Title
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 0 0 0 17 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 90 0 0 28 Apr 2025
polyGen: A Learning Framework for Atomic-level Polymer Structure Generation Ayush Jain Rampi Ramprasad 48 0 0 24 Apr 2025
Scaling Laws of Graph Neural Networks for Atomistic Materials Modeling Chaojian Li Zhifan Ye Massimiliano Lupo Pasini Jong Youl Choi Cheng Wan Y. Lin Prasanna Balaprakash 39 0 0 10 Apr 2025
Accelerating and enhancing thermodynamic simulations of electrochemical interfaces Xiaochen Du Mengren Liu Jiayu Peng Hoje Chun Alexander Hoffman Bilge Yildiz Lin Li Martin Z. Bazant Rafael Gómez-Bombarelli 56 0 0 22 Mar 2025
Transfer learning from first-principles calculations to experiments with chemistry-informed domain transformation Yuta Yahagi Kiichi Obuchi Fumihiko Kosaka Kota Matsui 26 0 0 20 Mar 2025
CrystalFramer: Rethinking the Role of Frames for SE(3)-Invariant Crystal Structure Modeling Yusei Ito Tatsunori Taniai Ryo Igarashi Yoshitaka Ushiku K. Ono 60 0 0 04 Mar 2025
A Periodic Bayesian Flow for Material Generation Hanlin Wu Yuxuan Song Jingjing Gong Ziyao Cao Y. Ouyang Jianbing Zhang Hao Zhou Wei-Ying Ma Jingjing Liu DiffM 69 2 0 04 Feb 2025
DenseGNN: universal and scalable deeper graph neural networks for high-performance property prediction in crystals and molecules Hongwei Du Jiamin Wang Jian Hui Lanting Zhang Hong Wang AI4CE GNN 29 2 0 08 Jan 2025
The dark side of the forces: assessing non-conservative force models for atomistic machine learning Filippo Bigi Marcel F. Langer Michele Ceriotti AI4CE 93 7 0 16 Dec 2024
Bridging Geometric States via Geometric Diffusion Bridge Shengjie Luo Yixian Xu Di He Shuxin Zheng Tie-Yan Liu Liwei Wang 39 0 0 31 Oct 2024
The Importance of Being Scalable: Improving the Speed and Accuracy of Neural Network Interatomic Potentials Across Chemical Domains Eric Qu Aditi S. Krishnapriyan LRM 30 10 0 31 Oct 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 41 16 0 16 Oct 2024
Improving Molecular Modeling with Geometric GNNs: an Empirical Study Ali Ramlaoui Théo Saulus Basile Terver Victor Schmidt David Rolnick Fragkiskos D. Malliaros Alexandre Duval AI4CE 38 1 0 11 Jul 2024
MaTableGPT: GPT-based Table Data Extractor from Materials Science Literature Gyeong Hoon Yi Jiwoo Choi Hyeongyun Song Olivia Miano Jaewoong Choi ... Seok Su Sohn David Buttler A. Hiszpanski S. Han Donghun Kim LMTD 39 3 0 08 Jun 2024
Guided Multi-objective Generative AI to Enhance Structure-based Drug Design Amit Kadan Kevin Ryczko Erika Lloyd A. Roitberg Takeshi Yamazaki 93 1 0 20 May 2024
React-OT: Optimal Transport for Generating Transition State in Chemical Reactions Chenru Duan Guan-Horng Liu Yuanqi Du Tianrong Chen Qiyuan Zhao Haojun Jia Carla P. Gomes Evangelos A. Theodorou Heather J. Kulik OT 45 3 0 20 Apr 2024
Adapting OC20-trained EquiformerV2 Models for High-Entropy Materials Christian M. Clausen Jan Rossmeisl Zachary W. Ulissi 35 1 0 14 Mar 2024
Generalizing Denoising to Non-Equilibrium Structures Improves Equivariant Force Fields Yi-Lun Liao Tess E. Smidt Abhishek Das DiffM AI4CE 40 12 0 14 Mar 2024
A Survey of Geometric Graph Neural Networks: Data Structures, Models and Applications Jiaqi Han Jiacheng Cen Liming Wu Zongzhao Li Xiangzhe Kong ... Zhewei Wei Deli Zhao Yu Rong Wenbing Huang Wenbing Huang AI4CE 34 20 0 01 Mar 2024
CHILI: Chemically-Informed Large-scale Inorganic Nanomaterials Dataset for Advancing Graph Machine Learning Ulrik Friis-Jensen Frederik L. Johansen A. Anker Erik B. Dam Kirsten M. Ø. Jensen Raghavendra Selvan AI4CE 40 3 0 20 Feb 2024
