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publications

Dynamic Activity-Dependent Pruning (DADP): A Reverse-Hebbian Structural Plasticity Framework for Neural Networks

Under review, ICLR 2027, 2026

A dynamic structural sparsification algorithm based on biological synapse elimination, achieving 72.79% structural sparsity on VGG-16 while improving CIFAR-10 baseline accuracy by +1.70%.

Recommended citation: Deshpande, B. (2026). Dynamic Activity-Dependent Pruning (DADP): A Reverse-Hebbian Structural Plasticity Framework for Neural Networks. arXiv preprint arXiv:2610.11853 (Under review, ICLR 2027).
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teaching

Teaching experience 1

Undergraduate course, University 1, Department, 2014

This is a description of a teaching experience. You can use markdown like any other post.

Teaching experience 2

Workshop, University 1, Department, 2015

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