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Poster
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Wed 14:00
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The Neural Covariance SDE: Shaped Infinite Depth-and-Width Networks at Initialization
Mufan Li · Mihai Nica · Dan Roy
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Poster
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Thu 9:00
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Bidirectional Learning for Offline Infinite-width Model-based Optimization
Can Chen · Yingxueff Zhang · Jie Fu · Xue (Steve) Liu · Mark Coates
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Workshop
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An Empirical Analysis of the Advantages of Finite vs.~Infinite Width Bayesian Neural Networks
Jiayu Yao · Yaniv Yacoby · Beau Coker · Weiwei Pan · Finale Doshi-Velez
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Workshop
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An Empirical Analysis of the Advantages of Finite v.s. Infinite Width Bayesian Neural Networks
Jiayu Yao · Yaniv Yacoby · Beau Coker · Weiwei Pan · Finale Doshi-Velez
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Poster
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Wed 14:00
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Self-Consistent Dynamical Field Theory of Kernel Evolution in Wide Neural Networks
Blake Bordelon · Cengiz Pehlevan
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Poster
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Thu 9:00
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On global convergence of ResNets: From finite to infinite width using linear parameterization
Raphaël Barboni · Gabriel Peyré · Francois-Xavier Vialard
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Poster
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Tue 9:00
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Depth is More Powerful than Width with Prediction Concatenation in Deep Forest
Shen-Huan Lyu · Yi-Xiao He · Zhi-Hua Zhou
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Poster
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Wed 14:00
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Neural Network Architecture Beyond Width and Depth
Shijun Zhang · Zuowei Shen · Haizhao Yang
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Poster
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Empirical Phase Diagram for Three-layer Neural Networks with Infinite Width
Hanxu Zhou · Zhou Qixuan · Zhenyuan Jin · Tao Luo · Yaoyu Zhang · Zhi-Qin Xu
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Poster
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Thu 9:00
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Robustness in deep learning: The good (width), the bad (depth), and the ugly (initialization)
Zhenyu Zhu · Fanghui Liu · Grigorios Chrysos · Volkan Cevher
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Poster
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Wed 9:00
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Free Probability for predicting the performance of feed-forward fully connected neural networks
Reda CHHAIBI · Tariq Daouda · Ezechiel Kahn
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