26 Results

Affinity Workshop		Model Averaging to Learn Bayesian Network Structures with Non-Linear Structured Representations Charupriya Sharma
Poster	Wed 9:00	Understanding Non-linearity in Graph Neural Networks from the Bayesian-Inference Perspective Rongzhe Wei · Haoteng YIN · Junteng Jia · Austin Benson · Pan Li
Poster	Thu 9:00	On global convergence of ResNets: From finite to infinite width using linear parameterization Raphaël Barboni · Gabriel Peyré · Francois-Xavier Vialard
Poster	Tue 14:00	On the Effective Number of Linear Regions in Shallow Univariate ReLU Networks: Convergence Guarantees and Implicit Bias Itay Safran · Gal Vardi · Jason Lee
Poster	Tue 9:00	Understanding Deep Contrastive Learning via Coordinate-wise Optimization Yuandong Tian
Workshop		Evaluating Error Bound for Physics-Informed Neural Networks on Linear Dynamical Systems Shuheng Liu · Xiyue Huang · Pavlos Protopapas
Poster	Tue 9:00	Exact learning dynamics of deep linear networks with prior knowledge Lukas Braun · Clémentine Dominé · James Fitzgerald · Andrew Saxe
Poster	Thu 9:00	Improved Bounds on Neural Complexity for Representing Piecewise Linear Functions Kuan-Lin Chen · Harinath Garudadri · Bhaskar D Rao
Poster	Wed 9:00	Globally Gated Deep Linear Networks Qianyi Li · Haim Sompolinsky
Poster	Wed 9:00	Cost-efficient Gaussian tensor network embeddings for tensor-structured inputs Linjian Ma · Edgar Solomonik
Poster	Thu 9:00	Exact Solutions of a Deep Linear Network Liu Ziyin · Botao Li · Xiangming Meng
Poster	Tue 14:00	Learning dynamics of deep linear networks with multiple pathways Jianghong Shi · Eric Shea-Brown · Michael Buice