Papers citing A critical examination of robustness and generalizability of machine learning prediction of materials properties
Neural Arithmetic Logic Units with Two Transition Matrix and Independent Gates
Engineering Applications of Artificial Intelligence · 2024-11-29
Sthefanie Jofer Gomes Passo, Vishal H. Kothavade, Wei-Ming Lin, C. Michael Walton
Read original paper ↗ ·Chemical space-property predictor model of perovskite materials by high-throughput synthesis and artificial neural networks
Chem · 2024-12-06
Md. Ataur Rahman, Md. Shahjahan, Yaqing Zhang, Rihan Wu, Elad Harel
Read original paper ↗ ·Classification-Based Detection and Quantification of Cross-Domain Data Bias in Materials Discovery
Journal of Chemical Information and Modeling · 2024-12-16
Giovanni Trezza, Eliodoro Chiavazzo
Read original paper ↗ ·Physical encoding improves OOD performance in deep learning materials property prediction
Computational Materials Science · 2024-12-19
Nihang Fu, Sadman Sadeed Omee, Jianjun Hu
Read original paper ↗ ·COBRA web application to benchmark linear regression models for catalyst optimization with few-entry datasets
Cell Reports Physical Science · 2024-12-20
Zhen Zhu Cao, Laura Falivene, Albert Poater, Bholanath Maity, Ziyung Zhang, Gentoku Takasao, Sadeed Bin Sayed, Andrea Petta, Giovanni Talarico, Romina Oliva, Luigi Cavallo
Read original paper ↗ ·Are We Overfitting to the Materials Project? A Critique of Dataset Bias in Property Prediction Benchmarks
Journal of Computational and Data-Driven Materials Engineering · 2025-01-01
Ricardo Alves, Bruno Costa, Helena Martins, Nuno Faria
Read original paper ↗ ·Assessing data-driven predictions of band gap and electrical conductivity for transparent conducting materials
Digital Discovery · 2025-01-01
Federico Ottomano, John Yannis Goulermas, Vladimir V. Gusev, Rahul Savani, Michael W. Gaultois, Troy D. Manning, Hai Lin, Teresa Partida Manzanera, Emma Poole, Matthew Stephen Dyer, John B. Claridge, Jonathan Alaria, Luke M. Daniels, Su Varma, David Rimmer, Kevin D. Sanderson, Matthew J. Rosseinsky
Read original paper ↗ ·Coherent collections of rules describing exceptional materials identified with a multi-objective optimization of subgroups
Digital Discovery · 2025-01-01
Lucas Foppa, Matthias Scheffler
Read original paper ↗ ·High throughput computational and experimental methods for accelerated electrochemical materials discovery
Journal of Materials Chemistry A · 2025-01-01
Uzoma O. Nwabara, Kunran Yang, Akshay Talekar, Varinia Bernales, Jorge González, Stuart Miller, Jeff Wu
Read original paper ↗ ·Learning Under Scarcity: A Conceptual Theory of Small-Data Regimes in Materials Artificial Intelligence
Journal of Artificial Intelligence for Materials Science · 2025-01-01
Oliver Grant, Daniel Brooks, Amelia Carter
Read original paper ↗ ·Out-of-Distribution Generalization in Materials AI: A Systematic Review of Domain Shift, Robustness, and What Remains Unsolved
Journal of Computational and Data-Driven Materials Engineering · 2025-01-01
Nikolai Ivanov, Sergey Volkov, Elena Morozova
Read original paper ↗ ·Revolutionizing infectious disease surveillance: Multi-omics technologies and AI-driven integration
Decoding Infection and Transmission · 2025-01-01
R. Aswini, B. Saranya, K. Gayathri, Karthikeyan Elumalai
Read original paper ↗ ·Predicting thermodynamic stability of inorganic compounds using ensemble machine learning based on electron configuration
Nature Communications · 2025-01-02
Hao Lin Zou, Haochen Zhao, Mingming Lu, Jiong Wang, Jiong Wang, Zeyu Deng, Jianxin Wang, Jianxin Wang
Read original paper ↗ ·Probing out-of-distribution generalization in machine learning for materials
Communications Materials · 2025-01-11
Kangming Li, Andre Niyongabo Rubungo, Xiangyun Lei, Daniel Persaud, Kamal Kumar Choudhary, Brian DeCost, Adji Bousso Dieng, Jason R. Hattrick-Simpers
Read original paper ↗ ·AI-empowered digital design of zeolites: Progress, challenges, and perspectives
APL Materials · 2025-02-01
Mengfan Wu, Shiyi Zhang, Jie Ren
Read original paper ↗ ·Improved hardness prediction for reduced-activation high-entropy alloys by incorporating symbolic regression and domain adaptation on small datasets
