Cherenkov Detectors Fast Simulation Using Neural Networks. - Denis Derkach; Nikita Kazeev; Fedor Ratnikov; Andrey Ustyuzhanin; Alexandra Volokhova (CoRR, 2019)

Semi-Conditional Normalizing Flows for Semi-Supervised Learning. - Andrei Atanov; Alexandra Volokhova; Arsenii Ashukha; Ivan Sosnovik; Dmitry P. Vetrov (CoRR, 2019)

Stochasticity in Neural ODEs: An Empirical Study. - Viktor Oganesyan; Alexandra Volokhova; Dmitry P. Vetrov (CoRR, 2020)

Generative Flow Networks for Discrete Probabilistic Modeling. - Dinghuai Zhang; Nikolay Malkin; Zhen Liu 019; Alexandra Volokhova; Aaron C. Courville; Yoshua Bengio (ICML, 2022)

A theory of continuous generative flow networks. - Salem Lahlou; Tristan Deleu; Pablo Lemos; Dinghuai Zhang; Alexandra Volokhova; Alex Hernández-García; Léna Néhale Ezzine; Yoshua Bengio; Nikolay Malkin (ICML, 2023)

Crystal-GFN: sampling crystals with desirable properties and constraints. - Alex Hernández-García; Alexandre Duval; Alexandra Volokhova; Yoshua Bengio; Divya Sharma; Pierre Luc Carrier; Michal Koziarski; Victor Schmidt (CoRR, 2023)

Towards equilibrium molecular conformation generation with GFlowNets. - Alexandra Volokhova; Michal Koziarski; Alex Hernández-García; Cheng-Hao Liu; Santiago Miret; Pablo Lemos; Luca A. Thiede; Zichao Yan; Alán Aspuru-Guzik; Yoshua Bengio (CoRR, 2023)

Torsional-GFN: a conditional conformation generator for small molecules. - Alexandra Volokhova; Léna Néhale Ezzine; Piotr Gainski; Luca Scimeca; Emmanuel Bengio; Prudencio Tossou; Yoshua Bengio; Alex Hernández-García (CoRR, 2025)