-box objective function by only leveraging a static dataset of designs and their scores.
Simple statistical gradient-following algorithms for connectionist reinforcement learning
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Survey of variation in human transcription factors reveals prevalent dna binding changes
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The reparameterization trick for acquisition functions
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Single-mutation fitness landscapes for an enzyme on multiple substrates reveal specificity is globally encoded
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A framework for exhaustively mapping functional missense variants
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Bilevel programming for hyperparameter optimization and meta-learning
Luca Franceschi, Paolo Frasconi, Saverio Salzo, Riccardo Grazzi, and Massimiliano Pontil · 2018
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Learning to reweight examples for robust deep learning
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Model-based reinforcement learning for biological sequence design
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Human 5 UTR design and variant effect prediction from a massively parallel translation assay
Paul J Sample, Ban Wang, David W Reid, Vlad Presnyak, Iain J McFadyen, David R Morris, and Georg Seelig · 2019
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Wide neural networks of any depth evolve as linear models under gradient descent
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Conditioning by adaptive sampling for robust design
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Pytorch: An imperative style, high-performance deep learning library
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Learning data manipulation for augmentation and weighting
Zhiting Hu, Bowen Tan, Russ R Salakhutdinov, Tom M Mitchell, and Eric P Xing · 2019
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Pervasive pairwise intragenic epistasis among sequential mutations in tem-1 β \beta -lactamase
Courtney E Gonzalez and Marc Ostermeier · 2019
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Neural tangent generalization attacks
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Soft-label dataset distillation and text dataset distillation
Ilia Sucholutsky and Matthias Schonlau · 2021
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Dataset distillation with infinitely wide convolutional networks
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Generalized data weighting via class-level gradient manipulation
Can Chen, Shuhao Zheng, Xi Chen, Erqun Dong, Xue Steve Liu, Hao Liu, and Dejing Dou · 2021
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Dnabert: pre-trained bidirectional encoder representations from transformers model for dna-language in genome
Yanrong Ji, Zhihan Zhou, Han Liu, and Ramana V Davuluri · 2021
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Unifying likelihood-free inference with black-box optimization and beyond
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Artificial intelligence foundation for therapeutic science
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Machine Learning Approaches to Reveal Discrete Signals in Gene Expression
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Tommaso Giovannelli, Griffin Kent, and Luis Nunes Vicente · 2023
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Bidirectional learning for offline model-based biological sequence design
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