Towards Precise Prediction Uncertainty in GNNs: Refining GNNs with Topology-grouping Strategy

AAAI 2024 Towards Precise Prediction Uncertainty in GNNs: Refining GNNs with Topology-grouping Strategy  Hyunjin Seo, Kyusung Seo, Joonhyung Park, Eunho Yang  Recent advancements in graph neural networks (GNNs) have highlighted the critical need of calibrating model predicti...

Saliency Grafting: Innocuous Attribution-Guided Mixup with Calibrated Label Mixing

AAAI 2022 Saliency Grafting: Innocuous Attribution-Guided Mixup with Calibrated Label Mixing Joonhyung Park, June Yong Yang, Jinwoo Shin, Sung Ju Hwang, Eunho Yang  The Mixup scheme suggests mixing a pair of samples to create an augmented training sample and has gained considerab...

Graph Transplant: Node Saliency-Guided Graph mixup with Local Structure Preservation

AAAI 2022 Graph Transplant: Node Saliency-Guided Graph mixup with Local Structure Preservation Joonhyung Park*, Hajin Shim*, Eunho Yang (*: equal contribution)    Graph-structured datasets usually have irregular graph sizes and connectivities, rendering the use of recen...

Consistency Regularization for Adversarial Robustness

AAAI 2022 Consistency Regularization for Adversarial Robustness Jihoon Tack, Sihyun Yu, Jongheon Jeong, Minseon Kim, Sung Ju Hwang, Jinwoo Shin  Adversarial training (AT) is currently one of the most successful methods to obtain the adversarial robustness of deep neural networks....

GTA: Graph Truncated Attention for Retrosynthesis

AAAI 2021 GTA: Graph Truncated Attention for Retrosynthesis Seung-Woo Seo, You Young Song, June Yong Yang, Seohui Bae, Hankook Lee, Jinwoo Shin, Sung Ju Hwang, and Eunho Yang  Retrosynthesis is the task of predicting reactant molecules from a given product molecule and is, import...

Clinical Risk Prediction with Temporal Probabilistic Asymmetric Multi-Task Learning

AAAI 2021 Clinical Risk Prediction with Temporal Probabilistic Asymmetric Multi-Task Learning Tuan Nguyen*, Hyewon Jeong*, Eunho Yang and Sung Ju Hwang  Although recent multi-task learning methods have shown to be effective in improving the generalization of deep n...

Deep Mixed Effect Models using Gaussian Process: A Personalized and Reliable Prediction Model for Healthcare

AAAI 2020 Deep Mixed Effect Models using Gaussian Process: A Personalized and Reliable Prediction Model for Healthcare Ingyo Chung, Saehoon Kim, Juho Lee, Kwang Joon Kim, Sung Ju Hwang, Eunho Yang  We present a personalized and reliable prediction model for healthcare, which can ...

Product Quantized Translation for Fast Nearest Neighbor Search

AAAI 2018 Product Quantized Translation for Fast Nearest Neighbor SearchYoonho Hwang, Mooyeol Baek, Saehoon Kim, Bohyung Han, Hee-Kap Ahn We propose an effective filtering algorithm to eliminate nearest neighbor candidates using their distance lower bounds in nonlinear embedded spaces, con...

On the Optimal Bit Complexity of Circulant Binary Embedding

AAAI 2018 On the Optimal Bit Complexity of Circulant Binary EmbeddingSaehoon Kim, Jungtaek Kim, Seungjin Choi In this paper, to support promising empirical results of CBE, we extend the previous theoretical framework to address the optimal condition on the number of bits, achieving that CB...