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Poster
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Thu 11:00
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Dissecting the Failure of Invariant Learning on Graphs
Qixun Wang · Yifei Wang · Yisen Wang · Xianghua Ying
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Workshop
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Sparsely Connected Layers for Financial Tabular Data
Mohammed Abdulrahman · Yin Wang · Hui Chen
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Workshop
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Improved Depth Estimation of Bayesian Neural Networks
Bart van Erp · Bert de Vries
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Poster
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Wed 11:00
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What do Graph Neural Networks learn? Insights from Tropical Geometry
Tuan Anh Pham · Vikas Garg
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Poster
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Fri 11:00
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Learning from higher-order correlations, efficiently: hypothesis tests, random features, and neural networks
Eszter Szekely · Lorenzo Bardone · Federica Gerace · Sebastian Goldt
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Workshop
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Graph Representation of Local Environments for Learning High-Entropy Alloy Properties
Hengrui Zhang · Ruishu Huang · Jie Chen · James Rondinelli · Wei Chen
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Workshop
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How do students become teachers: A dynamical analysis for two-layer neural networks
Zhenyu Zhu · Fanghui Liu · Volkan Cevher
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Workshop
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Towards Faster Quantum Circuit Simulation Using Graph Decompositions, GNNs and Reinforcement Learning
Alexander Koziell-Pipe · Richie Yeung · Matthew Sutcliffe
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Affinity Event
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Enhancing Water Stress Classification using Drift-Aware Dynamic Neural Networks
Tejasri Nampally · Rajalakshmi pachamuthu · Balaji Banothu · Uday Desai
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Workshop
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Convolutional Hierarchical Deep Learning Neural Networks-Tensor Decomposition (C-HiDeNN-TD): a scalable surrogate modeling approach for large-scale physical systems
Jiachen Guo · Chanwook Park · Xiaoyu Xie · Zhongsheng Sang · Gregory J. Wagner · Kam Liu
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Poster
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Wed 11:00
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DASH: Warm-Starting Neural Network Training in Stationary Settings without Loss of Plasticity
Baekrok Shin · Junsoo Oh · Hanseul Cho · Chulhee Yun
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Workshop
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Task-Relevant Covariance from Manifold Capacity Theory Improves Robustness in Deep Networks
William Yang · Chi-Ning Chou · SueYeon Chung
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