Moshe Eliasof

CoRR, August, 2025

Return of ChebNet: Understanding and Improving an Overlooked GNN on Long Range Tasks.

[BibT_eX]

[DOI]

Md Shahriar Rahim Siddiqui

Davide Bacciu

Kamyar Azizzadenesheli

Xiaowen Dong

Pierre Vandergheynst

CoRR, June, 2025

Graph Flow Matching: Enhancing Image Generation with Neighbor-Aware Flow Fields.

[BibT_eX]

[DOI]

CoRR, May, 2025

Improving the Effective Receptive Field of Message-Passing Neural Networks.

[BibT_eX]

[DOI]

CoRR, May, 2025

Message-Passing State-Space Models: Improving Graph Learning with Modern Sequence Modeling.

[BibT_eX]

[DOI]

CoRR, May, 2025

One-Step Offline Distillation of Diffusion-based Models via Koopman Modeling.

[BibT_eX]

[DOI]

CoRR, May, 2025

FLASH: Flexible Learning of Adaptive Sampling from History in Temporal Graph Neural Networks.

[BibT_eX]

[DOI]

Or Feldman

Krishna Sri Ipsit Mantri

Chaim Baskin

CoRR, April, 2025

Towards Efficient Training of Graph Neural Networks: A Multiscale Approach.

[BibT_eX]

[DOI]

Eshed Gal

CoRR, March, 2025

Iterative Flow Matching - Path Correction and Gradual Refinement for Enhanced Generative Modeling.

[BibT_eX]

[DOI]

Md Shahriar Rahim Siddiqui

Shadab Ahamed

Niloufar Zakariaei

CoRR, February, 2025

Towards Invariance to Node Identifiers in Graph Neural Networks.

[BibT_eX]

[DOI]

Maya Bechler-Speicher

Ran Gilad-Bachrach

Amir Globerson

CoRR, February, 2025

On the Effectiveness of Random Weights in Graph Neural Networks.

[BibT_eX]

[DOI]

Thu Bui

Bruno Ribeiro

Beatrice Bevilacqua

CoRR, February, 2025

Multiscale Training of Convolutional Neural Networks.

[BibT_eX]

[DOI]

CoRR, January, 2025

GRAMA: Adaptive Graph Autoregressive Moving Average Models.

[BibT_eX]

[DOI]

CoRR, January, 2025

Towards Graph Foundation Models: A Study on the Generalization of Positional and Structural Encodings.

[BibT_eX]

[DOI]

Sophie Fellenz

Marius Kloft

Trans. Mach. Learn. Res., 2025

Understanding and Improving Laplacian Positional Encodings for Temporal GNNs.

[BibT_eX]

[DOI]

Proceedings of the Machine Learning and Knowledge Discovery in Databases. Research Track, 2025

Estimation of single-cell and tissue perturbation effect in spatial transcriptomics via Spatial Causal Disentanglement.

[BibT_eX]

[DOI]

Sarah A. Teichmann

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

DiTASK: Multi-Task Fine-Tuning with Diffeomorphic Transformations.

[BibT_eX]

[DOI]

Krishna Sri Ipsit Mantri

Bruno Ribeiro

Chaim Baskin

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2025

On Oversquashing in Graph Neural Networks Through the Lens of Dynamical Systems.

[BibT_eX]

[DOI]

Proceedings of the AAAI-25, Sponsored by the Association for the Advancement of Artificial Intelligence, February 25, 2025

Learning Regularization for Graph Inverse Problems.

[BibT_eX]

[DOI]

Md Shahriar Rahim Siddiqui

Proceedings of the AAAI-25, Sponsored by the Association for the Advancement of Artificial Intelligence, February 25, 2025

2024

Haar Wavelet Feature Compression for Quantized Graph Convolutional Networks.

[BibT_eX]

[DOI]

Benjamin Jacob Bodner

IEEE Trans. Neural Networks Learn. Syst., April, 2024

Graph Neural Reaction Diffusion Models.

[BibT_eX]

[DOI]

SIAM J. Sci. Comput., 2024

Global-local graph neural networks for node-classification.

[BibT_eX]

[DOI]

Pattern Recognit. Lett., 2024

Towards Foundation Models on Graphs: An Analysis on Cross-Dataset Transfer of Pretrained GNNs.

[BibT_eX]

[DOI]

Thomas Gärtner

Haggai Maron

CoRR, 2024

On the Utilization of Unique Node Identifiers in Graph Neural Networks.

[BibT_eX]

[DOI]

Maya Bechler-Speicher

Ran Gilad-Bachrach

Amir Globerson

CoRR, 2024

A General Recipe for Contractive Graph Neural Networks - Technical Report.

[BibT_eX]

[DOI]

Maya Bechler-Speicher

CoRR, 2024

Celcomen: spatial causal disentanglement for single-cell and tissue perturbation modeling.

