GemNet: Universal Directional Graph Neural Networks for Molecules

2 June 2021

Stephan Günnemann

Papers citing "GemNet: Universal Directional Graph Neural Networks for Molecules"

50 / 237 papers shown

Title
MatSciML: A Broad, Multi-Task Benchmark for Solid-State Materials Modeling Kin Long Kelvin Lee Carmelo Gonzales Marcel Nassar Matthew Spellings Mikhail Galkin Santiago Miret 32 15 0 12 Sep 2023
3D Denoisers are Good 2D Teachers: Molecular Pretraining via Denoising and Cross-Modal Distillation Sungjun Cho Dae-Woong Jeong Sung Moon Ko Jinwoo Kim Sehui Han Seunghoon Hong Honglak Lee Moontae Lee AI4CE DiffM 32 1 0 08 Sep 2023
PolyGET: Accelerating Polymer Simulations by Accurate and Generalizable Forcefield with Equivariant Transformer Rui Feng Huan Tran Aubrey Toland Binghong Chen Qi Zhu R. Ramprasad Chao Zhang 11 1 0 01 Sep 2023
May the Force be with You: Unified Force-Centric Pre-Training for 3D Molecular Conformations Rui Feng Qi Zhu Huan Tran Binghong Chen Aubrey Toland R. Ramprasad Chao Zhang AI4CE 28 9 0 24 Aug 2023
Diffusion probabilistic models enhance variational autoencoder for crystal structure generative modeling T. Pakornchote Natthaphon Choomphon-anomakhun Sorrjit Arrerut C. Atthapak S. Khamkaeo Thiparat Chotibut T. Bovornratanaraks DiffM 29 17 0 04 Aug 2023
Crystal Structure Prediction by Joint Equivariant Diffusion Rui Jiao Wen-bing Huang Peijia Lin Jiaqi Han Pin Chen Yutong Lu Yang Liu DiffM 27 60 0 30 Jul 2023
Generalizing Graph ODE for Learning Complex System Dynamics across Environments Zijie Huang Yizhou Sun Wei Wang CML OOD AI4CE 29 25 0 10 Jul 2023
ChiENN: Embracing Molecular Chirality with Graph Neural Networks Piotr Gaiñski Michał Koziarski Jacek Tabor Marek Śmieja GNN 34 3 0 05 Jul 2023
Why Deep Models Often cannot Beat Non-deep Counterparts on Molecular Property Prediction? Jun-Xiong Xia Lecheng Zhang Xiao Zhu Stan Z. Li 26 3 0 30 Jun 2023
Equivariant flow matching Leon Klein Andreas Krämer Frank Noé 16 60 0 26 Jun 2023
Accelerating Molecular Graph Neural Networks via Knowledge Distillation Filip Ekstrom Kelvinius D. Georgiev Artur P. Toshev Johannes Gasteiger 26 7 0 26 Jun 2023
StrainTensorNet: Predicting crystal structure elastic properties using SE(3)-equivariant graph neural networks T. Pakornchote A. Ektarawong Thiparat Chotibut 31 4 0 22 Jun 2023
EquiformerV2: Improved Equivariant Transformer for Scaling to Higher-Degree Representations Yidong Liao Brandon M. Wood Abhishek Das Tess E. Smidt 26 131 0 21 Jun 2023
Uncertainty Estimation for Molecules: Desiderata and Methods Tom Wollschlager Nicholas Gao Bertrand Charpentier Mohamed Amine Ketata Stephan Günnemann 21 9 0 20 Jun 2023
QH9: A Quantum Hamiltonian Prediction Benchmark for QM9 Molecules Haiyang Yu Meng Liu Youzhi Luo A. Strasser X. Qian Xiaoning Qian Shuiwang Ji 15 20 0 15 Jun 2023
Symmetry-Informed Geometric Representation for Molecules, Proteins, and Crystalline Materials Shengchao Liu Weitao Du Yanjing Li Zhuoxinran Li Zhiling Zheng ... Anima Anandkumar C. Borgs J. Chayes Hongyu Guo Jian Tang AI4CE 33 20 0 15 Jun 2023
M $^2$ Hub: Unlocking the Potential of Machine Learning for Materials Discovery Yuanqi Du Yingheng Wang Yin-Hua Huang Jianan Canal Li Yanqiao Zhu T. Xie Chenru Duan J. Gregoire Carla P. Gomes 34 6 0 14 Jun 2023
Automated 3D Pre-Training for Molecular Property Prediction Xu Wang Huan Zhao Weiwei Tu Quanming Yao AI4CE 28 35 0 13 Jun 2023
Efficient Approximations of Complete Interatomic Potentials for Crystal Property Prediction Yu-Ching Lin Keqiang Yan Youzhi Luo Yi Liu Xiaoning Qian Shuiwang Ji 66 33 0 12 Jun 2023
TensorNet: Cartesian Tensor Representations for Efficient Learning of Molecular Potentials Guillem Simeon Gianni De Fabritiis 26 45 0 10 Jun 2023
Efficient and Equivariant Graph Networks for Predicting Quantum Hamiltonian Haiyang Yu Zhao Xu X. Qian Xiaoning Qian Shuiwang Ji 37 24 0 08 Jun 2023
Optimized Crystallographic Graph Generation for Material Science Astrid Klipfel Y. Frégier A. Sayede Zied Bouraoui 12 1 0 07 Jun 2023
Unified Model for Crystalline Material Generation Astrid Klipfel Y. Frégier A. Sayede Zied Bouraoui 11 6 0 07 Jun 2023
How does over-squashing affect the power of GNNs? Francesco Di Giovanni T. Konstantin Rusch Michael M. Bronstein Andreea Deac Marc Lackenby Siddhartha Mishra Petar Velivcković 30 34 0 06 Jun 2023
