 Information Bottleneck-based Causal Attention for Multi-label Medical Image RecognitionInternational Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI), 2025 |
 Recognizable Information BottleneckInternational Joint Conference on Artificial Intelligence (IJCAI), 2023 |
 R2-Trans:Fine-Grained Visual Categorization with Redundancy ReductionImage and Vision Computing (IVC), 2022 |
 Learning to Learn with Variational Information Bottleneck for Domain
GeneralizationEuropean Conference on Computer Vision (ECCV), 2020 |
 Decision-Making with Auto-Encoding Variational BayesNeural Information Processing Systems (NeurIPS), 2020 Romain Lopez Pierre Boyeau Nir Yosef Michael I. Jordan Jeffrey Regier |
 Restricting the Flow: Information Bottlenecks for AttributionInternational Conference on Learning Representations (ICLR), 2020 |
 High Frequency Component Helps Explain the Generalization of
Convolutional Neural NetworksComputer Vision and Pattern Recognition (CVPR), 2019 |
 CBAM: Convolutional Block Attention ModuleEuropean Conference on Computer Vision (ECCV), 2018 |
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 Variational Attention for Sequence-to-Sequence ModelsInternational Conference on Computational Linguistics (COLING), 2017 |
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 Very Deep Convolutional Networks for Large-Scale Image RecognitionInternational Conference on Learning Representations (ICLR), 2014 |
 Neural Machine Translation by Jointly Learning to Align and TranslateInternational Conference on Learning Representations (ICLR), 2014 |
 Deep Inside Convolutional Networks: Visualising Image Classification
Models and Saliency MapsInternational Conference on Learning Representations (ICLR), 2013 |