Structure-based out-of-distribution (OOD) materials property prediction: a benchmark study Sadman Sadeed Omee Nihang Fu Rongzhi Dong Ming Hu Jianjun Hu OOD 31 17 0 16 Jan 2024
Accelerating the prediction of inorganic surfaces with machine learning interatomic potentials Kyle Noordhoek Christopher J. Bartel AI4CE 27 6 0 18 Dec 2023
Higher-Order Equivariant Neural Networks for Charge Density Prediction in Materials Teddy Koker Keegan Quigley Eric Taw Kevin Tibbetts Lin Li 20 12 0 08 Dec 2023
AdsorbRL: Deep Multi-Objective Reinforcement Learning for Inverse Catalysts Design Romain Lacombe Lucas Hendren Khalid El-Awady 13 1 0 04 Dec 2023
The perpetual motion machine of AI-generated data and the distraction of ChatGPT-as-scientist Jennifer Listgarten LRM 14 2 0 29 Nov 2023
Unified machine learning tasks and datasets for enhancing renewable energy Arsam Aryandoust Thomas Rigoni Francesco di Stefano Anthony Patt 40 0 0 12 Nov 2023
Gradual Optimization Learning for Conformational Energy Minimization Artem Tsypin L. Ugadiarov Kuzma Khrabrov Alexander Telepov Egor Rumiantsev Alexey Skrynnik Aleksandr I. Panov Dmitry Vetrov E. Tutubalina Artur Kadurin 24 1 0 05 Nov 2023
The Open DAC 2023 Dataset and Challenges for Sorbent Discovery in Direct Air Capture Anuroop Sriram Sihoon Choi Xiaohan Yu Logan M. Brabson Abhishek Das Zachary W. Ulissi Matthew Uyttendaele A. Medford D. Sholl AI4CE 31 35 0 01 Nov 2023
Towards Combinatorial Generalization for Catalysts: A Kohn-Sham Charge-Density Approach Phillip Pope David Jacobs 26 3 0 28 Oct 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 24 32 0 25 Oct 2023
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 35 15 0 12 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 36 35 0 28 Aug 2023
On Data Imbalance in Molecular Property Prediction with Pre-training Limin Wang Masatoshi Hanai Toyotaro Suzumura Shun Takashige Kenjiro Taura AI4CE 35 0 0 17 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
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
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
Automated 3D Pre-Training for Molecular Property Prediction Xu Wang Huan Zhao Weiwei Tu Quanming Yao AI4CE 28 35 0 13 Jun 2023
Generalist Equivariant Transformer Towards 3D Molecular Interaction Learning Xiangzhe Kong Wen-bing Huang Yang Liu 22 13 0 02 Jun 2023
Connectivity Optimized Nested Graph Networks for Crystal Structures R. Ruff Patrick Reiser Jan Stuhmer Pascal Friederich GNN 28 11 0 27 Feb 2023
Reducing SO(3) Convolutions to SO(2) for Efficient Equivariant GNNs Saro Passaro C. L. Zitnick 3DPC 34 79 0 07 Feb 2023
GPS++: Reviving the Art of Message Passing for Molecular Property Prediction Dominic Masters Josef Dean Kerstin Klaser Zhiyi Li Sam Maddrell-Mander ... D. Beker Andrew Fitzgibbon Shenyang Huang Ladislav Rampášek Dominique Beaini 38 8 0 06 Feb 2023
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 35 44 0 29 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 38 19 0 31 Oct 2022
Forces are not Enough: Benchmark and Critical Evaluation for Machine Learning Force Fields with Molecular Simulations Xiang Fu Zhenghao Wu Wujie Wang T. Xie S. Keten Rafael Gómez-Bombarelli Tommi Jaakkola 32 136 0 13 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 33 6 0 07 Oct 2022
E(3)-Equivariant Graph Neural Networks for Data-Efficient and Accurate Interatomic Potentials Simon L. Batzner Albert Musaelian Lixin Sun Mario Geiger J. Mailoa M. Kornbluth N. Molinari Tess E. Smidt Boris Kozinsky 215 1,240 0 08 Jan 2021
The Open Catalyst 2020 (OC20) Dataset and Community Challenges L. Chanussot Abhishek Das Siddharth Goyal Thibaut Lavril Muhammed Shuaibi ... Brandon M. Wood Junwoong Yoon Devi Parikh C. L. Zitnick Zachary W. Ulissi 232 504 0 20 Oct 2020