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Poster
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Wed 4:30
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PAC-Bayesian Generalization Bounds for Knowledge Graph Representation Learning
Jaejun Lee · Minsung Hwang · Joyce Whang
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Poster
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Thu 2:30
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A Neural-Guided Dynamic Symbolic Network for Exploring Mathematical Expressions from Data
Wenqiang Li · Weijun Li · Lina Yu · Min Wu · Linjun Sun · Jingyi Liu · Yanjie Li · Shu Wei · Deng Yusong · Meilan Hao
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Workshop
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Sat 1:20
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Contributed: Variational Inference Failures Under Model Symmetries: Permutation Invariant Posteriors for Bayesian Neural Networks
Yoav Gelberg
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Workshop
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A Unified Approach to Feature Learning in Bayesian Neural Networks
Noa Rubin · Zohar Ringel · Inbar Seroussi · Moritz Helias
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Workshop
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Fine-Tuning with Uncertainty-Aware Priors Makes Vision and Language Foundation Models More Reliable
Tim G. J. Rudner · Xiang Pan · Yucen Li · Ravid Shwartz-Ziv · Andrew Wilson
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Poster
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Wed 4:30
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Reparameterized Importance Sampling for Robust Variational Bayesian Neural Networks
Yunfei Long · Zilin Tian · Liguo Zhang · Huosheng Xu
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Poster
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Wed 2:30
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Partially Stochastic Infinitely Deep Bayesian Neural Networks
Sergio Calvo Ordoñez · Matthieu Meunier · Francesco Piatti · Yuantao Shi
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Workshop
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EVCL: Elastic Variational Continual Learning with Weight Consolidation
Hunar Batra · Ronald Clark
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Workshop
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Function Space Diversity for Uncertainty Prediction via Repulsive Last-Layer Ensembles
Sophie Steger · Christian Knoll · Bernhard Klein · Holger Fröning · Franz Pernkopf
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Poster
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Tue 2:30
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Synergistic Integration of Coordinate Network and Tensorial Feature for Improving Neural Radiance Fields from Sparse Inputs
Mingyu Kim · Kim Jun-Seong · Se-Young Yun · Jin-Hwa Kim
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Poster
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Thu 2:30
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Parameterized Physics-informed Neural Networks for Parameterized PDEs
Woojin Cho · Minju Jo · Haksoo Lim · Kookjin Lee · Dongeun Lee · Sanghyun Hong · Noseong Park
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Poster
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Tue 4:30
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Benign Overfitting in Adversarial Training of Neural Networks
Yunjuan Wang · Kaibo Zhang · Raman Arora
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