HyperInterval: Hypernetwork approach to training weight interval regions in continual learning

1 code implementation • 24 May 2024 • Patryk Krukowski, Anna Bielawska, Kamil Książek, Paweł Wawrzyński, Paweł Batorski, Przemysław Spurek

To address this issue, we introduce HyperInterval, a technique that employs interval arithmetic within the embedding space and utilizes a hypernetwork to map these intervals to the target network parameter space.

HyperPlanes: Hypernetwork Approach to Rapid NeRF Adaptation

1 code implementation • 2 Feb 2024 • Paweł Batorski, Dawid Malarz, Marcin Przewięźlikowski, Marcin Mazur, Sławomir Tadeja, Przemysław Spurek

Neural radiance fields (NeRFs) are a widely accepted standard for synthesizing new 3D object views from a small number of base images.

Few-Shot Learning Object

Bounding Evidence and Estimating Log-Likelihood in VAE

no code implementations • 19 Jun 2022 • Łukasz Struski, Marcin Mazur, Paweł Batorski, Przemysław Spurek, Jacek Tabor

Many crucial problems in deep learning and statistics are caused by a variational gap, i. e., a difference between evidence and evidence lower bound (ELBO).