Author

Sanjit Shashi

2 papers indexed here

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#machine learning May 2026

Hessian Matching for Machine-Learned Coarse-Grained Molecular Dynamics

This work introduces a framework that augments force matching with stochastic Hessian-vector product (HVP) matching, instilling second-order curvature information into CG potentials without constructing the full Hessian.

S. Murdeshwar, Sanjit Shashi, Kevin Bachelor et al. · arXiv.org · 0 citations

#machine learning Open access Jan 2026

Holographic generative flows with AdS/CFT

This work builds Generative AdS, an approach to generative flow matching in which the dynamics are represented by the evolution of fields in AdS, together with a residual correction learned by a neural network.

Ehsan Mirafzali, Sanjit Shashi, S. Murdeshwar et al. · Machine Learning: Science an... · 0 citations