SchNet: A continuous-filter convolutional neural network for modeling quantum interactions

26 June 2017

Kristof T. Schütt

Pieter-Jan Kindermans

Huziel Enoc Sauceda Felix

Papers citing "SchNet: A continuous-filter convolutional neural network for modeling quantum interactions"

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Title
SELFormer: Molecular Representation Learning via SELFIES Language Models Atakan Yüksel Erva Ulusoy Atabey Ünlü Tunca Dogan 25 55 0 10 Apr 2023
Learning Energy-Based Representations of Quantum Many-Body States Abhijith Jayakumar Marc Vuffray A. Lokhov AI4CE 27 3 0 08 Apr 2023
On the Relationships between Graph Neural Networks for the Simulation of Physical Systems and Classical Numerical Methods Artur P. Toshev Ludger Paehler A. Panizza Nikolaus A. Adams AI4CE PINN 11 5 0 31 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
GraphVF: Controllable Protein-Specific 3D Molecule Generation with Variational Flow Fangce Sun Zhihao Zhan Hongyu Guo Ming Zhang Jian Tang 26 6 0 23 Feb 2023
Complete Neural Networks for Complete Euclidean Graphs Snir Hordan Tal Amir S. Gortler Nadav Dym 3DPC 29 5 0 31 Jan 2023
Graph Scattering beyond Wavelet Shackles Christian Koke Gitta Kutyniok 18 4 0 26 Jan 2023
Scalable Bayesian Uncertainty Quantification for Neural Network Potentials: Promise and Pitfalls Stephan Thaler Gregor Doehner J. Zavadlav 35 21 0 15 Dec 2022
Implicit Convolutional Kernels for Steerable CNNs Maksim Zhdanov Nico Hoffmann Gabriele Cesa 29 5 0 12 Dec 2022
Integration of Pre-trained Protein Language Models into Geometric Deep Learning Networks Fang Wu Yujun Tao Dragomir R. Radev Jinbo Xu Stan Z. Li AI4CE 30 32 0 07 Dec 2022
AdsorbML: A Leap in Efficiency for Adsorption Energy Calculations using Generalizable Machine Learning Potentials Janice Lan Aini Palizhati Muhammed Shuaibi Brandon M. Wood Brook Wander Abhishek Das M. Uyttendaele C. L. Zitnick Zachary W. Ulissi 29 44 0 29 Nov 2022
Synthetic data enable experiments in atomistic machine learning John L A Gardner Z. Beaulieu Volker L. Deringer 31 6 0 29 Nov 2022
Supervised Pretraining for Molecular Force Fields and Properties Prediction Xiang Gao Weihao Gao Wen Xiao Zhirui Wang Chong Wang Liang Xiang AI4CE 20 8 0 23 Nov 2022
Fast Uncertainty Estimates in Deep Learning Interatomic Potentials Albert J. W. Zhu Simon L. Batzner Albert Musaelian Boris Kozinsky 22 45 0 17 Nov 2022
ParticleGrid: Enabling Deep Learning using 3D Representation of Materials Shehtab Zaman E. Ferguson Cécile Pereira D. Akhiyarov Mauricio Araya-Polo Kenneth Chiu DiffM AI4CE 21 2 0 15 Nov 2022
Equivariant Networks for Crystal Structures Sekouba Kaba Siamak Ravanbakhsh AI4CE 48 23 0 15 Nov 2022
Deep Surrogate Docking: Accelerating Automated Drug Discovery with Graph Neural Networks Ryien Hosseini F. Simini Austin R. Clyde A. Ramanathan 21 5 0 04 Nov 2022
Materials Property Prediction with Uncertainty Quantification: A Benchmark Study Daniel Varivoda Rongzhi Dong Sadman Sadeed Omee Jianjun Hu AI4CE 28 20 0 04 Nov 2022
A 3D-Shape Similarity-based Contrastive Approach to Molecular Representation Learning Austin O. Atsango N. Diamant Ziqing Lu Tommaso Biancalani Gabriele Scalia Kangway V Chuang 24 2 0 03 Nov 2022
A Continuous Convolutional Trainable Filter for Modelling Unstructured Data Dario Coscia L. Meneghetti N. Demo G. Stabile G. Rozza 16 8 0 24 Oct 2022
Theoretical Guarantees for Permutation-Equivariant Quantum Neural Networks Louis Schatzki Martín Larocca Quynh T. Nguyen F. Sauvage M. Cerezo 34 84 0 18 Oct 2022
PEMP: Leveraging Physics Properties to Enhance Molecular Property Prediction Yuancheng Sun Yimeng Chen Weizhi Ma Wenhao Huang Kang Liu Zhiming Ma Wei-Ying Ma Yanyan Lan 20 7 0 18 Oct 2022
Injecting Domain Knowledge from Empirical Interatomic Potentials to Neural Networks for Predicting Material Properties Zeren Shui Daniel S. Karls Mingjian Wen Ilia Nikiforov E. Tadmor George Karypis 40 7 0 14 Oct 2022
S4ND: Modeling Images and Videos as Multidimensional Signals Using State Spaces Eric N. D. Nguyen Karan Goel Albert Gu Gordon W. Downs Preey Shah Tri Dao S. Baccus Christopher Ré VLM 22 38 0 12 Oct 2022
Hyperactive Learning (HAL) for Data-Driven Interatomic Potentials Cas van der Oord Matthias Sachs D. P. Kovács Christoph Ortner Gábor Csányi 41 64 0 09 Oct 2022
