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
Learning equivariant models by discovering symmetries with learnable augmentations Eduardo Santos Escriche Stefanie Jegelka 91 0 0 04 Jun 2025
The Generalized Skew Spectrum of Graphs Armando Bellante Martin Plávala Alessandro Luongo 51 0 0 29 May 2025
Understanding the Capabilities of Molecular Graph Neural Networks in Materials Science Through Multimodal Learning and Physical Context Encoding Can Polat Hasan Kurban Erchin Serpedin Mustafa Kurban AI4CE 61 1 0 17 May 2025
EDBench: Large-Scale Electron Density Data for Molecular Modeling Hongxin Xiang Ke Li M. Liu Zhixiang Cheng Bin Yao Wenjie Du Jun Xia Li Zeng Xin Jin Xiangxiang Zeng 67 0 0 14 May 2025
Quotient Complex Transformer (QCformer) for Perovskite Data Analysis Xinyu You Xiang Liu Chuan-Shen Hu Kelin Xia Tze Chien Sum 70 0 0 14 May 2025
Representing spherical tensors with scalar-based machine-learning models Michelangelo Domina Filippo Bigi Paolo Pegolo Michele Ceriotti 78 0 0 08 May 2025
Universally applicable and tunable graph-based coarse-graining for Machine learning force fields Christoph Brunken Sebastien Boyer Mustafa Omar Martin Maarand Olivier Peltre Solal Attias Bakary Diallo Anastasia Markina Olaf Othersen Oliver E. Bent OOD AI4CE 109 1 0 24 Mar 2025
How simple can you go? An off-the-shelf transformer approach to molecular dynamics Max Eissler Tim Korjakow Stefan Ganscha Oliver T. Unke Klaus-Robert Müller Stefan Gugler 127 2 0 03 Mar 2025
Effective Field Neural Network Xi Liu Yujun Zhao Chun Yu Wan Yang Zhang Junwei Liu AI4CE 85 0 0 24 Feb 2025
Predicting the Energy Landscape of Stochastic Dynamical System via Physics-informed Self-supervised Learning Ruikun Li Huandong Wang Qingmin Liao Yong Li 57 2 0 24 Feb 2025
Survey on Recent Progress of AI for Chemistry: Methods, Applications, and Opportunities Ding Hu Pengxiang Hua Zhen Huang 268 0 0 09 Feb 2025
Evaluation of uncertainty estimations for Gaussian process regression based machine learning interatomic potentials Matthias Holzenkamp Dongyu Lyu Ulrich Kleinekathöfer Peter Zaspel 95 0 0 10 Jan 2025
OpenQDC: Open Quantum Data Commons Cristian Gabellini Nikhil Shenoy Stephan Thaler Semih Cantürk Daniel McNeela Dominique Beaini Michael Bronstein Prudencio Tossou AI4CE 167 1 0 29 Nov 2024
Integrating Graph Neural Networks and Many-Body Expansion Theory for Potential Energy Surfaces Siqi Chen Zhiqiang Wang Xianqi Deng Yili Shen C. Ju ... Lin Xiong Guo Ling Dieaa Alhmoud Hui Guan Zhou Lin 75 0 0 03 Nov 2024
Investigating Data Hierarchies in Multifidelity Machine Learning for Excitation Energies Vivin Vinod Peter Zaspel 99 1 0 15 Oct 2024
Pretraining Graph Transformers with Atom-in-a-Molecule Quantum Properties for Improved ADMET Modeling Alessio Fallani Ramil I. Nugmanov Jose A. Arjona-Medina Jörg Kurt Wegner Alexandre Tkatchenko Kostiantyn Chernichenko MedIm AI4CE 70 2 0 10 Oct 2024
Hydrogen under Pressure as a Benchmark for Machine-Learning Interatomic Potentials Thomas Bischoff Bastian Jäckl Matthias Rupp 48 2 0 20 Sep 2024
Towards Symbolic XAI -- Explanation Through Human Understandable Logical Relationships Between Features Thomas Schnake Farnoush Rezaei Jafaria Jonas Lederer Ping Xiong Shinichi Nakajima Stefan Gugler G. Montavon Klaus-Robert Müller 97 4 0 30 Aug 2024
A Large Encoder-Decoder Family of Foundation Models For Chemical Language Eduardo Soares Victor Shirasuna E. V. Brazil Renato F. G. Cerqueira Dmitry Zubarev Kristin Schmidt AI4CE 79 8 0 24 Jul 2024
Assessing Non-Nested Configurations of Multifidelity Machine Learning for Quantum-Chemical Properties Vivin Vinod Peter Zaspel AI4CE 95 3 0 24 Jul 2024
Probing the effects of broken symmetries in machine learning Marcel F. Langer Sergey Pozdnyakov Michele Ceriotti AI4CE 85 10 0 25 Jun 2024
Encoder-Decoder Neural Networks in Interpretation of X-ray Spectra Jalmari Passilahti A. Vladyka Johannes Niskanen 38 1 0 20 Jun 2024
Multi-Type Point Cloud Autoencoder: A Complete Equivariant Embedding for Molecule Conformation and Pose Michael Kilgour Mark Tuckerman Jutta Rogal 114 0 0 22 May 2024
Data-Error Scaling in Machine Learning on Natural Discrete Combinatorial Mutation-prone Sets: Case Studies on Peptides and Small Molecules Vanni Doffini O. A. von Lilienfeld Michael A. Nash 60 1 0 08 May 2024
