4 citations · 6 across the 6 of their papers we have counts for
4 papers · 1 filter
GlueNN: gluing patchwise analytic solutions with neural networks
Doyoung Kim, Donghee Lee, Hye-Sung Lee +2
In the analysis of complex physical systems, the objective often extends beyond merely computing a numerical solution to capturing the precise crossover between different regimes a…
Adaptive Shortcut Debiasing for Online Continual Learning
Doyoung Kim, Dongmin Park, Yooju Shin +3
We propose a novel framework DropTop that suppresses the shortcut bias in online continual learning (OCL) while being adaptive to the varying degree of the shortcut bias incurred b…
Robust Data Pruning under Label Noise via Maximizing Re-labeling Accuracy
Dongmin Park, Seola Choi, Doyoung Kim +2
Data pruning, which aims to downsize a large training set into a small informative subset, is crucial for reducing the enormous computational costs of modern deep learning. Though…
One Size Fits All for Semantic Shifts: Adaptive Prompt Tuning for Continual Learning
Doyoung Kim, Susik Yoon, Dongmin Park +4
In real-world continual learning (CL) scenarios, tasks often exhibit intricate and unpredictable semantic shifts, posing challenges for fixed prompt management strategies which are…