946 citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- Seoul National UniversityKR77 papers
- Seoul National University of EducationKR23 papers
- Seoul National University of Science and TechnologyKR10 papers
- Sungkyunkwan UniversityKR6 papers
- The Seoul InstituteKR6 papers
- Centre National de la Recherche ScientifiqueFR5 papers
- Stanford UniversityUS5 papers
- Chung-Ang UniversityKR4 papers
- Korea Institute for Advanced StudyKR4 papers
- Columbia UniversityUS3 papers
- Institute for Basic ScienceKR3 papers
- Korea UniversityKR3 papers
9 papers · 1 filter
IgPose: A Generative Data-Augmented Pipeline for Robust Immunoglobulin-Antigen Binding Prediction
Tien-Cuong Bui, Injae Chung, Wonjun Lee +2
Predicting immunoglobulin-antigen (Ig-Ag) binding remains a significant challenge due to the paucity of experimentally-resolved complexes and the limited accuracy of de novo Ig str…
Understanding Clinical Decision-Making in Traditional East Asian Medicine through Dimensionality Reduction: An Empirical Investigation
Hyojin Bae, Bongsu Kang, Chang-Eop Kim
This study examines the clinical decision-making processes in Traditional East Asian Medicine (TEAM) by reinterpreting pattern identification (PI) through the lens of dimensionalit…
Data Context Adaptation for Accurate Recommendation with Additional Information
Hyunsik Jeon, Bonhun Koo, U Kang
Given a sparse rating matrix and an auxiliary matrix of users or items, how can we accurately predict missing ratings considering different data contexts of entities? Many previous…
SARN: Relational Reasoning through Sequential Attention
Jinwon An, Sungwon Lyu, Sungzoon Cho
This paper proposes an attention module augmented relational network called SARN(Sequential Attention Relational Network) that can carry out relational reasoning by extracting refe…
Instance-based entropy fuzzy support vector machine for imbalanced data
Poongjin Cho, Minhyuk Lee, Woojin Chang
Imbalanced classification has been a major challenge for machine learning because many standard classifiers mainly focus on balanced datasets and tend to have biased results toward…
Energy-Efficient Inference Accelerator for Memory-Augmented Neural Networks on an FPGA
Seongsik Park, Jaehee Jang, Seijoon Kim +1
Memory-augmented neural networks (MANNs) are designed for question-answering tasks. It is difficult to run a MANN effectively on accelerators designed for other neural networks (NN…
DNA Steganalysis Using Deep Recurrent Neural Networks
Ho Bae, Byunghan Lee, Sunyoung Kwon +1
Recent advances in next-generation sequencing technologies have facilitated the use of deoxyribonucleic acid (DNA) as a novel covert channels in steganography. There are various me…
An Efficient Approach to Boosting Performance of Deep Spiking Network Training
Seongsik Park, Sang-gil Lee, Hyunha Nam +1
Nowadays deep learning is dominating the field of machine learning with state-of-the-art performance in various application areas. Recently, spiking neural networks (SNNs) have bee…
Neural Universal Discrete Denoiser
Taesup Moon, Seonwoo Min, Byunghan Lee +1
We present a new framework of applying deep neural networks (DNN) to devise a universal discrete denoiser. Unlike other approaches that utilize supervised learning for denoising, w…