Title
Transition States Energies from Machine Learning: An Application to Reverse Water-Gas Shift on Single-Atom Alloys Raffaele Cheula Mie Andersen 51 0 0 01 May 2025
Towards Faster and More Compact Foundation Models for Molecular Property Prediction Yasir Ghunaim Andrés Villa Gergo Ignacz Gyorgy Szekely Motasem Alfarra Bernard Ghanem AI4CE 84 0 0 28 Apr 2025
Equivariant Masked Position Prediction for Efficient Molecular Representation Junyi An C. Qu Yun-Fei Shi XinHao Liu Qianwei Tang Fenglei Cao Yuan Qi 35 0 0 12 Feb 2025
SymmCD: Symmetry-Preserving Crystal Generation with Diffusion Models Daniel Levy Siba Smarak Panigrahi Sékou-Oumar Kaba Qiang Zhu Kin Long Kelvin Lee Mikhail Galkin Santiago Miret Siamak Ravanbakhsh 192 11 0 05 Feb 2025
The dark side of the forces: assessing non-conservative force models for atomistic machine learning Filippo Bigi Marcel F. Langer Michele Ceriotti AI4CE 91 7 0 16 Dec 2024
Open Materials 2024 (OMat24) Inorganic Materials Dataset and Models Luis Barroso-Luque Muhammed Shuaibi Xiang Fu Brandon M. Wood Misko Dzamba Meng Gao Ammar Rizvi C. L. Zitnick Zachary W. Ulissi AI4CE PINN 32 16 0 16 Oct 2024
SpinMultiNet: Neural Network Potential Incorporating Spin Degrees of Freedom with Multi-Task Learning Koki Ueno Satoru Ohuchi Kazuhide Ichikawa Kei Amii Kensuke Wakasugi 46 0 0 05 Sep 2024
Physics-Informed Weakly Supervised Learning for Interatomic Potentials Makoto Takamoto Viktor Zaverkin Mathias Niepert AI4CE 57 0 0 23 Jul 2024
GeoMFormer: A General Architecture for Geometric Molecular Representation Learning Tianlang Chen Shengjie Luo Di He Shuxin Zheng Tie-Yan Liu Liwei Wang AI4CE 38 5 0 24 Jun 2024
A Recipe for Charge Density Prediction Xiang Fu Andrew S. Rosen Kyle Bystrom Rui Wang Albert Musaelian Boris Kozinsky Tess E. Smidt Tommi Jaakkola 48 5 0 29 May 2024
Guided Multi-objective Generative AI to Enhance Structure-based Drug Design Amit Kadan Kevin Ryczko Erika Lloyd A. Roitberg Takeshi Yamazaki 85 1 0 20 May 2024
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Triplet Interaction Improves Graph Transformers: Accurate Molecular Graph Learning with Triplet Graph Transformers Md Shamim Hussain Mohammed J. Zaki D. Subramanian ViT 26 5 0 07 Feb 2024
Reducing the Cost of Quantum Chemical Data By Backpropagating Through Density Functional Theory Alexander Mathiasen Hatem Helal Paul Balanca Adam Krzywaniak Ali Parviz Frederik Hvilshoj Bla.zej Banaszewski Carlo Luschi Andrew William Fitzgibbon 32 3 0 06 Feb 2024
Holistic chemical evaluation reveals pitfalls in reaction prediction models Victor Sabanza Gil Andres M Bran Malte Franke Remi Schlama J. Luterbacher Philippe Schwaller ELM 25 1 0 14 Dec 2023
Unified machine learning tasks and datasets for enhancing renewable energy Arsam Aryandoust Thomas Rigoni Francesco di Stefano Anthony Patt 35 0 0 12 Nov 2023
From Molecules to Materials: Pre-training Large Generalizable Models for Atomic Property Prediction Nima Shoghi Adeesh Kolluru John R. Kitchin Zachary W. Ulissi C. L. Zitnick Brandon M. Wood AI4CE 22 32 0 25 Oct 2023
Latent Conservative Objective Models for Data-Driven Crystal Structure Prediction Han Qi Xinyang Geng Stefano Rando Iku Ohama Aviral Kumar Sergey Levine DiffM 42 2 0 16 Oct 2023
On the importance of catalyst-adsorbate 3D interactions for relaxed energy predictions Alvaro Carbonero Alexandre Duval Victor Schmidt Santiago Miret Alex Hernandez-Garcia Yoshua Bengio David Rolnick 30 0 0 10 Oct 2023
Materials Informatics Transformer: A Language Model for Interpretable Materials Properties Prediction Hongshuo Huang Rishikesh Magar Chang Xu A. Farimani AI4CE 32 4 0 30 Aug 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 28 33 0 28 Aug 2023
QH9: A Quantum Hamiltonian Prediction Benchmark for QM9 Molecules Haiyang Yu Meng Liu Youzhi Luo A. Strasser X. Qian Xiaoning Qian Shuiwang Ji 13 20 0 15 Jun 2023
Towards Predicting Equilibrium Distributions for Molecular Systems with Deep Learning Shuxin Zheng Jiyan He Chang-Shu Liu Yu Shi Ziheng Lu ... Peiran Jin Chi Chen Frank Noé Haiguang Liu Tie-Yan Liu AI4CE 19 40 0 08 Jun 2023
