Author

Shourya Verma

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#machine learning Preprint Sep 2026

Certified Approximation for Interpretable Representer Landmarks

Representer explanations rank the training landmarks that most influence a self-supervised representation. At scale, this ranking rests on up to four stacked approximations of the empirical neural tangent kernel (eNTK). These are random output heads, a parameter sketch, landmark sampling and a coefficient fit. Existing...

Jayanta Mukherjee, Shourya Verma, Meng-Bo Wang et al. · 0 citations

Open access Aug 2026

Solving High-Dimensional Population Balance Equations via Dynamics-Preserving Autoencoders

A hybrid mechanistic-machine learning framework for reducing and simulating PBEs defined over high-dimensional intracellular coordinates provides a computationally tractable and mechanistically interpretable route for integrating single-cell genomic data with population balance models of cell-state dynamics.

Prateek Gupta, Shourya Verma, Ananth Grama et al. · bioRxiv · 0 citations