ResearchTrend.AI
  • Papers
  • Communities
  • Events
  • Blog
  • Pricing
Papers
Communities
Social Events
Terms and Conditions
Pricing
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2025 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 2211.13853
  4. Cited By
Extreme Acceleration of Graph Neural Network-based Prediction Models for
  Quantum Chemistry

Extreme Acceleration of Graph Neural Network-based Prediction Models for Quantum Chemistry

25 November 2022
Hatem Helal
J. Firoz
Jenna A. Bilbrey
M. M. Krell
Tom Murray
Ang Li
S. Xantheas
Sutanay Choudhury
    GNN
ArXivPDFHTML

Papers citing "Extreme Acceleration of Graph Neural Network-based Prediction Models for Quantum Chemistry"

7 / 7 papers shown
Title
Towards Foundational Models for Molecular Learning on Large-Scale
  Multi-Task Datasets
Towards Foundational Models for Molecular Learning on Large-Scale Multi-Task Datasets
Dominique Beaini
Shenyang Huang
Joao Alex Cunha
Zhiyi Li
Gabriela Moisescu-Pareja
...
Thérence Bois
Andrew Fitzgibbon
Bla.zej Banaszewski
Chad Martin
Dominic Masters
AI4CE
26
19
0
06 Oct 2023
BitGNN: Unleashing the Performance Potential of Binary Graph Neural
  Networks on GPUs
BitGNN: Unleashing the Performance Potential of Binary Graph Neural Networks on GPUs
Jou-An Chen
Hsin-Hsuan Sung
Xipeng Shen
Sutanay Choudhury
Ang Li
GNN
MQ
23
6
0
04 May 2023
PopSparse: Accelerated block sparse matrix multiplication on IPU
PopSparse: Accelerated block sparse matrix multiplication on IPU
Zhiyi Li
Douglas Orr
V. Ohan
Godfrey Da Costa
Tom Murray
Adam Sanders
D. Beker
Dominic Masters
19
1
0
29 Mar 2023
Accelerating Training and Inference of Graph Neural Networks with Fast
  Sampling and Pipelining
Accelerating Training and Inference of Graph Neural Networks with Fast Sampling and Pipelining
Tim Kaler
Nickolas Stathas
Anne Ouyang
A. Iliopoulos
Tao B. Schardl
C. E. Leiserson
Jie Chen
GNN
68
52
0
16 Oct 2021
E(3)-Equivariant Graph Neural Networks for Data-Efficient and Accurate
  Interatomic Potentials
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
190
1,229
0
08 Jan 2021
The Open Catalyst 2020 (OC20) Dataset and Community Challenges
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
221
498
0
20 Oct 2020
Deep Graph Library: A Graph-Centric, Highly-Performant Package for Graph
  Neural Networks
Deep Graph Library: A Graph-Centric, Highly-Performant Package for Graph Neural Networks
Minjie Wang
Da Zheng
Zihao Ye
Quan Gan
Mufei Li
...
J. Zhao
Haotong Zhang
Alex Smola
Jinyang Li
Zheng-Wei Zhang
AI4CE
GNN
189
743
0
03 Sep 2019
1