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RESEARCH PAPER · Machine Learning Science and Technology · 2023

Role of multifidelity data in sequential active learning materials discovery campaigns: case study of electronic bandgap

Ryan M. Jacobs, Philip E. Goins, Dane D. Morgan

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7 direct citing papers in this saved network. Explore the next layer with second-order citations.

Open in your workspace →Saved 2026-10-14 · complete coverage
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Role of multifidelity data in sequential active learning materials discovery campaigns: case study of electronic bandgapOriginalWhen Optimization Conflicts with Discovery: A Conceptual Tension in Materials AI0Toward Accelerating Discovery via Physics-Driven and Interactive Multifidelity Bayesian Optimization3Machine learning materials properties with accurate predictions, uncertainty estimates, domain guidance, and persistent online accessibility17Discovering novel halide perovskites using generative adversarial networks and random forest regression4Best practices for multi-fidelity Bayesian optimization in materials and molecular research30Experimental Data Integration into ML Workflows for Real Alloys: A Review of Noisy, Sparse, and Heterogeneous Fusion0Predicting Materials Using Variational Autoencoders: A Systematic Literature Review8

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  1. When Optimization Conflicts with Discovery: A Conceptual Tension in Materials AI

    Journal of Artificial Intelligence for Materials Science · 2023-01-01

    Wei Liu, Zhang Min

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  2. Toward Accelerating Discovery via Physics-Driven and Interactive Multifidelity Bayesian Optimization

    Journal of Computing and Information Science in Engineering · 2024-10-14

    Arpan Biswas, Mani Valleti, Rama Krishnan Vasudevan, Maxim A Ziatdinov, Sergei V. Kalinin

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  3. Machine learning materials properties with accurate predictions, uncertainty estimates, domain guidance, and persistent online accessibility

    Machine Learning Science and Technology · 2024-12-01

    Ryan M. Jacobs, Lane E. Schultz, Aristana Scourtas, K. J. Schmidt, Owen Price-Skelly, Will Engler, Ian T Foster, Ben J. Blaiszik, Paul M. Voyles, Dane D. Morgan

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  4. Discovering novel halide perovskites using generative adversarial networks and random forest regression

    Computational Materials Science · 2025-06-22

    Ishaanvi Agrawal, Maitreyo Biswas, Arun Mannodi‐Kanakkithodi

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  5. Best practices for multi-fidelity Bayesian optimization in materials and molecular research

    Nature Computational Science · 2025-07-23

    Victor Sabanza Gil, Riccardo Barbano, Daniel Pacheco Gutiérrez, Jeremy S. Luterbacher, José Miguel Hernández-Lobato, Philippe Schwaller, Loı̈c M. Roch

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  6. Experimental Data Integration into ML Workflows for Real Alloys: A Review of Noisy, Sparse, and Heterogeneous Fusion

    Journal of Computational and Data-Driven Materials Engineering · 2026-01-01

    Hassan Rahman, Tariq Mahmood, Ali Raza

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  7. Predicting Materials Using Variational Autoencoders: A Systematic Literature Review

    Archives of Computational Methods in Engineering · 2026-01-07

    Mohammad Mazedul Islam, T. M. A. