6 citations · 11 across the 3 of their papers we have counts for
4 papers
Hypernetworks build Implicit Neural Representations of Sounds
Filip Szatkowski, Karol J. Piczak, Przemysław Spurek +2
Implicit Neural Representations (INRs) are nowadays used to represent multimedia signals across various real-life applications, including image super-resolution, image compression,…
HyperSound: Generating Implicit Neural Representations of Audio Signals with Hypernetworks
Filip Szatkowski, Karol J. Piczak, Przemysław Spurek +2
Implicit neural representations (INRs) are a rapidly growing research field, which provides alternative ways to represent multimedia signals. Recent applications of INRs include im…
Continual Learning with Guarantees via Weight Interval Constraints
Maciej Wołczyk, Karol J. Piczak, Bartosz Wójcik +5
We introduce a new training paradigm that enforces interval constraints on neural network parameter space to control forgetting. Contemporary Continual Learning (CL) methods focus…
Siamese Generative Adversarial Privatizer for Biometric Data
Witold Oleszkiewicz, Peter Kairouz, Karol Piczak +2
State-of-the-art machine learning algorithms can be fooled by carefully crafted adversarial examples. As such, adversarial examples present a concrete problem in AI safety. In this…