15 Results

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