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a2c548b2ed3141400d86a235eaa6fad0-Paper-Datasets_and_Benchmarks_Track.pdf

cb2266111eadcfa2c02187ace64e2183-Supplemental-Conference.pdf

Efficient Uncertainty Quantification and Reduction for Over-Parameterized Neural Networks

Neural Information Processing Systems

Uncertainty quantification (UQ) is important for reliability assessment and enhancement of machine learning models.

a2a7e58309d5190082390ff10ff3b2b8-Paper-Datasets_and_Benchmarks_Track.pdf

a29f0fc2127c9d8cb1c9d86e423241af-Paper-Conference.pdf

Checklist 1. For all authors (a)

Neural Information Processing Systems

A.1 Motivation For what purpose was the dataset created?

a291dad965af9bc2e39ffeb2ca1c6dc0-Paper-Datasets_and_Benchmarks_Track.pdf

ProteinGym: Large-Scale Benchmarks for Protein Fitness Prediction and Design

Neural Information Processing Systems

Addressing these challenges requires scale. To that end we introduce ProteinGym, a large-scale and holistic set of benchmarks specifically designed for protein fitness prediction and design.

a28af221f2f70be183afc16797a56b91-Paper-Conference.pdf

Improved Guarantees for Fully Dynamic k-Center Clustering with Outliers in General Metric Spaces

Neural Information Processing Systems

In the first case, points arrive sequentially, and only a summary can be stored in memory.