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How the Hessian-Spectrum of Neural Networks Depends on Data
Jasraj Singh, Enea Monzio Compagnoni, Antonio Orvieto
The Hessian matrix is an important quantity of interest when it comes to studying the loss landscape and optimization dynamics in deep learning, as well as designing measures of ge…
Effects of Dropout on Performance in Long-range Graph Learning Tasks
Jasraj Singh, Keyue Jiang, Brooks Paige +1
Message Passing Neural Networks (MPNNs) are a class of Graph Neural Networks (GNNs) that propagate information across the graph via local neighborhoods. The scheme gives rise to tw…
Training-Free Neural Active Learning with Initialization-Robustness Guarantees
Apivich Hemachandra, Zhongxiang Dai, Jasraj Singh +2
Existing neural active learning algorithms have aimed to optimize the predictive performance of neural networks (NNs) by selecting data for labelling. However, other than a good pr…