Predicting commercially available antiviral drugs that may act on the novel coronavirus (SARS-CoV-2) through a drug-target interaction deep learning model von Beck, Bo Ram, Shin, Bonggun, Choi, Yoonjung, Park, Sungsoo, Kang, Keunsoo

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Turbocharging protein binding site prediction with geometric attention, inter-resolution transfer learning, and homology-based augmentation von Lee, Daeseok, Hwang, Wonjun, Byun, Jeunghyun, Shin, Bonggun

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Target-Centered Drug Repurposing Predictions of Human Angiotensin-Converting Enzyme 2 (ACE2) and Transmembrane Protease Serine Subtype 2 (TMPRSS2) Interacting Approved Drugs for Co... von Choi, Yoonjung, Shin, Bonggun, Kang, Keunsoo, Park, Sungsoo, Beck, Bo Ram

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Cascaded Wx: A Novel Prognosis-Related Feature Selection Framework in Human Lung Adenocarcinoma Transcriptomes von Shin, Bonggun, Park, Sungsoo, Hong, Ji Hyung, An, Ho Jung, Chun, Sang Hoon, Kang, Kilsoo, Ahn, Young-Ho, Ko, Yoon Ho, Kang, Keunsoo

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Abstract 35: Molecular optimization of phase III trial failed anticancer drugs using target affinity and toxicity-centered multiple properties reinforcement learning von Park, Sungsoo, Ko, Yoon Ho, Lee, Bora, Shin, Bonggun, Beck, Bo Ram

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Wx: a neural network-based feature selection algorithm for transcriptomic data von Park, Sungsoo, Shin, Bonggun, Sang Shim, Won, Choi, Yoonjung, Kang, Kilsoo, Kang, Keunsoo

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Learning From Drift: Federated Learning on Non-IID Data via Drift Regularization von Kim, Yeachan, Shin, Bonggun

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SMAT: An Attention-Based Deep Learning Solution to the Automation of Schema Matching von Zhang, Jing, Shin, Bonggun, Choi, Jinho D., Ho, Joyce C.

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In Defense of Core-set: A Density-aware Core-set Selection for Active Learning von Kim, Yeachan, Shin, Bonggun

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Improving evidential deep learning via multi-task learning von Oh, Dongpin, Shin, Bonggun

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An Interpretable Framework for Drug-Target Interaction with Gated Cross Attention von Kim, Yeachan, Shin, Bonggun

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Method for predict affinity between drug and target substance von Kim, Yeachan, Shin, Bonggun

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Method For Predict Affinity Between Drug And Target Substance von SHIN, Bonggun, KIM, Yeachan

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Method For Data Augmentation Related To Target Protein von SHIN, Bonggun, LEE, Daeseok

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Method Of Training Local Neural Network Model For Federated Learning von SHIN, Bonggun, KIM, Yeachan

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Boosting Convolutional Neural Networks' Protein Binding Site Prediction Capacity Using SE(3)-invariant transformers, Transfer Learning and Homology-based Augmentation von Lee, Daeseok, Byun, Jeunghyun, Shin, Bonggun

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Learning From Drift: Federated Learning on Non-IID Data via Drift Regularization von Kim, Yeachan, Shin, Bonggun

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Pattern-preserving-based motion imitation for robots von Bonggun Shin, Sungho Jo

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In Defense of Core-set: A Density-aware Core-set Selection for Active Learning von Kim, Yeachan, Shin, Bonggun

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Phase-shifted Adversarial Training von Kim, Yeachan, Kim, Seongyeon, Seo, Ihyeok, Shin, Bonggun

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