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Beomsu Kim
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Why are Saliency Maps Noisy? Cause of and Solution to Noisy Saliency Maps
B Kim, J Seo, SH Jeon, J Koo, J Choe, T Jeon
ICCV 2019 Workshop on Interpreting and Explaining Visual Artificial …, 2019
572019
Bridging Adversarial Robustness and Gradient Interpretability
B Kim, J Seo, T Jeon
ICLR 2019 Workshop on Safe Machine Learning: Specification, Robustness, and …, 2019
402019
Noise-adding Methods of Saliency Map as Series of Higher Order Partial Derivative
J Seo, J Choe, J Koo, S Jeon, B Kim, T Jeon
ICML 2018 Workshop on Human Interpretability in Machine Learning (WHI@ICML18), 2018
242018
Minimizing Trajectory Curvature of ODE-based Generative Models
S Lee, B Kim, JC Ye
ICML 2023, 2023
152023
Revisiting Classical Bagging with Modern Transfer Learning for On-the-fly Disaster Damage Detector
J Seo, S Lee, B Kim, T Jeon
NeurIPS 2019 Workshop on Artificial Intelligence for Humanitarian Assistance …, 2019
82019
Unpaired Image-to-Image Translation via Neural Schrödinger Bridge
B Kim*, G Kwon*, K Kim, JC Ye
ICLR 2024, 2024
72024
Denoising MCMC for Accelerating Diffusion-Based Generative Models
B Kim, JC Ye
ICML 2023 Oral Paper, 2023
52023
Energy-Based Cross Attention for Bayesian Context Update in Text-to-Image Diffusion Models
GY Park*, J Kim*, B Kim, SW Lee, JC Ye
NeurIPS 2023, 2023
12023
Energy-Based Contrastive Learning of Visual Representations
B Kim, JC Ye
NeurIPS 2022 Oral Paper, 2022
12022
Semi-Implicit Hybrid Gradient Methods with Application to Adversarial Robustness
B Kim, J Seo
AISTATS 2022, 2022
2022
Mitigating Out-of-Distribution Data Density Overestimation in Energy-Based Models
B Kim, JC Ye
arXiv preprint arXiv:2205.14817, 2022
2022
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Articles 1–11