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Workshop
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A Curriculum-Training-Based Strategy for Distributing Collocation Points during Physics-Informed Neural Network Training
Marcus Münzer · Christopher Bard
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Workshop
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Shift-Robust Node Classification via Graph Clustering Co-training
Qi Zhu · Chao Zhang · Chanyoung Park · Carl Yang · Jiawei Han
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Poster
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Tue 9:00
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UQGAN: A Unified Model for Uncertainty Quantification of Deep Classifiers trained via Conditional GANs
Philipp Oberdiek · Gernot Fink · Matthias Rottmann
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Poster
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Improving Out-of-Distribution Generalization by Adversarial Training with Structured Priors
Qixun Wang · Yifei Wang · Hong Zhu · Yisen Wang
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Poster
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Tue 9:00
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In What Ways Are Deep Neural Networks Invariant and How Should We Measure This?
Henry Kvinge · Tegan Emerson · Grayson Jorgenson · Scott Vasquez · Tim Doster · Jesse Lew
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Poster
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Tue 9:00
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Transferring Fairness under Distribution Shifts via Fair Consistency Regularization
Bang An · Zora Che · Mucong Ding · Furong Huang
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Workshop
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Consistent Training via Energy-Based GFlowNets for Modeling Discrete Joint Distributions
Chanakya Ekbote · Moksh Jain · Payel Das · Yoshua Bengio
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Poster
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Thu 9:00
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A Communication-Efficient Distributed Gradient Clipping Algorithm for Training Deep Neural Networks
Mingrui Liu · Zhenxun Zhuang · Yunwen Lei · Chunyang Liao
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Workshop
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Inferring Class Label Distribution of Training Data from Classifiers: An Accuracy-Augmented Meta-Classifier Attack
Raksha Ramakrishna · György Dán
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Poster
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Wed 9:00
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Beyond spectral gap: the role of the topology in decentralized learning
Thijs Vogels · Hadrien Hendrikx · Martin Jaggi
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Poster
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Thu 14:00
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Generative Visual Prompt: Unifying Distributional Control of Pre-Trained Generative Models
Chen Henry Wu · Saman Motamed · Shaunak Srivastava · Fernando D De la Torre
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Workshop
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An Empirical Study on Distribution Shift Robustness From the Perspective of Pre-Training and Data Augmentation
Ziquan Liu · Yi Xu · Yuanhong Xu · Qi Qian · Hao Li · Rong Jin · Xiangyang Ji · Antoni Chan
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