4 papers
VaSST: Variational Inference for Symbolic Regression using Soft Symbolic Trees
Somjit Roy, Pritam Dey, Bani K. Mallick
Symbolic regression (SR) has gained recent traction in AI-driven scientific discovery for learning closed-form physical laws. Yet existing methods are dominated by heuristic search…
A Generalized Tangent Approximation based Variational Inference Framework for Strongly Super-Gaussian Likelihoods
Somjit Roy, Pritam Dey, Debdeep Pati +1
Variational inference, as an alternative to Markov chain Monte Carlo sampling, has played a transformative role in enabling scalable computation for complex Bayesian models. Nevert…
Frequentist Regret Analysis of Gaussian Process Thompson Sampling via Fractional Posteriors
Somjit Roy, Prateek Jaiswal, Anirban Bhattacharya +2
We study Gaussian Process Thompson Sampling (GP-TS) for sequential decision-making over compact, continuous action spaces and provide a frequentist regret analysis based on fractio…
Probabilistic Symbolic Regression for Equation Discovery via Operator-induced and Regularized Symbolic Forests
Somjit Roy, Pritam Dey, Debdeep Pati +1
Symbolic regression has emerged as a powerful tool for artificial intelligence-driven scientific discovery by learning interpretable analytical expressions that reveal governing re…