Accelerating Molecular Graph Neural Networks via Knowledge Distillation

26 June 2023

Papers citing "Accelerating Molecular Graph Neural Networks via Knowledge Distillation"

7 / 7 papers shown

Title
Towards Faster and More Compact Foundation Models for Molecular Property Prediction Yasir Ghunaim Andrés Villa Gergo Ignacz Gyorgy Szekely Motasem Alfarra Bernard Ghanem AI4CE 90 0 0 28 Apr 2025
Spherical Channels for Modeling Atomic Interactions C. L. Zitnick Abhishek Das Adeesh Kolluru Janice Lan Muhammed Shuaibi Anuroop Sriram Zachary W. Ulissi Brandon M. Wood 79 58 0 29 Jun 2022
Distilling Knowledge via Knowledge Review Pengguang Chen Shu-Lin Liu Hengshuang Zhao Jiaya Jia 149 422 0 19 Apr 2021
E(3)-Equivariant Graph Neural Networks for Data-Efficient and Accurate Interatomic Potentials Simon L. Batzner Albert Musaelian Lixin Sun Mario Geiger J. Mailoa M. Kornbluth N. Molinari Tess E. Smidt Boris Kozinsky 206 1,240 0 08 Jan 2021
Pushing the Limits of Semi-Supervised Learning for Automatic Speech Recognition Yu Zhang James Qin Daniel S. Park Wei Han Chung-Cheng Chiu Ruoming Pang Quoc V. Le Yonghui Wu VLM SSL 146 308 0 20 Oct 2020
The Open Catalyst 2020 (OC20) Dataset and Community Challenges L. Chanussot Abhishek Das Siddharth Goyal Thibaut Lavril Muhammed Shuaibi ... Brandon M. Wood Junwoong Yoon Devi Parikh C. L. Zitnick Zachary W. Ulissi 232 503 0 20 Oct 2020
Distilling Knowledge from Graph Convolutional Networks Yiding Yang Jiayan Qiu Xiuming Zhang Dacheng Tao Xinchao Wang 160 226 0 23 Mar 2020