Generative Flow Networks as Entropy-Regularized RL

1 code implementation • 19 Oct 2023 • Daniil Tiapkin, Nikita Morozov, Alexey Naumov, Dmitry Vetrov

We demonstrate how the task of learning a generative flow network can be efficiently redefined as an entropy-regularized RL problem with a specific reward and regularizer structure.

Weight Averaging Improves Knowledge Distillation under Domain Shift

1 code implementation • 20 Sep 2023 • Valeriy Berezovskiy, Nikita Morozov

While it is widely known that KD can offer an improvement to student generalization in i. i. d setting, its performance under domain shift, i. e. the performance of student networks on data from domains unseen during training, has received little attention in the literature.

Domain Generalization Knowledge Distillation

Differentiable Rendering with Reparameterized Volume Sampling

1 code implementation • 21 Feb 2023 • Nikita Morozov, Denis Rakitin, Oleg Desheulin, Dmitry Vetrov, Kirill Struminsky

To generate a pixel of a novel view, it marches a ray through the pixel and computes a weighted sum of radiance emitted from a dense set of ray points.

Novel View Synthesis