25 citations · 25 across the 2 of their papers we have counts for
4 papers
Information-Theoretic Bias Reduction via Causal View of Spurious Correlation
Seonguk Seo, Joon-Young Lee, Bohyung Han
We propose an information-theoretic bias measurement technique through a causal interpretation of spurious correlation, which is effective to identify the feature-level algorithmic…
Learning to Optimize Domain Specific Normalization for Domain Generalization
Seonguk Seo, Yumin Suh, Dongwan Kim +3
We propose a simple but effective multi-source domain generalization technique based on deep neural networks by incorporating optimized normalization layers that are specific to in…
Domain-Specific Batch Normalization for Unsupervised Domain Adaptation
Woong-Gi Chang, Tackgeun You, Seonguk Seo +2
We propose a novel unsupervised domain adaptation framework based on domain-specific batch normalization in deep neural networks. We aim to adapt to both domains by specializing ba…
Learning for Single-Shot Confidence Calibration in Deep Neural Networks through Stochastic Inferences
Seonguk Seo, Paul Hongsuck Seo, Bohyung Han
We propose a generic framework to calibrate accuracy and confidence of a prediction in deep neural networks through stochastic inferences. We interpret stochastic regularization us…