Improving Molecular Graph Neural Network Explainability with Orthonormalization and Induced Sparsity

11 May 2021

Papers citing "Improving Molecular Graph Neural Network Explainability with Orthonormalization and Induced Sparsity"

16 / 16 papers shown

Title
Recent advances in interpretable machine learning using structure-based protein representations L. Vecchietti Minji Lee Begench Hangeldiyev Hyunkyu Jung Hahnbeom Park Tae-Kyun Kim Meeyoung Cha Ho Min Kim AI4CE 21 1 0 26 Sep 2024
Advancements in Molecular Property Prediction: A Survey of Single and Multimodal Approaches Tanya Liyaqat T. Ahmad Chandni Saxena 32 2 0 18 Aug 2024
Graph AI in Medicine Ruth Johnson Michelle M. Li Ayush Noori Owen Queen Marinka Zitnik 21 3 0 20 Oct 2023
Encoding Time-Series Explanations through Self-Supervised Model Behavior Consistency Owen Queen Thomas Hartvigsen Teddy Koker Huan He Theodoros Tsiligkaridis Marinka Zitnik AI4TS 37 17 0 03 Jun 2023
A Survey on Explainability of Graph Neural Networks Jaykumar Kakkad Jaspal Jannu Kartik Sharma Charu C. Aggarwal Sourav Medya 28 23 0 02 Jun 2023
Streamlining models with explanations in the learning loop Francesco Lomuscio P. Bajardi Alan Perotti E. Amparore FAtt 21 0 0 15 Feb 2023
MEGAN: Multi-Explanation Graph Attention Network Jonas Teufel Luca Torresi Patrick Reiser Pascal Friederich 16 8 0 23 Nov 2022
Graph-based Molecular Representation Learning Zhichun Guo Kehan Guo B. Nan Yijun Tian Roshni G. Iyer ... Olaf Wiest Xiangliang Zhang Wei Wang Chuxu Zhang Nitesh V. Chawla AI4CE 20 60 0 08 Jul 2022
Towards Learning Self-Organized Criticality of Rydberg Atoms using Graph Neural Networks Simon Ohler Daniel Brady Winfried Lotzsch M. Fleischhauer Johannes Otterbach AI4CE 16 1 0 05 Jul 2022
Learning the Solution Operator of Boundary Value Problems using Graph Neural Networks Winfried Lotzsch Simon Ohler Johannes Otterbach AI4CE 22 18 0 28 Jun 2022
A Survey of Trustworthy Graph Learning: Reliability, Explainability, and Privacy Protection Bingzhe Wu Jintang Li Junchi Yu Yatao Bian Hengtong Zhang ... Guangyu Sun Peng Cui Zibin Zheng Zhe Liu P. Zhao OOD 25 25 0 20 May 2022
Trustworthy Graph Neural Networks: Aspects, Methods and Trends He Zhang Bang Wu Xingliang Yuan Shirui Pan Hanghang Tong Jian Pei 41 104 0 16 May 2022
Physics-Informed Graph Learning Ciyuan Peng Feng Xia Vidya Saikrishna Huan Liu PINN AI4CE 24 6 0 22 Feb 2022
Explaining, Evaluating and Enhancing Neural Networks' Learned Representations Marco Bertolini Djork-Arné Clevert F. Montanari FAtt 4 5 0 18 Feb 2022
Interpretable and Generalizable Graph Learning via Stochastic Attention Mechanism Siqi Miao Miaoyuan Liu Pan Li 14 196 0 31 Jan 2022
Graph Information Bottleneck Tailin Wu Hongyu Ren Pan Li J. Leskovec AAML 88 224 0 24 Oct 2020