Machine Learning Force Fields with Data Cost Aware Training Alexander Bukharin Tianyi Liu Sheng Wang Simiao Zuo Weihao Gao Wen Yan Tuo Zhao AI4CE 29 0 0 05 Jun 2023
Transfer learning for atomistic simulations using GNNs and kernel mean embeddings Johannes Falk L. Bonati P. Novelli Michele Parinello Massimiliano Pontil 30 4 0 02 Jun 2023
Generalist Equivariant Transformer Towards 3D Molecular Interaction Learning Xiangzhe Kong Wen-bing Huang Yang Liu 22 13 0 02 Jun 2023
DiffPack: A Torsional Diffusion Model for Autoregressive Protein Side-Chain Packing Yang Zhang Zuobai Zhang Bozitao Zhong Sanchit Misra Jian Tang DiffM 21 33 0 01 Jun 2023
Smooth, exact rotational symmetrization for deep learning on point clouds Sergey Pozdnyakov Michele Ceriotti 3DPC 37 25 0 30 May 2023
From Zero to Turbulence: Generative Modeling for 3D Flow Simulation Marten Lienen David Lüdke Jan Hansen-Palmus Stephan Günnemann DiffM AI4CE 24 23 0 29 May 2023
Learning Lagrangian Fluid Mechanics with E( $3$ )-Equivariant Graph Neural Networks Artur P. Toshev Gianluca Galletti Johannes Brandstetter Stefan Adami Nikolaus A. Adams AI4CE 27 5 0 24 May 2023
Learning Joint 2D & 3D Diffusion Models for Complete Molecule Generation Han Huang Leilei Sun Bowen Du Weifeng Lv DiffM 24 16 0 21 May 2023
PANNA 2.0: Efficient neural network interatomic potentials and new architectures Franco Pellegrini Ruggero Lot Yusuf Shaidu E. Küçükbenli 17 9 0 19 May 2023
Clifford Group Equivariant Neural Networks David Ruhe Johannes Brandstetter Patrick Forré 29 35 0 18 May 2023
Towards Multi-Layered 3D Garments Animation Yidi Shao Chen Change Loy Bo Dai 3DH AI4CE 29 10 0 17 May 2023
Efficient Equivariant Transfer Learning from Pretrained Models Sourya Basu Pulkit Katdare P. Sattigeri Vijil Chenthamarakshan Katherine Driggs Campbell Payel Das L. Varshney 40 7 0 17 May 2023
E(n) Equivariant Message Passing Simplicial Networks Floor Eijkelboom Rob D. Hesselink Erik J. Bekkers 22 14 0 11 May 2023
3D Molecular Geometry Analysis with 2D Graphs Zhao Xu Yaochen Xie Youzhi Luo Xuan Zhang Xinyi Xu Meng Liu Kaleb Dickerson Cheng Deng Maho Nakata Shuiwang Ji 19 1 0 01 May 2023
FAENet: Frame Averaging Equivariant GNN for Materials Modeling Alexandre Duval Victor Schmidt A. Garcia Santiago Miret Fragkiskos D. Malliaros Yoshua Bengio David Rolnick 34 55 0 28 Apr 2023
A new perspective on building efficient and expressive 3D equivariant graph neural networks Weitao Du Yuanqi Du Limei Wang Dieqiao Feng Guifeng Wang Shuiwang Ji Carla P. Gomes Zhixin Ma AI4CE 32 33 0 07 Apr 2023
High Accuracy Uncertainty-Aware Interatomic Force Modeling with Equivariant Bayesian Neural Networks Tim Rensmeyer Benjamin Craig D. Kramer Oliver Niggemann BDL 41 3 0 05 Apr 2023
GeoTMI:Predicting quantum chemical property with easy-to-obtain geometry via positional denoising Hyeonsu Kim Jeheon Woo Seonghwan Kim Seokhyun Moon Jun Hyeong Kim Woo Youn Kim AI4CE 42 6 0 28 Mar 2023
Highly Accurate Quantum Chemical Property Prediction with Uni-Mol+ Shuqi Lu Zhifeng Gao Di He Linfeng Zhang Guolin Ke 40 24 0 16 Mar 2023
Ewald-based Long-Range Message Passing for Molecular Graphs Arthur Kosmala Johannes Gasteiger Nicholas Gao Stephan Günnemann 71 25 0 08 Mar 2023
DR-Label: Improving GNN Models for Catalysis Systems by Label Deconstruction and Reconstruction Bo-Lan Wang Chen Liang Jiaze Wang Furui Liu Shaogang Hao Dong Li Jianye Hao Guangyong Chen Xiaolong Zou Pheng-Ann Heng 41 3 0 06 Mar 2023
AERK: Aligned Entropic Reproducing Kernels through Continuous-time Quantum Walks Lixin Cui Ming Li Yue Wang Lu Bai Edwin R. Hancock 16 0 0 04 Mar 2023
Denoise Pretraining on Nonequilibrium Molecules for Accurate and Transferable Neural Potentials Yuyang Wang Chang Xu Zijie Li A. Farimani AAML AI4CE 21 21 0 03 Mar 2023
Connectivity Optimized Nested Graph Networks for Crystal Structures R. Ruff Patrick Reiser Jan Stuhmer Pascal Friederich GNN 28 11 0 27 Feb 2023
MiDi: Mixed Graph and 3D Denoising Diffusion for Molecule Generation Clément Vignac Nagham Osman Laura Toni P. Frossard DiffM 50 50 0 17 Feb 2023
Knowledge-augmented Graph Machine Learning for Drug Discovery: A Survey from Precision to Interpretability Zhiqiang Zhong A. Barkova Davide Mottin 24 8 0 16 Feb 2023