Building Knowledge That’s Truly Implementable Tomorrow

ICML 2020

Adversarial Neural Pruning with Latent Vulnerability Suppression

Divyam Madaan, Jinwoo Shin, Sung Ju Hwang

Read More
View Publication

ICML 2020

Self-supervised Label Augmentation via Input Transformations

Hankook Lee, Sung Ju Hwang, Jinwoo Shin

Read More
View Publication

ICML 2020

Cost-effective Interactive Attention Learning with Neural Attention Processes

Jay Heo, Junhyeon Park, Hyewon Jeong, Kwang Joon Kim, Juho Lee, Eunho Yang, Sung Ju Hwang

Read More
View Publication

ICML 2020 Workshop on Uncertainty and Robustness in Deep Learning

A benchmark study on reliable molecular supervised learning via Bayesian learning

Doyeong Hwang, Grace Lee, Hanseok Jo, Seyoul Yoon, Seongok Ryu

Read More
View Publication

ICLR 2020

Why Not to Use Zero Imputation? Correcting Sparsity Bias in Training Neural Networks

Joonyoung Yi, Juhyuk Lee, Kwang Joon Kim, Sung Ju Hwang, Eunho Yang

Read More
View Publication

ICLR 2020

Meta Dropout: Learning to Perturb Latent Features for Generalization

Hae Beom Lee, Taewook Nam, Eunho Yang, Sung Ju Hwang

Read More
View Publication

ICLR 2020

Scalable and Order-robust Continual Learning with Additive Parameter Decomposition

Jaehong Yoon, Saehoon Kim, Eunho Yang and Sung Ju Hwang

Read More
View Publication

ICLR 2020

Learning to Balance: Bayesian Meta-Learning for Imbalanced and Out-of-distribution Tasks

Hae Beom Lee, Hayeon Lee, Donghyun Na, Saehoon Kim, Minseop Park, Eunho Yang, Sung Ju Hwang

Read More
View Publication

Ingyo Chung, Saehoon Kim, Juho Lee, Kwang Joon Kim, Sung Ju Hwang, Eunho Yang

Read More
View Publication

NeurIPS 2019 Workshop on Bayesian Deep Learning

Deep Gaussian Processes for Weakly Supervised Learning: Tumor Mutation Burden (TMB) Prediction

Sunho Park, Hongming Xu, Tae Hyun Hwang, Saehoon Kim

Read More
View Publication