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cs.LG2026
Reliable Risk Estimation with Kernel Mean Matching under Dependent Sampling
Alexey Zaytsev, Diana Koldasbayeva, Egor Serov
Kernel Mean Matching (KMM) estimates risk under covariate shift by reweighting labelled source samples so that their kernel mean embedding matches that of unlabeled target samples.…
cs.LG2026
MercerFlow: Flow Matching in a Kernel-Induced Latent Space for Probabilistic Forecasting
Ilya Kuleshov, Egor Serov, Alexey Zaytsev
Recent work has shown that probabilistic flow matching for time series forecasting benefits from a data-matched prior. The resulting prior introduces local correlations, which a se…
cs.LG2026
Efficient Neural Controlled Differential Equations via Attentive Kernel Smoothing
Egor Serov, Ilya Kuleshov, Alexey Zaytsev
Neural Controlled Differential Equations (Neural CDEs) provide a powerful continuous-time framework for sequence modeling, yet the roughness of the driving control path often restr…