Fast and Accurate Modeling of Molecular Atomization Energies with Machine Learning

12 September 2011

Papers citing "Fast and Accurate Modeling of Molecular Atomization Energies with Machine Learning"

50 / 268 papers shown

Title
Higher Order Gauge Equivariant CNNs on Riemannian Manifolds and Applications Gianfranco Cortés Yue Yu R. Chen Melissa S. Armstrong David E Vaillancourt B. Vemuri 89 1 0 26 May 2023
Mol-PECO: a deep learning model to predict human olfactory perception from molecular structures Mengji Zhang Yusuke Hiki Akira Funahashi Tetsuya J. Kobayashi 31 1 0 21 May 2023
Chemellia: An Ecosystem for Atomistic Scientific Machine Learning Anant Thazhemadam Dhairya Gandhi V. Viswanathan Rachel C. Kurchin 38 0 0 19 May 2023
Multi-Fidelity Machine Learning for Excited State Energies of Molecules Vivin Vinod Sayan Maity Peter Zaspel Ulrich Kleinekathöfer AI4CE 79 9 0 18 May 2023
Accurate transition state generation with an object-aware equivariant elementary reaction diffusion model Chenru Duan Yuanqi Du Haojun Jia Heather J. Kulik DiffM 86 52 0 12 Apr 2023
Machine learning for structure-property relationships: Scalability and limitations Zhongzheng Tian Sheng Zhang Gia-Wei Chern 33 2 0 11 Apr 2023
Wigner kernels: body-ordered equivariant machine learning without a basis Filippo Bigi Sergey Pozdnyakov Michele Ceriotti 54 16 0 07 Mar 2023
Machine learning for phase ordering dynamics of charge density waves Chen Cheng Sheng Zhang Gia-Wei Chern 39 10 0 06 Mar 2023
Completeness of Atomic Structure Representations M. J. Willatt Sergey Pozdnyakov Christoph Ortner Michele Ceriotti 79 13 0 28 Feb 2023
Generative Adversarial Symmetry Discovery Jianke Yang Robin Walters Nima Dehmamy Rose Yu GAN 111 29 0 01 Feb 2023
Improved machine learning algorithm for predicting ground state properties Laura Lewis Hsin-Yuan Huang Viet-Trung Tran Sebastian Lehner R. Kueng J. Preskill AI4CE 89 49 0 30 Jan 2023
Graph Scattering beyond Wavelet Shackles Christian Koke Gitta Kutyniok 65 4 0 26 Jan 2023
Limitless stability for Graph Convolutional Networks Christian Koke 89 3 0 26 Jan 2023
Reconstructing Kernel-based Machine Learning Force Fields with Super-linear Convergence Stefan Blücher Klaus-Robert Muller Stefan Chmiela 94 4 0 24 Dec 2022
Machine Learning Coarse-Grained Potentials of Protein Thermodynamics Maciej Majewski Adriana Pérez Philipp Thölke Stefan Doerr N. Charron T. Giorgino B. Husic C. Clementi Frank Noé Gianni De Fabritiis AI4CE 73 78 0 14 Dec 2022
SchNetPack 2.0: A neural network toolbox for atomistic machine learning Kristof T. Schütt Stefaan S. P. Hessmann Niklas W. A. Gebauer Jonas Lederer M. Gastegger 83 65 0 11 Dec 2022
Convolution, aggregation and attention based deep neural networks for accelerating simulations in mechanics Saurabh Deshpande Raúl I. Sosa Stéphane P. A. Bordas J. Lengiewicz AI4CE 79 20 0 01 Dec 2022
Capturing long-range interaction with reciprocal space neural network Hongyu Yu Liangliang Hong Shiyou Chen X. Gong Hongjun Xiang 55 12 0 30 Nov 2022
Learning Regularized Positional Encoding for Molecular Prediction Xiang Gao Weihao Gao Wen Xiao Zhirui Wang Chong Wang Liang Xiang AI4CE 80 2 0 23 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 76 2 0 15 Nov 2022
Leveraging Orbital Information and Atomic Feature in Deep Learning Model Xiangru Yang 88 0 0 29 Oct 2022
Generalizability of Functional Forms for Interatomic Potential Models Discovered by Symbolic Regression Alberto Hernandez Tim Mueller 40 1 0 27 Oct 2022
Graph Neural Network Expressivity and Meta-Learning for Molecular Property Regression Haitz Sáez de Ocáriz Borde Federico Barbero 94 2 0 24 Sep 2022
SPICE, A Dataset of Drug-like Molecules and Peptides for Training Machine Learning Potentials Peter K. Eastman P. Behara David L. Dotson Raimondas Galvelis John E. Herr ... J. Chodera Benjamin P. Pritchard Yuanqing Wang Gianni De Fabritiis T. Markland 119 113 0 21 Sep 2022
