Search Results for author: Karol J. Piczak

Found 3 papers, 1 papers with code

Hypernetworks build Implicit Neural Representations of Sounds

no code implementations9 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

1 code implementation16 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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