Not too little, not too much: a theoretical analysis of graph (over)smoothing

von Keriven, Nicolas
Veröffentlicht in NeurIPS (36. : 2022 : New Orleans, La.; Online) 36th Conference on Neural Information Processing Systems (NeurIPS 2022 ; Volume 4 of 50 (2023)

UNIVERSAL INVARIANT AND EQUIVARIANT GRAPH NEURAL NETWORKS

von Keriven, Nicolas
Veröffentlicht in NeurIPS (33. : 2019 : Vancouver, British Columbia) 32nd Conference on Neural Information Processing Systems (NeurIPS 2019) ; Volume 9 of 20 (2020)

On the Universality of Graph Neural Networks on Large Random Graphs

von Keriven, Nicolas
Veröffentlicht in NeurIPS (35. : 2021 : Online) 35th Conference on Neural Information Processing Systems (NeurIPS 2021) ; Volume 9 of 36 (2022)

CONVERGENCE AND STABILITY OF GRAPH CONVOLUTIONAL NETWORKS ON LARGE RANDOM GRAPHS

von Keriven, Nicolas
Veröffentlicht in NeurIPS (34. : 2020 : Online) 34th Conference on Neural Information Processing Systems (NeurIPS 2020) ; Volume 26 of 27 (2021)