Search Results for author: Karol J. Piczak

Found 3 papers, 2 papers with code

Hypernetworks build Implicit Neural Representations of Sounds

1 code implementation9 Feb 2023 Filip Szatkowski, Karol J. Piczak, Przemysław Spurek, Jacek Tabor, Tomasz Trzciński

Implicit Neural Representations (INRs) are nowadays used to represent multimedia signals across various real-life applications, including image super-resolution, image compression, or 3D rendering.

Image Compression Image Super-Resolution +1

HyperSound: Generating Implicit Neural Representations of Audio Signals with Hypernetworks

no code implementations3 Nov 2022 Filip Szatkowski, Karol J. Piczak, Przemysław Spurek, Jacek Tabor, Tomasz Trzciński

Implicit neural representations (INRs) are a rapidly growing research field, which provides alternative ways to represent multimedia signals.

Image Super-Resolution Meta-Learning

Continual Learning with Guarantees via Weight Interval Constraints

2 code implementations16 Jun 2022 Maciej Wołczyk, Karol J. Piczak, Bartosz Wójcik, Łukasz Pustelnik, Paweł Morawiecki, Jacek Tabor, Tomasz Trzciński, Przemysław Spurek

We introduce a new training paradigm that enforces interval constraints on neural network parameter space to control forgetting.

Continual Learning

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