D. Beaini

发表

Long Range Graph Benchmark

Vijay Prakash Dwivedi, Guy Wolf, A. Luu, 2022, 2206.08164.

Recipe for a General, Powerful, Scalable Graph Transformer

Vijay Prakash Dwivedi, Ladislav Rampášek, Guy Wolf, 2022, ArXiv.

3D Infomax improves GNNs for Molecular Property Prediction

P. Lio’, Christian Dallago, Christian Dallago, 2021, ICML.

Rethinking Graph Transformers with Spectral Attention pdf

Dominique Beaini, Prudencio Tossou, Devin Kreuzer, 2021, NeurIPS.

Recipe for a General, Powerful, Scalable Graph Transformer

Vijay Prakash Dwivedi, Ladislav Rampášek, Guy Wolf, 2022, ArXiv.

Deep green function convolution for improving saliency in convolutional neural networks

S. Achiche, M. Raison, D. Beaini, 2019, Vis. Comput..

Deep green function convolution for improving saliency in convolutional neural networks

S. Achiche, M. Raison, D. Beaini, 2020, The Visual Computer.

Recipe for a General, Powerful, Scalable Graph Transformer

Vijay Prakash Dwivedi, Ladislav Rampášek, Guy Wolf, 2022, NeurIPS.

Directional Graph Networks

Dominique Beaini, William L. Hamilton, Pietro Lio, 2020, ICML.

DIRECTIONAL GRAPH NETWORKS ANISOTROPIC AGGREGATION IN GRAPH NEURAL NETWORKS VIA DIRECTIONAL VECTOR FIELDS

D. Beaini, Saro Passaro, 2021 .

Peripheral N‐methyl‐d‐aspartate receptors contribute to mechanical hypersensitivity in a rat model of inflammatory temporomandibular joint pain

B. Sessle, J. Ivanusic, E. Jennings, 2011, European journal of pain.

GPS++: Reviving the Art of Message Passing for Molecular Property Prediction

A. Fitzgibbon, Ladislav Rampášek, Dominic Masters, 2023, ArXiv.

GPS++: An Optimised Hybrid MPNN/Transformer for Molecular Property Prediction

Ladislav Rampášek, Dominic Masters, D. Beker, 2022, ArXiv.

Principal Neighbourhood Aggregation for Graph Nets pdf

Dominique Beaini, Pietro Liò, Petar Velickovic, 2020, NeurIPS.

Task-Agnostic Graph Neural Network Evaluation via Adversarial Collaboration

Hannes Stärk, D. Beaini, Yiren Zhao, 2023, ArXiv.

Long Range Graph Benchmark

Vijay Prakash Dwivedi, Ladislav Rampášek, Guy Wolf, 2022, NeurIPS.

Towards Interpretable Sparse Graph Representation Learning with Laplacian Pooling pdf

Emmanuel Noutahi, Julien Horwood, Dominique Beani, 2019, ArXiv.

Image-based truss recognition for density-based topology optimization approach

Sofiane Achiche, Dominique Beaini, Aurelian Vadean, 2018, Structural and Multidisciplinary Optimization.

Image-based truss recognition for density-based topology optimization approach

S. Achiche, A. Vadean, D. Beaini, 2018, Structural And Multidisciplinary Optimization.

Fast scene analysis using vision and artificial intelligence for object prehension by an assistive robot

Maxime Raison, Dominique Beaini, Sofiane Achiche, 2017, Eng. Appl. Artif. Intell..

Improving Convolutional Neural Networks Via Conservative Field Regularisation and Integration pdf

Dominique Beaini, Sofiane Achiche, Maxime Raison, 2020, ArXiv.

Saliency Enhancement using Gradient Domain Edges Merging pdf

Dominique Beaini, Sofiane Achiche, Maxime Raison, 2020, ArXiv.

GPS++: Reviving the Art of Message Passing for Molecular Property Prediction

A. Fitzgibbon, Ladislav Rampášek, Dominic Masters, 2023, ArXiv.

Graph Positional and Structural Encoder

Guy Wolf, Renming Liu, Ladislav Ramp'avsek, 2023, ArXiv.

Fast and Optimal Laplacian Solver for Gradient-Domain Image Editing using Green Function Convolution pdf

Maxime Raison, Dominique Beaini, Sofiane Achiche, 2019, ArXiv.

Deep green function convolution for improving saliency in convolutional neural networks

S. Achiche, M. Raison, D. Beaini, 2019, The Visual Computer.

Computing the Spatial Probability of Inclusion inside Partial Contours for Computer Vision Applications pdf

Sofiane Achiche, Maxime Raison, Dominique Beaini, 2018, ArXiv.

Towards Foundational Models for Molecular Learning on Large-Scale Multi-Task Datasets

Jama Hussein Mohamud, M. Ravanelli, Reihaneh Rabbany, 2023, ICLR.

Role of Structural and Conformational Diversity for Machine Learning Potentials

Prudencio Tossou, D. Beaini, Hadrien Mary, 2023, ArXiv.