Journal of Materials Informatics · 2025-02-08
Hao Pan, Mingjie Zheng, Xiaochen Li, Shijun Zhao
Read original paper ↗ ·Foundation models for materials discovery – current state and future directions
npj Computational Materials · 2025-03-05
Edward O. Pyzer‐Knapp, Matteo Manica, Peter Staar, Lucas Morin, Patrick Ruch, Teodoro Laino, John R. Smith, Alessandro Curioni
Read original paper ↗ ·Machine Learning to Adaptively Predict Gold Nanorod Sizes on Different Substrates
The Journal of Physical Chemistry C · 2025-03-18
Katsuya Shiratori, Claire A. West, Zhenyang Jia, Stephen Lee, Emily A. Cook, Catherine Jones Murphy, Christy F. Landes, Stephan Link
Read original paper ↗ ·Out-of-Distribution Material Property Prediction Using Adversarial Learning
The Journal of Physical Chemistry C · 2025-03-25
Qinyang Li, Nicholas Miklaucic, Jianjun Hu
Read original paper ↗ ·Flipping the script: Predicting chemical composition in metal-halide perovskites from optical spectroscopy
Chem · 2025-03-27
Alexander J. Norquist
Read original paper ↗ ·NHC-Cracker: A Platform for the In Silico Engineering of N-Heterocyclic Carbenes for Diverse Chemical Applications
ACS Catalysis · 2025-03-27
Gentoku Takasao, Bholanath Maity, Sayan Dutta, Rajesh Kancherla, Magnus Rueping, Luigi Cavallo
Read original paper ↗ ·Electron-Informed Coarse-Graining Molecular Representation Learning for Real-World Molecular Physics
ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD) · 2025-04-04
Gyoung S. Na, Chanyoung Park
Read original paper ↗ ·High-Throughput Screening of Molecule/Polymer Photocatalysts for the Hydrogen Evolution Reaction
ACS Catalysis · 2025-04-10
Lei Shi, Alessandro Troisi
Read original paper ↗ ·Benchmarking Methods for Pointwise Reliability
Information · 2025-04-20
Cláudio Correia, Simão Paredes, Teresa Rocha, Jorge M. O. Henriques, Jorge Bernardino
Read original paper ↗ ·Using GNN property predictors as molecule generators
Nature Communications · 2025-05-08
Félix Therrien, Edward Hartley Sargent, Oleksandr Voznyy
Read original paper ↗ ·Revealing the interstitial-mediated sluggish diffusion mechanism in concentrated solid-solution alloys via machine learning-integrated kinetic Monte Carlo
Physical Review Materials · 2025-05-12
Biao Xu, Mingxuan Jiang, Shihua Ma, Jun Zhang, Yaoxu Xiong, Shasha Huang, Xuepeng Xiang, Haijun Fu, Wenyu Lu, Huiqiu Deng, Ji-Jung Kai, Shijun Zhao
Read original paper ↗ ·Quantum machine learning-based electrokinetic mining for the identification of nanoparticles and exosomes with minimal training data
Bioactive Materials · 2025-05-21
Abhimanyu Thakur, Pedro Correia Santos Bezerra, Abhishek, Shihao Zeng, Kui Zhang, Werner L. Treptow, Alan Luna, Urszula Dougherty, Akushika Kwesi, Isabella R. Huang, Christine M. Bestvina, Marina Chiara Garassino, Fuyu Duan, Yash Gokhale, Bin Duan, Yin Chen, Qizhou Lian, Marc Bissonnette, Jianpan Huang, Huanhuan Joyce Chen
Read original paper ↗ ·AI-assisted wafer-scale exfoliation and transfer of 2D materials: status, challenges and perspectives
AI for Science · 2025-06-01
Haoyu Ge, Jialin Liu, Matej Sebek, Zixuan Li, Wei Fu, Ziyu Wang, Zeng Wang
Read original paper ↗ ·Machine learning perspective: Revealing deep mechanisms and new advances in adsorption and catalysis of gaseous molecules
Applied Energy · 2025-06-05
Yue Zhu, Fengyu Gao, Lei Yi, Honghong Yi, Qingjun Yu, Shunzheng Zhao, Yuansong Zhou, Ya Wang, Xiaolong Tang
Read original paper ↗ ·Machine learning investigation of the effects of elemental doping on the mechanical properties of Fe-Cr-Ni-Al high-entropy alloys
Science China Technological Sciences · 2025-06-11
Jingteng Xue, Jingtao Huang, Zhonghong Lai, Nan Qu, Yong Liu, Jingchuan Zhu
Read original paper ↗ ·Data-driven prediction of ultimate tensile strength in low alloy steel: A machine learning approach
Computational Materials Science · 2025-06-12
Ali Mohammed Haji Shabani, Marieh Aminaei, Mohammad Reza Toroghinejad
Read original paper ↗ ·‘Intelligent’ proteins
Cellular and Molecular Life Sciences · 2025-06-14
Timir Tripathi, Vladimir Nikolaevich Uversky, Alessandro Giuliani
Read original paper ↗ ·A framework to evaluate machine learning crystal stability predictions
