3 citations · 7 across the 15 of their papers we have counts for
4 papers · 1 filter
DANCE: Doubly Adaptive Neighborhood Conformal Estimation
Brandon R. Feng, Brian J. Reich, Daniel Beaglehole +7
The recent developments of complex deep learning models have led to unprecedented ability to accurately predict across multiple data representation types. Conformal prediction for…
Emergence in non-neural models: grokking modular arithmetic via average gradient outer product
Neil Mallinar, Daniel Beaglehole, Libin Zhu +3
Neural networks trained to solve modular arithmetic tasks exhibit grokking, a phenomenon where the test accuracy starts improving long after the model achieves 100% training accura…
Feature learning as alignment: a structural property of gradient descent in non-linear neural networks
Daniel Beaglehole, Ioannis Mitliagkas, Atish Agarwala
Understanding the mechanisms through which neural networks extract statistics from input-label pairs through feature learning is one of the most important unsolved problems in supe…
Mechanism of feature learning in convolutional neural networks
Daniel Beaglehole, Adityanarayanan Radhakrishnan, Parthe Pandit +1
Understanding the mechanism of how convolutional neural networks learn features from image data is a fundamental problem in machine learning and computer vision. In this work, we i…