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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.
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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.
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Improved Guarantees for Fully Dynamic k-Center Clustering with Outliers in General Metric Spaces
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In the first case, points arrive sequentially, and only a summary can be stored in memory.
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