3 citations · 3 across the 2 of their papers we have counts for
2 papers
cs.LG2024
HINT: Hypernetwork Approach to Training Weight Interval Regions in Continual Learning
Patryk Krukowski, Anna Bielawska, Kamil Książek +3
Recently, a new Continual Learning (CL) paradigm was presented to control catastrophic forgetting, called Interval Continual Learning (InterContiNet), which relies on enforcing int…
cs.NE2020★ 3 cited
DCT-Conv: Coding filters in convolutional networks with Discrete Cosine Transform
Karol Chęciński, Paweł Wawrzyński
Convolutional neural networks are based on a huge number of trained weights. Consequently, they are often data-greedy, sensitive to overtraining, and learn slowly. We follow the li…