Publications

Research papers and preprints I have contributed to, spanning machine learning, optimisation and applied probability.

AdaWeather: Adaptively Mixing Probabilistic Weather Forecasts with Logarithmic Regret

Saptarishi Dhanuka, Sarvesh Iyer, Manmeet Singh, Mihir More, Rushil Gupta, Dhruman Gupta, Parthasarathi Mukhopadhyay, Sandeep Juneja

arXivJune 2026

An adaptive framework that mixes many probabilistic weather forecasts using both machine learning and a mixture of experts. We prove logarithmic regret against the best static mixture of experts in hindsight, and show empirical gains on temperature forecasting.

Fundamental limits for weighted empirical approximations of tilted distributions

Sarvesh Ravichandran Iyer, Himadri Mandal, Dhruman Gupta, Rushil Gupta, Agniv Bandhyopadhyay, Achal Bassamboo, Varun Gupta, Sandeep Juneja

AISTATS 2026December 2025arXiv

A sharp characterisation of how accurately a self-normalized importance sampler can approximate a tilted distribution from samples of the base distribution alone. Bounded random vectors need polynomially many samples in the tilt amount; unbounded ones need super-polynomially many.