agp-2023-1 - biblio

bibliografía y ligas

Semi-Supervised Classification with Graph Convolutional Networks Thomas N. Kipf, Max Welling

código: Graph Convolutional Networks in PyTorch

Hyperbolic Graph Convolutional Neural Networks, Ines Chami, Rex Ying, Christopher Ré, Jure Leskovec

código Hyperbolic Graph Convolutional Networks in PyTorch

Computational Optimal Transport Gabriel Peyré, Marco Cuturi

Código : POT: Python Optimal Transport Rémi Flamary

Generative Adversial Nets, I. Goodfellow et al.

Wasserstein GAN, M. Arjovsky et al.

Improved Training of Wasserstein GANs, I. Gulrajani et al.

Metric Reconstruction Via Optimal Transport Michał Adamaszek, Henry Adams, Florian Frick

Otras fuentes interesantes

Deep Neural Networks Motivated by Partial Differential Equations Lars Ruthotto, and Eldad Haber

A Machine Learning Framework for Solving High-Dimensional Mean Field Game and Mean Field Control Problems Lars Ruthotto , Stanley Osher , Wuchen Li , Levon Nurbekyan , and Samy Wu Fung

Automatic Differentiation, PyTorch and Graph Neural Networks Soumith Chintala

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