Hello, I am Nikita! I am a first-year PhD student at HSE University supervised by Prof. Dmitry Vetrov and a part of Bayesian Methods Research Group. My research is focused on neural samplers, such as Generative Flow Networks (GFlowNets) in discrete domains and Diffusion Samplers in continuous domains. By drawing ideas from reinforcement learning and variational inference, I am working towards creating new efficient training algorithms for these models and expanding their theoretical understanding. Generally speaking, my research interests include generative modeling and probabilistic methods in deep learning, as well as their applications in the sciences.

I did a research internship at EPFL MLBIO under the supervision of Prof. Maria Brbić, where I worked with Yist Yu on geometric diffusion models for single-cell data. I have also previously worked on novel view synthesis and text-to-3D generative models with Kirill Struminsky. Prior to joining Bayesian Methods Research Group, I was a software engineer intern at Yandex, where I worked on refining YTsaurus platform.

I have a background in competitive programming, I participated in 2024 ICPC World Finals and you can find me on codeforces.

Email / CV (Last update: June 2025) / GitHub / Google Scholar / OpenReview / HSE webpage / Twitter

 

Publications

• Adaptive Destruction Processes for Diffusion Samplers
  Timofei Gritsaev, Nikita Morozov, Kirill Tamogashev, Daniil Tiapkin, Sergey Samsonov, Alexey Naumov, Dmitry Vetrov, Nikolay Malkin
  arXiv / code TBA
  Preprint 2025

• Revisiting Non-Acyclic GFlowNets in Discrete Environments
  Nikita Morozov*, Ian Maksimov*, Daniil Tiapkin, Sergey Samsonov
  arXiv / code
  ICML 2025

• Tissue Reassembly with Generative AI
  Tingyang Yu, Chanakya Ekbote, Nikita Morozov, Jiashuo Fan, Pascal Frossard, Stéphane d’Ascoli, Maria Brbić
  bioRxiv / project / code
  Preprint, ICML 2025 Workshop on Generative AI and Biology (Spotlight)

• Optimizing Backward Policies in GFlowNets via Trajectory Likelihood Maximization
  Timofei Gritsaev, Nikita Morozov, Sergey Samsonov, Daniil Tiapkin
  arXiv / code
  ICLR 2025

• Improving GFlowNets with Monte Carlo Tree Search
  Nikita Morozov, Daniil Tiapkin, Sergey Samsonov, Alexey Naumov, Dmitry Vetrov
  arXiv
  ICML 2024 Workshop on Structured Probabilistic Inference & Generative Modeling

• Generative Flow Networks as Entropy-Regularized RL
  Daniil Tiapkin*, Nikita Morozov*, Alexey Naumov, Dmitry Vetrov
  arXiv / code
  AISTATS 2024 (Oral)

• Differentiable Rendering with Reparameterized Volume Sampling
  Nikita Morozov, Denis Rakitin, Oleg Desheulin, Dmitry Vetrov, Kirill Struminsky
  arXiv / code
  AISTATS 2024
  Short version appeared in ICLR 2023 Workshop on Neural Fields

• Weight Averaging Improves Knowledge Distillation under Domain Shift
  Valeriy Berezovskiy, Nikita Morozov
  arXiv / code
  ICCV 2023 Workshop on Out-of-Distribution Generalization in Computer Vision