Distribution Learning for Molecular Regression

30 July 2024

Papers citing "Distribution Learning for Molecular Regression"

22 / 22 papers shown

Title
Towards Training Billion Parameter Graph Neural Networks for Atomic Simulations Anuroop Sriram Abhishek Das Brandon M. Wood Siddharth Goyal C. L. Zitnick AI4CE 69 27 0 18 Mar 2022
Rotation Invariant Graph Neural Networks using Spin Convolutions Muhammed Shuaibi Adeesh Kolluru Abhishek Das Aditya Grover Anuroop Sriram Zachary W. Ulissi C. L. Zitnick AI4CE 90 69 0 17 Jun 2021
GemNet: Universal Directional Graph Neural Networks for Molecules Johannes Klicpera Florian Becker Stephan Günnemann AI4CE 127 464 0 02 Jun 2021
Equivariant message passing for the prediction of tensorial properties and molecular spectra Kristof T. Schütt Oliver T. Unke M. Gastegger 110 544 0 05 Feb 2021
Fast and Uncertainty-Aware Directional Message Passing for Non-Equilibrium Molecules Johannes Klicpera Shankari Giri Johannes T. Margraf Stephan Günnemann 88 324 0 28 Nov 2020
Molecular Mechanics-Driven Graph Neural Network with Multiplex Graph for Molecular Structures Shuo-feng Zhang Yang Liu Lei Xie GNN 65 60 0 15 Nov 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 301 535 0 20 Oct 2020
GraphNorm: A Principled Approach to Accelerating Graph Neural Network Training Tianle Cai Shengjie Luo Keyulu Xu Di He Tie-Yan Liu Liwei Wang GNN 88 167 0 07 Sep 2020
Graph Convolutional Neural Networks with Node Transition Probability-based Message Passing and DropNode Regularization T. Do Duc Minh Nguyen Giannis Bekoulis Adrian Munteanu Nikos Deligiannis 50 37 0 28 Aug 2020
DeeperGCN: All You Need to Train Deeper GCNs Guohao Li Chenxin Xiong Ali K. Thabet Guohao Li GNN 243 442 0 13 Jun 2020
Towards Deeper Graph Neural Networks with Differentiable Group Normalization Kaixiong Zhou Xiao Huang Yuening Li Daochen Zha Rui Chen Helen Zhou 133 205 0 12 Jun 2020
Directional Message Passing for Molecular Graphs Johannes Klicpera Janek Groß Stephan Günnemann 140 881 0 06 Mar 2020
PyTorch: An Imperative Style, High-Performance Deep Learning Library Adam Paszke Sam Gross Francisco Massa Adam Lerer James Bradbury ... Sasank Chilamkurthy Benoit Steiner Lu Fang Junjie Bai Soumith Chintala ODL 565 42,677 0 03 Dec 2019
PairNorm: Tackling Oversmoothing in GNNs Lingxiao Zhao Leman Akoglu 74 510 0 26 Sep 2019
DropEdge: Towards Deep Graph Convolutional Networks on Node Classification Yu Rong Wenbing Huang Tingyang Xu Junzhou Huang 113 1,349 0 25 Jul 2019
Accurate Uncertainties for Deep Learning Using Calibrated Regression Volodymyr Kuleshov Nathan Fenner Stefano Ermon BDL UQCV 209 636 0 01 Jul 2018
SchNet: A continuous-filter convolutional neural network for modeling quantum interactions Kristof T. Schütt Pieter-Jan Kindermans Huziel Enoc Sauceda Felix Stefan Chmiela A. Tkatchenko K. Müller 157 1,087 0 26 Jun 2017
Neural Message Passing for Quantum Chemistry Justin Gilmer S. Schoenholz Patrick F. Riley Oriol Vinyals George E. Dahl 598 7,500 0 04 Apr 2017
Regularizing Neural Networks by Penalizing Confident Output Distributions Gabriel Pereyra George Tucker J. Chorowski Lukasz Kaiser Geoffrey E. Hinton NoLa 165 1,141 0 23 Jan 2017
Rethinking the Inception Architecture for Computer Vision Christian Szegedy Vincent Vanhoucke Sergey Ioffe Jonathon Shlens Z. Wojna 3DV BDL 886 27,427 0 02 Dec 2015
Convolutional Networks on Graphs for Learning Molecular Fingerprints David Duvenaud D. Maclaurin J. Aguilera-Iparraguirre Rafael Gómez-Bombarelli Timothy D. Hirzel Alán Aspuru-Guzik Ryan P. Adams GNN 229 3,356 0 30 Sep 2015
Fast R-CNN Ross B. Girshick ObjD 312 25,087 0 30 Apr 2015