activity
20192022
most citedInvertible Denoising Network: A Light Solution for Real Noise Removal

11 citations · 21 across the 8 of their papers we have counts for

collaborators

9 papers

cs.IR20221 cited

Item-based Variational Auto-encoder for Fair Music Recommendation

Jinhyeok Park, Dain Kim, Dongwoo Kim

We present our solution for the EvalRS DataChallenge. The EvalRS DataChallenge aims to build a more realistic recommender system considering accuracy, fairness, and diversity in ev…

cs.LG20222 cited

Substructure-Atom Cross Attention for Molecular Representation Learning

Jiye Kim, Seungbeom Lee, Dongwoo Kim +2

Designing a neural network architecture for molecular representation is crucial for AI-driven drug discovery and molecule design. In this work, we propose a new framework for molec…

cs.LG2022

MetaSSD: Meta-Learned Self-Supervised Detection

Moon Jeong Park, Jungseul Ok, Yo-Seb Jeon +1

Deep learning-based symbol detector gains increasing attention due to the simple algorithm design than the traditional model-based algorithms such as Viterbi and BCJR. The supervis…

cs.CV20214 cited

Informative Class Activation Maps

Zhenyue Qin, Dongwoo Kim, Tom Gedeon

We study how to evaluate the quantitative information content of a region within an image for a particular label. To this end, we bridge class activation maps with information theo…

cs.LG2021

Neural Network Classifier as Mutual Information Evaluator

Zhenyue Qin, Dongwoo Kim, Tom Gedeon

Cross-entropy loss with softmax output is a standard choice to train neural network classifiers. We give a new view of neural network classifiers with softmax and cross-entropy as…

eess.IV202111 cited

Invertible Denoising Network: A Light Solution for Real Noise Removal

Yang Liu, Zhenyue Qin, Saeed Anwar +4

Invertible networks have various benefits for image denoising since they are lightweight, information-lossless, and memory-saving during back-propagation. However, applying inverti…