Artificial Intelligence in Material Engineering: A review on applications of AI in Material Engineering Lipichanda Goswami Manoj Deka Mohendra Roy AI4CE 94 22 0 15 Sep 2022
Graph Neural Networks for Molecules Yuyang Wang Zijie Li A. Farimani GNN AI4CE 160 28 0 12 Sep 2022
Ab-initio quantum chemistry with neural-network wavefunctions J. Hermann J. Spencer Kenny Choo Antonio Mezzacapo W. Foulkes David Pfau Giuseppe Carleo Frank Noé AI4CE 83 86 0 26 Aug 2022
Algorithmic Differentiation for Automated Modeling of Machine Learned Force Fields Niklas Schmitz Klaus-Robert Muller Stefan Chmiela AI4CE 77 11 0 25 Aug 2022
A machine learning approach to predict the structural and magnetic properties of Heusler alloy families S. Mitra Aquil Ahmad Sajib Biswas A. Das 34 16 0 07 Aug 2022
Graph Neural Network with Local Frame for Molecular Potential Energy Surface Xiyuan Wang Muhan Zhang 70 12 0 01 Aug 2022
Molecular-orbital-based Machine Learning for Open-shell and Multi-reference Systems with Kernel Addition Gaussian Process Regression Lixue Cheng Jiace Sun J. E. Deustua Vignesh C. Bhethanabotla Thomas F. Miller 41 7 0 17 Jul 2022
Lagrangian Density Space-Time Deep Neural Network Topology B. Bishnoi PINN 75 1 0 30 Jun 2022
Approximate Equivariance SO(3) Needlet Convolution Kai Yi Jialin Chen Yu Guang Wang Bingxin Zhou Pietro Lio Yanan Fan J. Hamann 55 5 0 17 Jun 2022
Molecular Dipole Moment Learning via Rotationally Equivariant Gaussian Process Regression with Derivatives in Molecular-orbital-based Machine Learning Jiace Sun Lixue Cheng Thomas F. Miller 74 3 0 31 May 2022
Accurate Machine Learned Quantum-Mechanical Force Fields for Biomolecular Simulations Oliver T. Unke M. Stohr Stefan Ganscha Thomas Unterthiner Hartmut Maennel ... Daniel Ahlin M. Gastegger L. M. Sandonas A. Tkatchenko Klaus-Robert Muller AI4CE 70 18 0 17 May 2022
Machine Learning Diffusion Monte Carlo Energies Kevin Ryczko J. Krogel Isaac Tamblyn DiffM 38 14 0 09 May 2022
Machine learning predictions for local electronic properties of disordered correlated electron systems Yi-Hsuan Liu Sheng Zhang Puhan Zhang Ting-Kuo Lee Gia-Wei Chern 39 8 0 12 Apr 2022
Automatic Identification of Chemical Moieties Jonas Lederer M. Gastegger Kristof T. Schütt Michael C. Kampffmeyer Klaus-Robert Muller Oliver T. Unke 69 5 0 30 Mar 2022
Permutation Invariant Representations with Applications to Graph Deep Learning R. Balan Naveed Haghani M. Singh 72 27 0 14 Mar 2022
A photonic chip-based machine learning approach for the prediction of molecular properties Hui Zhang Jonathan Wei Zhong Lau Lingxiao Wan Liang Shi H. Cai Xianshu Luo Guo-qiang Lo Chee-Kong Lee L. Kwek Ajian Liu 74 10 0 03 Mar 2022
Learning Neural Hamiltonian Dynamics: A Methodological Overview Zhijie Chen Mingquan Feng Junchi Yan H. Zha AI4CE 75 16 0 28 Feb 2022
TorchMD-NET: Equivariant Transformers for Neural Network based Molecular Potentials Philipp Thölke Gianni De Fabritiis AI4CE 129 198 0 05 Feb 2022
Atomistic Simulations for Reactions and Spectroscopy in the Era of Machine Learning -- Quo Vadis? Markus Meuwly AI4CE 25 0 0 11 Jan 2022
Descriptors for Machine Learning Model of Generalized Force Field in Condensed Matter Systems Puhan Zhang Sheng Zhang Gia-Wei Chern AI4CE 39 11 0 03 Jan 2022
Machine learning nonequilibrium electron forces for adiabatic spin dynamics Puhan Zhang Gia-Wei Chern 44 16 0 22 Dec 2021
Toward Explainable AI for Regression Models S. Letzgus Patrick Wagner Jonas Lederer Wojciech Samek Klaus-Robert Muller G. Montavon XAI 97 67 0 21 Dec 2021
Improving Subgraph Recognition with Variational Graph Information Bottleneck Junchi Yu Jie Cao Ran He 94 56 0 18 Dec 2021
AutoGMap: Learning to Map Large-scale Sparse Graphs on Memristive Crossbars Bo Lyu Shengbo Wang S. Wen Kaibo Shi Yin Yang Lingfang Zeng Tingwen Huang 37 3 0 15 Nov 2021
Reducing the Long Tail Losses in Scientific Emulations with Active Learning Yi Heng Lim M. F. Kasim 48 0 0 15 Nov 2021
Geometric Transformer for End-to-End Molecule Properties Prediction Yoni Choukroun Lior Wolf AI4CE ViT 78 16 0 26 Oct 2021