2 papers
cs.LG2026
Inverse Entropic Optimal Transport Solves Semi-supervised Learning via Data Likelihood Maximization
Mikhail Persiianov, Arip Asadulaev, Nikita Andreev +5
Learning conditional distributions is a central problem in machine learning, which is typically approached via supervised methods with paired data …
cs.LG2026
Learning of Population Dynamics: Inverse Optimization Meets JKO Scheme
Mikhail Persiianov, Jiawei Chen, Petr Mokrov +3
Learning population dynamics involves recovering the underlying process that governs particle evolution, given evolutionary snapshots of samples at discrete time points. Recent met…