activity
20152022
most citedLearning What and Where to Transfer

25 citations · 131 across the 21 of their papers we have counts for

collaborators

44 papers

cs.CV20227 cited

Exploring The Role of Mean Teachers in Self-supervised Masked Auto-Encoders

Youngwan Lee, Jeffrey Willette, Jonghee Kim +2

Masked image modeling (MIM) has become a popular strategy for self-supervised learning~(SSL) of visual representations with Vision Transformers. A representative MIM model, the mas…

cs.IR20221 cited

Augmenting Document Representations for Dense Retrieval with Interpolation and Perturbation

Soyeong Jeong, Jinheon Baek, Sukmin Cho +2

Dense retrieval models, which aim at retrieving the most relevant document for an input query on a dense representation space, have gained considerable attention for their remarkab…

cs.LG20221 cited

Factorized-FL: Agnostic Personalized Federated Learning with Kernel Factorization & Similarity Matching

Wonyong Jeong, Sung Ju Hwang

In real-world federated learning scenarios, participants could have their own personalized labels which are incompatible with those from other clients, due to using different label…

q-bio.QM202120 cited

Hit and Lead Discovery with Explorative RL and Fragment-based Molecule Generation

Soojung Yang, Doyeong Hwang, Seul Lee +2

Recently, utilizing reinforcement learning (RL) to generate molecules with desired properties has been highlighted as a promising strategy for drug design. A molecular docking prog…

cs.LG20217 cited

RetCL: A Selection-based Approach for Retrosynthesis via Contrastive Learning

Hankook Lee, Sungsoo Ahn, Seung-Woo Seo +4

Retrosynthesis, of which the goal is to find a set of reactants for synthesizing a target product, is an emerging research area of deep learning. While the existing approaches have…

cs.LG202118 cited

Edge Representation Learning with Hypergraphs

Jaehyeong Jo, Jinheon Baek, Seul Lee +3

Graph neural networks have recently achieved remarkable success in representing graph-structured data, with rapid progress in both the node embedding and graph pooling methods. Yet…