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Workshop
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Empirically Validating Conformal Prediction on Modern Vision Architectures Under Distribution Shift and Long-tailed Data
Kevin Kasa · Graham Taylor
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Workshop
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Towards Understanding Feature Learning in Out-of-Distribution Generalization
Yongqiang Chen · Wei Huang · Kaiwen Zhou · Yatao Bian · Bo Han · James Cheng
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Poster
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Tue 17:00
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Hybrid Energy Based Model in the Feature Space for Out-of-Distribution Detection
Marc Lafon · Elias Ramzi · Clément Rambour · Nicolas THOME
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Poster
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Tue 17:00
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Feed Two Birds with One Scone: Exploiting Wild Data for Both Out-of-Distribution Generalization and Detection
Haoyue Bai · Gregory Canal · Xuefeng Du · Jeongyeol Kwon · Robert Nowak · Sharon Li
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Workshop
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Morse Neural Networks for Uncertainty Quantification
Benoit Dherin · Huiyi Hu · JIE REN · Michael Dusenberry · Balaji Lakshminarayanan
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Poster
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Thu 13:30
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Model Ratatouille: Recycling Diverse Models for Out-of-Distribution Generalization
Alexandre Rame · Kartik Ahuja · Jianyu Zhang · Matthieu Cord · Leon Bottou · David Lopez-Paz
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Poster
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Wed 17:00
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Unleashing Mask: Explore the Intrinsic Out-of-Distribution Detection Capability
Jianing Zhu · Hengzhuang Li · Jiangchao Yao · Tongliang Liu · Jianliang Xu · Bo Han
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Workshop
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A Cosine Similarity-based Method for Out-of-Distribution Detection
Ngoc Hieu Nguyen · Nguyen Hung-Quang · The-Anh Ta · Thanh Nguyen-Tang · Khoa Doan · Hoang Thanh-Tung
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Workshop
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Proximal Compositional Optimization for Distributionally Robust Learning
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Workshop
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Nonlinear Wasserstein Distributionally Robust Optimal Control
Zhengang Zhong · Jia-Jie Zhu
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Poster
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Thu 16:30
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Label Distributionally Robust Losses for Multi-class Classification: Consistency, Robustness and Adaptivity
Dixian Zhu · Yiming Ying · Tianbao Yang
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Workshop
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Sat 13:45
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Jia-Jie Zhu: Duality from Gradient Flow Force-Balance to Distributionally Robust Learning
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