Generalist Equivariant Transformer Towards 3D Molecular Interaction Learning Xiangzhe Kong Wen-bing Huang Yang Liu 20 13 0 02 Jun 2023
Language models can generate molecules, materials, and protein binding sites directly in three dimensions as XYZ, CIF, and PDB files Daniel Flam-Shepherd Alán Aspuru-Guzik 22 51 0 09 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 29 53 0 28 Apr 2023
High Accuracy Uncertainty-Aware Interatomic Force Modeling with Equivariant Bayesian Neural Networks Tim Rensmeyer Benjamin Craig D. Kramer Oliver Niggemann BDL 36 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 28 6 0 28 Mar 2023
Connectivity Optimized Nested Graph Networks for Crystal Structures R. Ruff Patrick Reiser Jan Stuhmer Pascal Friederich GNN 26 10 0 27 Feb 2023
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Learning a Fourier Transform for Linear Relative Positional Encodings in Transformers K. Choromanski Shanda Li Valerii Likhosherstov Kumar Avinava Dubey Shengjie Luo Di He Yiming Yang Tamás Sarlós Thomas Weingarten Adrian Weller 23 8 0 03 Feb 2023
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Extreme Acceleration of Graph Neural Network-based Prediction Models for Quantum Chemistry Hatem Helal J. Firoz Jenna A. Bilbrey M. M. Krell Tom Murray Ang Li S. Xantheas Sutanay Choudhury GNN 31 5 0 25 Nov 2022
Equivariant Networks for Crystal Structures Sekouba Kaba Siamak Ravanbakhsh AI4CE 42 23 0 15 Nov 2022
The Open MatSci ML Toolkit: A Flexible Framework for Machine Learning in Materials Science Santiago Miret Kin Long Kelvin Lee Carmelo Gonzales Marcel Nassar Matthew Spellings 36 19 0 31 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 30 7 0 14 Oct 2022
AutoML for Climate Change: A Call to Action Renbo Tu Nicholas Roberts Vishak Prasad Sibasis Nayak P. Jain Frederic Sala Ganesh Ramakrishnan Ameet Talwalkar W. Neiswanger Colin White 25 6 0 07 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
Artificial Intelligence in Material Engineering: A review on applications of AI in Material Engineering Lipichanda Goswami Manoj Deka Mohendra Roy AI4CE 31 19 0 15 Sep 2022
Active Learning Exploration of Transition Metal Complexes to Discover Method-Insensitive and Synthetically Accessible Chromophores Chenru Duan Aditya Nandy Gianmarco G. Terrones D. Kastner Heather J. Kulik 28 9 0 10 Aug 2022
Graph neural networks for materials science and chemistry Patrick Reiser Marlen Neubert André Eberhard Luca Torresi Chen Zhou ... Houssam Metni Clint van Hoesel Henrik Schopmans T. Sommer Pascal Friederich GNN AI4CE 39 370 0 05 Aug 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
Graph-level Neural Networks: Current Progress and Future Directions Ge Zhang Jia Wu Jian Yang Shan Xue Wenbin Hu Chuan Zhou Hao Peng Quan.Z Sheng Charu C. Aggarwal GNN AI4CE 38 0 0 31 May 2022
Exploiting Ligand Additivity for Transferable Machine Learning of Multireference Character Across Known Transition Metal Complex Ligands Chenru Duan A. Ladera Julian C.-L. Liu Michael G. Taylor I. Ariyarathna Heather J. Kulik 11 10 0 05 May 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 31 65 0 06 Apr 2022
Towards Training Billion Parameter Graph Neural Networks for Atomic Simulations Anuroop Sriram Abhishek Das Brandon M. Wood Siddharth Goyal C. L. Zitnick AI4CE 25 27 0 18 Mar 2022
Benchmarking Graphormer on Large-Scale Molecular Modeling Datasets Yu Shi Shuxin Zheng Guolin Ke Yifei Shen Jiacheng You Jiyan He Shengjie Luo Chang-Shu Liu Di He Tie-Yan Liu AI4CE 33 65 0 09 Mar 2022
Non-equilibrium molecular geometries in graph neural networks Ali Raza E. Henle Xiaoli Z. Fern AI4CE 15 0 0 07 Mar 2022
Graph Neural Networks Accelerated Molecular Dynamics Zijie Li Kazem Meidani Prakarsh Yadav A. Farimani GNN AI4CE 15 53 0 06 Dec 2021
Geometric and Physical Quantities Improve E(3) Equivariant Message Passing Johannes Brandstetter Rob D. Hesselink Elise van der Pol Erik J. Bekkers Max Welling 17 229 0 06 Oct 2021