[BibT_eX]

[DOI]

Sarah A. Teichmann

CoRR, 2024

Tackling Graph Oversquashing by Global and Local Non-Dissipativity.

[BibT_eX]

[DOI]

CoRR, 2024

Graph Neural Networks for Binary Programming.

[BibT_eX]

[DOI]

CoRR, 2024

An Over Complete Deep Learning Method for Inverse Problems.

[BibT_eX]

[DOI]

CoRR, 2024

Advection Augmented Convolutional Neural Networks.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024

DiGRAF: Diffeomorphic Graph-Adaptive Activation Function.

[BibT_eX]

[DOI]

Krishna Sri Ipsit Mantri

Xinzhi Wang

Bruno Ribeiro

Beatrice Bevilacqua

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024

GRANOLA: Adaptive Normalization for Graph Neural Networks.

[BibT_eX]

[DOI]

Beatrice Bevilacqua

Haggai Maron

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024

Efficient Subgraph GNNs by Learning Effective Selection Policies.

[BibT_eX]

[DOI]

Proceedings of the Twelfth International Conference on Learning Representations, 2024

Resilient Graph Neural Networks: A Coupled Dynamical Systems Approach.

[BibT_eX]

[DOI]

Davide Murari

Ferdia Sherry

Proceedings of the ECAI 2024 - 27th European Conference on Artificial Intelligence, 19-24 October 2024, Santiago de Compostela, Spain, 2024

Every Node Counts: Improving the Training of Graph Neural Networks on Node Classification.

[BibT_eX]

[DOI]

Proceedings of the ECAI 2024 - 27th European Conference on Artificial Intelligence, 19-24 October 2024, Santiago de Compostela, Spain, 2024

On The Temporal Domain of Differential Equation Inspired Graph Neural Networks.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2024

Feature Transportation Improves Graph Neural Networks.

[BibT_eX]

[DOI]

Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023

Estimating a Potential Without the Agony of the Partition Function.

[BibT_eX]

[DOI]

Luis Tenorio

SIAM J. Math. Data Sci., December, 2023

MGIC: Multigrid-in-Channels Neural Network Architectures.

[BibT_eX]

[DOI]

SIAM J. Sci. Comput., June, 2023

Contractive Systems Improve Graph Neural Networks Against Adversarial Attacks.

[BibT_eX]

[DOI]

Davide Murari

Ferdia Sherry

CoRR, 2023

ADR-GNN: Advection-Diffusion-Reaction Graph Neural Networks.

[BibT_eX]

[DOI]

CoRR, 2023

DRIP: Deep Regularizers for Inverse Problems.

[BibT_eX]

[DOI]

CoRR, 2023

Improving Graph Neural Networks with Learnable Propagation Operators.

[BibT_eX]

[DOI]

Lars Ruthotto

Proceedings of the International Conference on Machine Learning, 2023

Graph Positional Encoding via Random Feature Propagation.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Machine Learning, 2023

2022

Mimetic Neural Networks: A Unified Framework for Protein Design and Folding.

[BibT_eX]

[DOI]

Frontiers Bioinform., 2022

ωGNNs: Deep Graph Neural Networks Enhanced by Multiple Propagation Operators.

[BibT_eX]

[DOI]

Lars Ruthotto

CoRR, 2022

Unsupervised Image Semantic Segmentation through Superpixels and Graph Neural Networks.

[BibT_eX]

[DOI]

Nir Ben Zikri

CoRR, 2022

pathGCN: Learning General Graph Spatial Operators from Paths.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Machine Learning, 2022

Rethinking Unsupervised Neural Superpixel Segmentation.

[BibT_eX]

[DOI]

Nir Ben Zikri

Proceedings of the 2022 IEEE International Conference on Image Processing, 2022

2021

Quantized convolutional neural networks through the lens of partial differential equations.

[BibT_eX]

[DOI]

CoRR, 2021

PDE-GCN: Novel Architectures for Graph Neural Networks Motivated by Partial Differential Equations.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

2020

Multimodal 3D Shape Reconstruction under Calibration Uncertainty Using Parametric Level Set Methods.

[BibT_eX]

[DOI]

Andrei Sharf

SIAM J. Imaging Sci., 2020

LeanConvNets: Low-Cost Yet Effective Convolutional Neural Networks.

[BibT_eX]

[DOI]

IEEE J. Sel. Top. Signal Process., 2020

Multigrid-in-Channels Neural Network Architectures.

[BibT_eX]

[DOI]

CoRR, 2020

DiffGCN: Graph Convolutional Networks via Differential Operators and Algebraic Multigrid Pooling.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

2019

Multi-modal 3D Shape Reconstruction Under Calibration Uncertainty using Parametric Level Set Methods.

[BibT_eX]

[DOI]

Andrei Sharf