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Workshop
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Good Lattice Accelerates Physics-Informed Neural Networks
Takashi Matsubara · Takaharu Yaguchi
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Workshop
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Expressivity of Graph Neural Networks Through the Lens of Adversarial Robustness
Francesco Campi · Lukas Gosch · Tom Wollschläger · Yan Scholten · Stephan Günnemann
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Workshop
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A Representer Theorem for Vector-Valued Neural Networks: Insights on Weight Decay Training and Widths of Deep Neural Networks
Joseph Shenouda · Rahul Parhi · Kangwook Lee · Robert Nowak
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Workshop
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Fri 14:10
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Neural Networks Are Graphs! Graph Neural Networks for Equivariant Processing of Neural Networks
David Zhang · Miltiadis (Miltos) Kofinas · Yan Zhang · Yunlu Chen · Gertjan Burghouts · Cees Snoek
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Workshop
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A Simple and Yet Fairly Effective Defense for Graph Neural Networks
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Workshop
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A Simple and Yet Fairly Effective Defense for Graph Neural Networks
Sofiane ENNADIR · Yassine Abbahaddou · Michalis Vazirgiannis · Henrik Boström
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Workshop
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HiGen: Hierarchical Graph Generative Networks
Mahdi Karami
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Workshop
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Fri 16:50
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Breaking the Curse of Depth in Graph Convolutional Networks via Refined Initialization Strategy
Senmiao Wang
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Workshop
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DNArch: Learning Convolutional Neural Architectures by Backpropagation
David Romero · Neil Zeghidour
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Poster
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Wed 17:00
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All in a Row: Compressed Convolution Networks for Graphs
Junshu Sun · Shuhui Wang · XINZHE HAN · Zhe Xue · Qingming Huang
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Affinity Workshop
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Mon 19:15
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Expanded Convolutional Network for Tabular Data
edson luque
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Workshop
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Fri 19:00
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Equivariant Representation Learning with Equivariant Convolutional Kernel Networks
Soutrik Roy Chowdhury · Johan Suykens
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