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stat.ML2025
Precise asymptotic analysis of Sobolev training for random feature models
Katharine E Fisher, Matthew TC Li, Youssef Marzouk +1
Gradient information is widely useful and available in applications, and is therefore natural to include in the training of neural networks. Yet little is known theoretically about…
stat.ML2025
Can Bayesian Neural Networks Make Confident Predictions?
Katharine Fisher, Youssef Marzouk
Bayesian inference promises a framework for principled uncertainty quantification of neural network predictions. Barriers to adoption include the difficulty of fully characterizing…