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Affinity Workshop
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Model Averaging to Learn Bayesian Network Structures with Non-Linear Structured Representations
Charupriya Sharma
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Poster
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Wed 9:00
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Understanding Non-linearity in Graph Neural Networks from the Bayesian-Inference Perspective
Rongzhe Wei · Haoteng YIN · Junteng Jia · Austin Benson · Pan Li
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Poster
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Tue 14:00
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On the Effective Number of Linear Regions in Shallow Univariate ReLU Networks: Convergence Guarantees and Implicit Bias
Itay Safran · Gal Vardi · Jason Lee
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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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Workshop
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Evaluating Error Bound for Physics-Informed Neural Networks on Linear Dynamical Systems
Shuheng Liu · Xiyue Huang · Pavlos Protopapas
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Poster
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Tue 9:00
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Understanding Deep Contrastive Learning via Coordinate-wise Optimization
Yuandong Tian
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Poster
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Thu 9:00
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Improved Bounds on Neural Complexity for Representing Piecewise Linear Functions
Kuan-Lin Chen · Harinath Garudadri · Bhaskar D Rao
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Poster
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Tue 9:00
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Exact learning dynamics of deep linear networks with prior knowledge
Lukas Braun · Clémentine Dominé · James Fitzgerald · Andrew Saxe
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Poster
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Wed 9:00
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Globally Gated Deep Linear Networks
Qianyi Li · Haim Sompolinsky
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Poster
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Wed 9:00
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Cost-efficient Gaussian tensor network embeddings for tensor-structured inputs
Linjian Ma · Edgar Solomonik
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Poster
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Wed 14:00
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The alignment property of SGD noise and how it helps select flat minima: A stability analysis
Lei Wu · Mingze Wang · Weijie Su
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Poster
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Tue 14:00
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Learning dynamics of deep linear networks with multiple pathways
Jianghong Shi · Eric Shea-Brown · Michael Buice
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