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Youjing Yu

2 accepted papers

2026

Exploiting weight-space symmetries for approximating curvature

ICML 2026poster

Many machine learning techniques rely on approximating a loss function's curvature, but this is notoriously hard to do at the scale of modern deep networks. Surprisingly, no previous work has exploited the curvature constraints that arise from well known weight-space symmetries in loss landscapes. B…

Cited by 0SourceScholar
2024

Second-order forward-mode optimization of recurrent neural networks for neuroscience

NeurIPS 2024spotlight

A common source of anxiety for the computational neuroscience student is the question “will my recurrent neural network (RNN) model finally learn that task?”. Unlike in machine learning where any architectural modification of an RNN (e.g. GRU or LSTM) is acceptable if it speeds up training, the RNN…

Cited by 0SourcePDFScholar