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Poster
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Thu 13:30
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What Can Be Learnt With Wide Convolutional Neural Networks?
Francesco Cagnetta · Alessandro Favero · Matthieu Wyart
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Poster
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Tue 17:00
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From Relational Pooling to Subgraph GNNs: A Universal Framework for More Expressive Graph Neural Networks
Cai Zhou · Xiyuan Wang · Muhan Zhang
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Poster
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Wed 17:00
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Efficient Learning of Mesh-Based Physical Simulation with Bi-Stride Multi-Scale Graph Neural Network
Yadi Cao · Menglei Chai · Minchen Li · Chenfanfu Jiang
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Poster
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Wed 17:00
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Tight Certification of Adversarially Trained Neural Networks via Nonconvex Low-Rank Semidefinite Relaxations
Hong-Ming Chiu · Richard Zhang
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Poster
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Wed 17:00
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Graph Generative Model for Benchmarking Graph Neural Networks
Minji Yoon · Yue Wu · John Palowitch · Bryan Perozzi · Ruslan Salakhutdinov
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Poster
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Wed 14:00
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The Acquisition of Physical Knowledge in Generative Neural Networks
Luca M. Schulze Buschoff · Eric Schulz · Marcel Binz
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Poster
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Tue 17:00
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Gradient-based Wang--Landau Algorithm: A Novel Sampler for Output Distribution of Neural Networks over the Input Space
Weitang Liu · Yi-Zhuang You · Ying Wai Li · Jingbo Shang
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Poster
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Tue 14:00
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Graph Neural Networks with Learnable and Optimal Polynomial Bases
Yuhe Guo · Zhewei Wei
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Poster
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Tue 14:00
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Masked Bayesian Neural Networks : Theoretical Guarantee and its Posterior Inference
Insung Kong · Dongyoon Yang · Jongjin Lee · Ilsang Ohn · GYUSEUNG BAEK · Yongdai Kim
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Poster
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Thu 16:30
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Do Not Train It: A Linear Neural Architecture Search of Graph Neural Networks
Peng XU · Lin Zhang · Xuanzhou Liu · Jiaqi Sun · Yue Zhao · Haiqin Yang · Bei Yu
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Poster
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Wed 14:00
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H-Likelihood Approach to Deep Neural Networks with Temporal-Spatial Random Effects for High-Cardinality Categorical Features
Hangbin Lee · Youngjo Lee
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Poster
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Thu 16:30
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ED-Batch: Efficient Automatic Batching of Dynamic Neural Networks via Learned Finite State Machines
Siyuan Chen · Pratik Fegade · Tianqi Chen · Phillip Gibbons · Todd Mowry
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