FeNNol: an Efficient and Flexible Library for Building Force-field-enhanced Neural Network Potentials Thomas Plé Olivier Adjoua Louis Lagardère Jean‐Philip Piquemal 169 9 0 02 May 2024
Transfer Learning for Molecular Property Predictions from Small Data Sets Thorren Kirschbaum A. Bande AI4CE 39 2 0 20 Apr 2024
Molecular relaxation by reverse diffusion with time step prediction Khaled Kahouli Stefaan S. P. Hessmann Klaus-Robert Muller Shinichi Nakajima Stefan Gugler Niklas W. A. Gebauer DiffM 74 6 0 16 Apr 2024
Twins in rotational spectroscopy: Does a rotational spectrum uniquely identify a molecule? Marcus Schwarting Nathan A Seifert Michael J. Davis Ben Blaiszik Ian Foster Kirill Prozument 58 2 0 05 Apr 2024
Expanding Chemical Representation with k-mers and Fragment-based Fingerprints for Molecular Fingerprinting Sarwan Ali Prakash Chourasia Murray Patterson 24 1 0 28 Mar 2024
3M-Diffusion: Latent Multi-Modal Diffusion for Text-Guided Generation of Molecular Graphs Huaisheng Zhu Teng Xiao V. Honavar DiffM 79 1 0 11 Mar 2024
Multi-Modal Representation Learning for Molecular Property Prediction: Sequence, Graph, Geometry Zeyu Wang Tianyi Jiang Jinhuan Wang Qi Xuan AI4CE 148 8 0 07 Jan 2024
Predicting Properties of Periodic Systems from Cluster Data: A Case Study of Liquid Water Viktor Zaverkin David Holzmüller Robin Schuldt Johannes Kastner 68 18 0 03 Dec 2023
Symphony: Symmetry-Equivariant Point-Centered Spherical Harmonics for Molecule Generation Ameya Daigavane Song Kim Mario Geiger Tess E. Smidt 123 10 0 27 Nov 2023
Interpretable Prototype-based Graph Information Bottleneck Sangwoo Seo Sungwon Kim Chanyoung Park 70 14 0 30 Oct 2023
Using Slisemap to interpret physical data Lauri Seppäläinen Anton Björklund V. Besel Kai Puolamäki 67 1 0 24 Oct 2023
Rethinking Tokenizer and Decoder in Masked Graph Modeling for Molecules Zhiyuan Liu Yaorui Shi An Zhang Enzhi Zhang Kenji Kawaguchi Xiang Wang Tat-Seng Chua AI4CE 93 40 0 23 Oct 2023
A Survey on Quantum Machine Learning: Current Trends, Challenges, Opportunities, and the Road Ahead Kamila Zaman Alberto Marchisio Muhammad Abdullah Hanif Mohamed Bennai 126 26 0 16 Oct 2023
Insightful analysis of historical sources at scales beyond human capabilities using unsupervised Machine Learning and XAI Oliver Eberle Jochen Büttner Hassan el-Hajj G. Montavon Klaus-Robert Muller Matteo Valleriani 65 2 0 13 Oct 2023
HoloNets: Spectral Convolutions do extend to Directed Graphs Christian Koke Zorah Lähner 106 11 0 03 Oct 2023
ResolvNet: A Graph Convolutional Network with multi-scale Consistency Christian Koke Abhishek Saroha Yuesong Shen Marvin Eisenberger Zorah Lähner GNN 59 1 0 30 Sep 2023
From Peptides to Nanostructures: A Euclidean Transformer for Fast and Stable Machine Learned Force Fields J. Frank Oliver T. Unke Klaus-Robert Muller Stefan Chmiela 71 3 0 21 Sep 2023
Matbench Discovery -- A framework to evaluate machine learning crystal stability predictions Janosh Riebesell Rhys E. A. Goodall Philipp Benner Chiang Yuan Bowen Deng A. Lee Anubhav Jain Kristin A. Persson OOD 79 44 0 28 Aug 2023
Physics-inspired Equivariant Descriptors of Non-bonded Interactions Kevin K. Huguenin-Dumittan P. Loche Haoran Ni Michele Ceriotti 42 22 0 25 Aug 2023
Modeling Edge Features with Deep Bayesian Graph Networks Daniele Atzeni Federico Errica D. Bacciu Alessio Micheli 75 7 0 17 Aug 2023
Rotation-Invariant Random Features Provide a Strong Baseline for Machine Learning on 3D Point Clouds O. Melia Eric Jonas Rebecca Willett OOD 3DPC 73 3 0 27 Jul 2023
On minimizing the training set fill distance in machine learning regression Paolo Climaco Jochen Garcke 47 1 0 20 Jul 2023
Variational Monte Carlo on a Budget -- Fine-tuning pre-trained Neural Wavefunctions Michael Scherbela Leon Gerard Philipp Grohs 68 7 0 15 Jul 2023
Substitutional Alloying Using Crystal Graph Neural Networks Dario Massa Daniel Cie'sliñski A. Naghdi Stefanos Papanikolaou AI4CE 47 1 0 19 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 211 37 0 12 Jun 2023
Scaling Spherical CNNs Carlos Esteves Jean-Jacques E. Slotine A. Makadia GNN LRM 85 14 0 08 Jun 2023