Nature Machine Intelligence · 2025-06-23
Janosh Riebesell, Rhys E. A. Goodall, Philipp Benner, Yuan Chiang, Bowen Deng, Gerbrand Ceder, Mark Asta, Alpha A. Lee, Anubhav Jain, Kristin Aslaug Persson
Read original paper ↗ ·Phenology-Based Maize and Soybean Yield Potential Prediction Using Machine Learning and Sentinel-2 Imagery Time-Series
Applied Sciences · 2025-06-26
Dorijan Radočaj, Ivan Plašćak, Mladen Jurišić
Read original paper ↗ ·Impact of Domain Knowledge on the Property Prediction of Specialized Machine Learning Models
ACS Materials Letters · 2025-07-01
Lin Wang, Tanjin He, Bin Ouyang
Read original paper ↗ ·Cross-material transfer learning for multiaxial fatigue prediction: A data-efficient adaptive framework
Engineering Fracture Mechanics · 2025-07-16
Peng Zhang, Anbin Wang, Keke Tang
Read original paper ↗ ·Robust surrogate modeling for glass forming process
The International Journal of Advanced Manufacturing Technology · 2025-07-19
K. E. Chang, Aabhash Dhakal, Torsten Kraft
Read original paper ↗ ·A Guide to Machine Learning Epistemic Ignorance, Hidden Paradoxes, and Other Tensions
Wiley Interdisciplinary Reviews Data Mining and Knowledge Discovery · 2025-07-23
Mohannad Zeyad Naser
Read original paper ↗ ·Out-of-Distribution Generalization on Graphs: A Survey
IEEE Transactions on Pattern Analysis and Machine Intelligence · 2025-07-31
Haoyang Li, Xin Wang, Ziwei Zhang, Wenwu Zhu
Read original paper ↗ ·Liposome stability: multifactorial regulation and optimization strategies in in vivo delivery
Journal of Liposome Research · 2025-09-21
Xiao-Si Lu, Liqing Yang, Lan Ma, Jiangfeng Wu, Hongbing Zhang, Ying Wang
Read original paper ↗ ·Evaluating the use of a machine learning simulator for structure–property prediction: A case study on disordered elastic networks
The Journal of Chemical Physics · 2025-09-24
Salman N. Salman, Sergey A. Shteingolts, Ron Levie, Dan Mendels
Read original paper ↗ ·Generalized convolutional many-body distribution functional representations
Proceedings of the National Academy of Sciences · 2025-10-06
Danish Khan, O. Anatole von Lilienfeld
Read original paper ↗ ·Machine learning in orthodontics: Transforming Invisalign treatment planning through precision, interpretability, and ethical practices
International Journal of Medical Informatics · 2025-10-11
Sanisa Trakulmututa, Khin Than Win
Read original paper ↗ ·Design and properties of ultra-hard high-entropy alloys based on machine learning and statistical feature selection
Journal of Alloys and Compounds · 2025-10-12
Peng Zeng, Siwen Tang, Haihui Wang, Yanchen Zhu, Xinpeng Chong, Hao Cheng, Feng Xiong, Meilian Gao
Read original paper ↗ ·Res-SH: Unbiased Residual Learning for Self-Healing Interface Toughness Prediction with Limited Data
IEEE Region 10 Conference (TENCON) · 2025-10-27
Pei-Sze Tan, Karen Jia-Jun Koh, Sailaja Rajanala, Arghya Pal, Raphaël C. -W. Phan, Nan Ze, Fuad M. Noman, Chee-Ming Ting, Norfadilah Dolmat, Nik Nur Wahidah Nik Hashim, A Tumian
Read original paper ↗ ·Constructing generalizable microstructure–property maps across diverse microstructure classes
MRS Communications · 2025-11-06
Hao Liu, Nirmal Baishnab, Balaji Sesha Sarath Pokuri, Baskar Ganapathysubramanian, Olga Wodo
Read original paper ↗ ·Accelerating multimetallic catalyst discovery with robotics and agentic AI
AI Agent · 2025-11-24
Jiayu Peng, Chuanyu Liu, Yiwen Luo, Kritarth Dandapat
Read original paper ↗ ·Object-based ensemble estimation of snow depth and snow water equivalent over multiple months in Sodankylä, Finland
The cryosphere · 2025-11-24
David Brodylo, Lauren Bosche, Ryan R. Busby, E. J. Deeb, Thomas Alexander Douglas, Juha Lemmetyinen
Read original paper ↗ ·SVR-RF-Transformer Ensemble for High-Precision and Full-Range Stable Thickness Measurement of SiC Epitaxial Layers
Unknown journal · 2025-12-26
Linxiang Tang, Chuxian Wu, Yulong Chen, Chen Grui Zhi, Zhen Luan, Yang Zhou
Read original paper ↗ ·Algorithmic Diversity as Scientific Robustness: A Conceptual Framework
Journal of Artificial Intelligence for Materials Science · 2026-01-01
Fernando Diaz, Lucia Morales, Diego Perez, Valeria Soto, Martin Alvarez
Read original paper ↗ ·