Guido Montúfar
19 papers · 2015–2025 · 4 venues · across top CS/AI venues
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neural tangent kernel
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graph neural network
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neural network optimization
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generative model
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implicit bia
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graph pooling
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binary classification
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wavelet transform
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representation learning
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function space
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graph classification
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gaussian process
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Papers
Demystifying Topological Message-Passing with Relational Structures: A Case Study on Oversquashing in Simplicial Message-Passing
ICLR 2025
Implicit Bias of Mirror Flow for Shallow Neural Networks in Univariate Regression
ICLR 2025
On the Local Complexity of Linear Regions in Deep ReLU Networks
ICML 2025
Benign overfitting in leaky ReLU networks with moderate input dimension
NeurIPS 2024
Bounds for the smallest eigenvalue of the NTK for arbitrary spherical data of arbitrary dimension
NeurIPS 2024
Characterizing the spectrum of the NTK via a power series expansion
ICLR 2023
Critical Points and Convergence Analysis of Generative Deep Linear Networks Trained with Bures-Wasserstein Loss
ICML 2023
Expected Gradients of Maxout Networks and Consequences to Parameter Initialization
ICML 2023
FoSR: First-order spectral rewiring for addressing oversquashing in GNNs
ICLR 2023
Implicit Bias of Gradient Descent for Mean Squared Error Regression with Two-Layer Wide Neural Networks
JMLR 2023
Implicit Bias of MSE Gradient Optimization in Underparameterized Neural Networks
ICLR 2022
Learning Curves for Gaussian Process Regression with Power-Law Priors and Targets
ICLR 2022
The Geometry of Memoryless Stochastic Policy Optimization in Infinite-Horizon POMDPs
ICLR 2022
How Framelets Enhance Graph Neural Networks
ICML 2021
Haar Graph Pooling
ICML 2020
Optimization Theory for ReLU Neural Networks Trained with Normalization Layers
ICML 2020
Wasserstein of Wasserstein Loss for Learning Generative Models
ICML 2019
Discrete Restricted Boltzmann Machines
JMLR 2015
Geometry and Expressive Power of Conditional Restricted Boltzmann Machines
JMLR 2015