Nikita Morozov
- Research Assistant:Faculty of Computer Science / AI and Digital Science Institute / Centre of Deep Learning and Bayesian Methods
- Nikita Morozov has been at HSE University since 2021.
Young Faculty Support Programme (Group of Young Academic Professionals)
Category "New Researchers" (2024)
Courses (2023/2024)
- Deep Learning 1 (Bachelor’s programme; Faculty of Computer Science; 3 year, 2, 3 module)Eng
- Machine Learning 1 (Bachelor’s programme; Faculty of Computer Science; 3 year, 1, 2 module)Rus
Machine Learning 2 (Bachelor’s programme; Faculty of Computer Science; field of study "01.03.02. Прикладная математика и информатика", field of study "01.03.02. Прикладная математика и информатика"; 3 year, 3, 4 module)Rus
- Past Courses
Courses (2022/2023)
- Introduction to Deep Learning (Bachelor’s programme; Faculty of Computer Science; 3 year, 1-3 module)Eng
- Machine Learning 1 (Bachelor’s programme; Faculty of Computer Science; 3 year, 1, 2 module)Rus
Machine Learning 2 (Bachelor’s programme; Faculty of Computer Science; field of study "01.03.02. Прикладная математика и информатика", field of study "01.03.02. Прикладная математика и информатика"; 3 year, 3, 4 module)Rus
Publications4
- Chapter Morozov N., Rakitin D., Oleg Desheulin, Dmitry P. Vetrov, Struminsky K. Differentiable Rendering with Reparameterized Volume Sampling, in: Proceedings of The 27th International Conference on Artificial Intelligence and Statistics (AISTATS 2024), 2-4 May 2024, Palau de Congressos, Valencia, Spain. PMLR: Volume 238 Vol. 238. Valencia : PMLR, 2024. P. 4852-4860.
- Chapter Tiapkin D., Morozov N., Naumov A., Dmitry P. Vetrov. Generative Flow Networks as Entropy-Regularized RL, in: Proceedings of The 27th International Conference on Artificial Intelligence and Statistics (AISTATS 2024), 2-4 May 2024, Palau de Congressos, Valencia, Spain. PMLR: Volume 238 Vol. 238. Valencia : PMLR, 2024. P. 4213-4221.
- Chapter Morozov N., Rakitin D., Oleg Desheulin, Vetrov D., Struminsky K. Differentiable Rendering with Reparameterized Volume Sampling, in: Neural Fields across Fields: Methods and Applications of Implicit Neural Representations. ICLR 2023 Workshop. , 2023. Ch. 8.
- Chapter Berezovskiy V., Morozov N. Weight Averaging Improves Knowledge Distillation under Domain Shift, in: The 2nd Workshop and Challenges for Out-of-Distribution Generalization in Computer Vision. ICCV 2023. , 2023.