Author

Syamantak Kumar

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#machine learning Preprint Oct 2026

Conditional Flow Matching for Transport Between Markov Processes

Motivated by sequence-to-sequence transport in the context time-series domain adaptation, we study the problem of transportation between trajectories of Markov processes. Given a limited number of trajectories from source distribution and the target distribution, we formulate a flow matching based algorithm which learn...

Syamantak Kumar, D. Nagaraj, Saptarshi Roy et al. · 0 citations

#machine learning Preprint Sep 2026

High-Magnetization Sampling at Low Temperatures: Ising Models and Bayesian Sparse Linear Regression

Sparsity is a powerful structural resource in optimization and statistics. We develop frameworks for leveraging sparsity in sampling problems over the Hamming slice $\mathcal{X}_k^d:=\{\mathbf{x}\in\{\pm 1\}^d:|\{i:\mathbf{x}_i=1\}|=k\}$, in high-dimensional regimes where $k\ll d$ (i.e., where $\mathcal{X}_k^d$ is \emp...

Syamantak Kumar, Purnamrita Sarkar, Kevin Tian et al. · 0 citations