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OpenAlex Citation Counts

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OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

Metrics for Benchmarking and Uncertainty Quantification: Quality, Applicability, and Best Practices for Machine Learning in Chemistry
Gaurav Vishwakarma, Aditya Sonpal, Johannes Hachmann
Trends in Chemistry (2021) Vol. 3, Iss. 2, pp. 146-156
Open Access | Times Cited: 55

Showing 26-50 of 55 citing articles:

Insights into machine-learning modeling for Cr(VI) removal from contaminated water using nano-nickel hydroxide
Ibrahim Maamoun, Mostafa A. Rushdi, Omar Falyouna, et al.
Separation and Purification Technology (2022) Vol. 308, pp. 122863-122863
Closed Access | Times Cited: 15
Harnessing the power of machine learning into tissue engineering: current progress and future prospects
Yujiang Wu, Xiaotong Ding, Yiwei Wang, et al.
Burns & Trauma (2024) Vol. 12
Open Access | Times Cited: 3
Relationship between prediction accuracy and uncertainty in compound potency prediction using deep neural networks and control models
Jannik P. Roth, Jürgen Bajorath
Scientific Reports (2024) Vol. 14, Iss. 1
Open Access | Times Cited: 2
Exploring explainable ensemble machine learning methods for long-term performance prediction of industrial gas turbines: A comparative analysis
Seyyed Ahmad Naghibi
Engineering Applications of Artificial Intelligence (2024) Vol. 138, pp. 109318-109318
Closed Access | Times Cited: 2
Uncertainty quantification of a deep learning fuel property prediction model
Kiran K. Yalamanchi, Sahil Kommalapati, Pinaki Pal, et al.
Applications in Energy and Combustion Science (2023) Vol. 16, pp. 100211-100211
Open Access | Times Cited: 6
High-throughput screening of tribological properties of monolayer films using molecular dynamics and machine learning
Co D. Quach, Justin Gilmer, Daniel Pert, et al.
The Journal of Chemical Physics (2022) Vol. 156, Iss. 15
Open Access | Times Cited: 9
Identification of High-Reliability Regions of Machine Learning Predictions Based on Materials Chemistry
Evan M. Askenazi, Emanuel A. Lazar, Ilya Grinberg
Journal of Chemical Information and Modeling (2023) Vol. 63, Iss. 23, pp. 7350-7362
Closed Access | Times Cited: 4
Building robust machine learning models for small chemical science data: the case of shear viscosity of fluids
Nikhil V. S. Avula, Shivanand Kumar Veesam, Sudarshan Behera, et al.
Machine Learning Science and Technology (2022) Vol. 3, Iss. 4, pp. 045032-045032
Open Access | Times Cited: 7
Learning Design Rules for Catalysts Through Computational Chemistry and Machine Learning
Aditya Nandy, Heather J. Kulik
(2024), pp. 513-558
Closed Access | Times Cited: 1
In silico drug repurposing by combining machine learning classification model and molecular dynamics to identify a potential OGT inhibitor
Pedro Henrique Rodrigues de Alencar Azevedo, Bruna Rachel de Britto Peçanha, Luiz A.P. Flores-Junior, et al.
Journal of Biomolecular Structure and Dynamics (2023) Vol. 42, Iss. 3, pp. 1417-1428
Closed Access | Times Cited: 3
A View on Model Misspecification in Uncertainty Quantification
Yuko Kato, David M. J. Tax, Marco Loog
Communications in computer and information science (2023), pp. 65-77
Closed Access | Times Cited: 3
Calibration in machine learning uncertainty quantification: Beyond consistency to target adaptivity
Pascal Pernot
APL Machine Learning (2023) Vol. 1, Iss. 4
Open Access | Times Cited: 3
Spatial distribution as a key factor for evaluation of soil attributes prediction at field level using online near-infrared spectroscopy
Ricardo Canal Filho, José Paulo Molin
Frontiers in Soil Science (2022) Vol. 2
Open Access | Times Cited: 4
Liquid Organic Hydrogen Carriers: High-throughput Screening of Homogeneous Catalysts
Gaurav Vishwakarma, Johannes Hachmann
(2023)
Open Access | Times Cited: 1
Soil Attributes Mapping with Online Near-Infrared Spectroscopy Requires Spatio-Temporal Local Calibrations
Ricardo Canal Filho, José Paulo Molin, Marcelo Chan Fu Wei, et al.
AgriEngineering (2023) Vol. 5, Iss. 3, pp. 1163-1177
Open Access | Times Cited: 1
Prediction of Supercapacitor Performance for Cobalt Oxide and Its Derivatives using Machine Learning Techniques
Shraddha Shukla, Manikandan
Research Square (Research Square) (2024)
Open Access
Tailored Convolutional Neural Network for Brain Tumor Detection Using Self-attention and Spatial Attention Mechanisms
Raed Alsini
(2024) Vol. 314, pp. 1-6
Closed Access
High-Throughput Reaction Discovery for Cs-Pb-Br Nanocrystal Synthesis
Ricki Chairil, Allison P. Forsberg, Richard L. Brutchey, et al.
Reaction Chemistry & Engineering (2024)
Closed Access
Benchmarking Machine Learning Descriptors for Crystals
Aditya Sonpal, Mohammad Atif Faiz Afzal, Yuling An, et al.
ACS symposium series (2022), pp. 111-126
Closed Access | Times Cited: 2
Heuristics and Uncertainty Quantification in Rational and Inverse Compound and Catalyst Design
Thomas Weymuth, Markus Reiher
Elsevier eBooks (2022), pp. 485-495
Open Access | Times Cited: 1
Online near-infrared spectroscopy for soil attributes prediction
Ricardo Canal Filho
(2023)
Open Access
Soft Metrology
Marcela Vallejo, Nelson Bahamón, Laura Rossi, et al.
(2023), pp. 1239-1269
Closed Access
Power Station Engine Failure Early Warning System Using Thermal Camera
Alfian Akbar Gozali
Jurnal Penelitian Pendidikan IPA (2023) Vol. 9, Iss. 8, pp. 6590-6596
Open Access
Calibration in Machine Learning Uncertainty Quantification: beyond consistency to target adaptivity
Pascal Pernot
arXiv (Cornell University) (2023)
Open Access
Enhancing Long-Term Performance Forecasting for Gas Turbines: An In-Depth Exploration of Ensemble Machine Learning Methods
Ahmad Naghibi
(2023)
Closed Access

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