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Oral
Thu 8:00 Going beyond persistent homology using persistent homology
Johanna Immonen · Amauri Souza · Vikas Garg
Workshop
Connectivity Optimized Nested Line Graph Networks for Crystal Structures
Robin Ruff · Patrick Reiser · Jan Stühmer · Pascal Friederich
Workshop
Fri 9:10 Message Passing Neural Network for Predicting Dipole Moment Dependent Core Electron Excitation Spectra
Kiyou Shibata · Teruyasu Mizoguchi
Workshop
Fri 14:40 EGraFFBench: Evaluation of Equivariant Graph Neural Network Force Fields for Atomistic Simulations
Vaibhav Bihani · UTKARSH PRATIUSH · Sajid Mannan · Tao Du · Zhimin Chen · Santiago Miret · Matthieu Micoulaut · Morten Smedskjaer · Sayan Ranu · N M Anoop Krishnan
Workshop
AnisoGNN: physics-informed graph neural networks that generalize to anisotropic properties of polycrystals
Guangyu Hu · Marat Latypov
Workshop
MHG-GNN: Combination of Molecular Hypergraph Grammar with Graph Neural Network
Akihiro Kishimoto · Hiroshi Kajino · Hirose Masataka · Junta Fuchiwaki · Indra Priyadarsini S · Lisa Hamada · Hajime Shinohara · Daiju Nakano · Seiji Takeda
Workshop
Accelerated Modelling of Interfaces for Electronic Devices using Graph Neural Networks
Pratik Brahma · Krishnakumar Bhattaram · Sayeef Salahuddin
Workshop
Fri 7:50 Investigating extrapolation and low-data challenges via contrastive learning of chemical compositions
Federico Ottomano · Giovanni De Felice · Rahul Savani · Vladimir Gusev · Matthew Rosseinsky
Workshop
BroGNet: Momentum-Conserving Graph Neural Stochastic Differential Equation for Learning Brownian Dynamics
Suresh Bishnoi · Jayadeva Dr · Sayan Ranu · N M Anoop Krishnan
Workshop
Predicting COVID-19 pandemic by spatio-temporal graph neural networks: A New Zealand's study
Bach Nguyen · Truong Son Hy · Long Tran-Thanh · Nhung Nghiem
Affinity Workshop
Explaining Drug Repositioning: A Case-Based Reasoning Graph Neural Network Approach
Adriana Carolina Gonzalez Cavazos
Workshop
Graph Neural Networks Go Forward-Forward
Daniele Paliotta · Mathieu Alain · Bálint Máté · François Fleuret