Author

Somjit Roy

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#machine learning Preprint Apr 2025

A Generalized Tangent Approximation based Variational Inference Framework for Strongly Super-Gaussian Likelihoods

This article proposes a novel variational framework based on tangent transformation for a broad class of probability models characterized by strongly super-Gaussian likelihoods, thereby inducing conjugacy with Gaussian priors over model parameters in an otherwise intractable setup.

Somjit Roy, Pritam Dey, D. Pati et al. · 0 citations

#machine learning Preprint Sep 2025

Probabilistic Symbolic Regression for Equation Discovery via Operator-induced and Regularized Symbolic Forests

This work introduces a probabilistic symbolic regression framework that represents mathematical expressions as ensembles of symbolic trees, and develops posterior concentration guarantees when symbolic expressions approximate the underlying relationship arbitrarily well, with a near-parametric rate when an exact finite...

Somjit Roy, Pritam Dey, B. Mallick et al. · 1 citation · ⚡1