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Suchismita Padhy

2 accepted papers

2021

On the geometry of generalization and memorization in deep neural networks

ICLR 2021poster

Understanding how large neural networks avoid memorizing training data is key to explaining their high generalization performance. To examine the structure of when and where memorization occurs in a deep network, we use a recently developed replica-based mean field theoretic geometric analysis metho…

Cited by 87SourcePDFScholar
2019

Untangling in Invariant Speech Recognition

NeurIPS 2019poster

Encouraged by the success of deep convolutional neural networks on a variety of visual tasks, much theoretical and experimental work has been aimed at understanding and interpreting how vision networks operate. At the same time, deep neural networks have also achieved impressive performance in audi…