works on

From the 1 of 17 linked papers with an AI index.

activity
20242026
collaborators

17 papers

cs.CV2026

Large scale cross-regional remote sensing flood monitoring framework for operative mapping and impact analysis

Ilya Novikov, Svetlana Illarionova, Ruslan Dzharkinov +6

The paper proposes an end‑to‑end multimodal deep‑learning framework that combines SAR, multispectral and elevation data to detect flood water surfaces and assess damage across larg…

cs.AI2026

LLMs in Process Diagram Engineering: From Optimal PFDs to Validated P&IDs

Timur Zakarin, Sergei Voitov, Sergei Shumilin +1

Nowadays, the creation of a process flow diagram (PFD) and its subsequent transformation into a piping and instrumentation diagram (P&ID) is predominantly performed manually. Apply…

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

Diffusion & Adversarial Schrödinger Bridges via Iterative Proportional Markovian Fitting

Sergei Kholkin, Grigoriy Ksenofontov, David Li +6

The Iterative Markovian Fitting (IMF) procedure, which iteratively projects onto the space of Markov processes and the reciprocal class, successfully solves the Schrödinger Bridge…

cs.LG2026

Loss Barcode: A Topological Measure of Escapability in Loss Landscapes

Serguei Barannikov, Daria Voronkova, Alexander Mironenko +4

Neural network training is commonly based on SGD. However, the understanding of SGD's ability to converge to good local minima, given the non-convex nature of loss functions and th…

cs.LG2026

InfoBridge: Mutual Information estimation via Bridge Matching

Sergei Kholkin, Ivan Butakov, Evgeny Burnaev +2

Diffusion bridge models have recently become a powerful tool in the field of generative modeling. In this work, we leverage their power to address another important problem in mach…