DiffDock: Diffusion Steps, Twists, and Turns for Molecular Docking Gabriele Corso Hannes Stärk Bowen Jing Regina Barzilay Tommi Jaakkola DiffM 139 410 0 04 Oct 2022
Periodic Graph Transformers for Crystal Material Property Prediction Keqiang Yan Yi Liu Yu-Ching Lin Shuiwang Ji AI4TS 88 84 0 23 Sep 2022
Exact conservation laws for neural network integrators of dynamical systems E. Müller PINN 41 12 0 23 Sep 2022
Interpreting the Mechanism of Synergism for Drug Combinations Using Attention-Based Hierarchical Graph Pooling Zehao Dong Heming Zhang Yixin Chen Philip R. O. Payne Fuhai Li GNN 43 16 0 19 Sep 2022
Unified 2D and 3D Pre-Training of Molecular Representations Jinhua Zhu Yingce Xia Lijun Wu Shufang Xie Tao Qin Wen-gang Zhou Houqiang Li Tie-Yan Liu AI4CE 54 67 0 14 Jul 2022
Cluster Generation via Deep Energy-Based Model A. Y. Artsukevich S. Lepeshkin 27 0 0 17 Jun 2022
The Open Catalyst 2022 (OC22) Dataset and Challenges for Oxide Electrocatalysts Richard Tran Janice Lan Muhammed Shuaibi Brandon M. Wood Siddharth Goyal ... Jehad Abed Oleksandr Voznyy Edward H. Sargent Zachary W. Ulissi C. L. Zitnick 28 172 0 17 Jun 2022
ComENet: Towards Complete and Efficient Message Passing for 3D Molecular Graphs Limei Wang Yi Liu Yu-Ching Lin Hao Liu Shuiwang Ji GNN 38 89 0 17 Jun 2022
MACE: Higher Order Equivariant Message Passing Neural Networks for Fast and Accurate Force Fields Ilyes Batatia D. P. Kovács G. Simm Christoph Ortner Gábor Csányi 41 441 0 15 Jun 2022
Towards a General Purpose CNN for Long Range Dependencies in $N$ D David W. Romero David M. Knigge Albert Gu Erik J. Bekkers E. Gavves Jakub M. Tomczak Mark Hoogendoorn 16 19 0 07 Jun 2022
An Empirical Study of Retrieval-enhanced Graph Neural Networks Dingmin Wang Shengchao Liu Hanchen Wang Bernardo Cuenca Grau Linfeng Song Jian Tang Song Le Qi Liu 13 0 0 01 Jun 2022
Torsional Diffusion for Molecular Conformer Generation Bowen Jing Gabriele Corso Jeffrey Chang Regina Barzilay Tommi Jaakkola DiffM BDL 27 259 0 01 Jun 2022
Tyger: Task-Type-Generic Active Learning for Molecular Property Prediction Kuangqi Zhou Kaixin Wang Jiashi Feng Jian Tang Tingyang Xu Xinchao Wang 26 1 0 23 May 2022
3DLinker: An E(3) Equivariant Variational Autoencoder for Molecular Linker Design Yinan Huang Xing Peng Jianzhu Ma Muhan Zhang BDL 30 47 0 15 May 2022
Pocket2Mol: Efficient Molecular Sampling Based on 3D Protein Pockets Xingang Peng Shitong Luo Jiaqi Guan Qi Xie Jian-wei Peng Jianzhu Ma 27 176 0 15 May 2022
Relaxing Equivariance Constraints with Non-stationary Continuous Filters Tycho F. A. van der Ouderaa David W. Romero Mark van der Wilk 24 33 0 14 Apr 2022
GemNet-OC: Developing Graph Neural Networks for Large and Diverse Molecular Simulation Datasets Johannes Gasteiger Muhammed Shuaibi Anuroop Sriram Stephan Günnemann Zachary W. Ulissi C. L. Zitnick Abhishek Das AI4TS MLAU 33 66 0 06 Apr 2022
When Physics Meets Machine Learning: A Survey of Physics-Informed Machine Learning Chuizheng Meng Sungyong Seo Defu Cao Sam Griesemer Yan Liu PINN AI4CE 39 55 0 31 Mar 2022
Towards Training Billion Parameter Graph Neural Networks for Atomic Simulations Anuroop Sriram Abhishek Das Brandon M. Wood Siddharth Goyal C. L. Zitnick AI4CE 30 27 0 18 Mar 2022
Non-equilibrium molecular geometries in graph neural networks Ali Raza E. Henle Xiaoli Z. Fern AI4CE 21 0 0 07 Mar 2022
GeoDiff: a Geometric Diffusion Model for Molecular Conformation Generation Minkai Xu Lantao Yu Yang Song Chence Shi Stefano Ermon Jian Tang BDL DiffM 24 496 0 06 Mar 2022
Equivariant Graph Attention Networks for Molecular Property Prediction Tuan Le Frank Noé Djork-Arné Clevert 16 21 0 20 Feb 2022
A Survey of Pretraining on Graphs: Taxonomy, Methods, and Applications Jun-Xiong Xia Yanqiao Zhu Yuanqi Du Stan Z. Li VLM 30 41 0 16 Feb 2022
TorchMD-NET: Equivariant Transformers for Neural Network based Molecular Potentials Philipp Thölke Gianni de Fabritiis AI4CE 34 185 0 05 Feb 2022
GraphVAMPNet, using graph neural networks and variational approach to markov processes for dynamical modeling of biomolecules Mahdi Ghorbani Samarjeet Prasad Jeffery B. Klauda B. Brooks GNN 24 30 0 12 Jan 2022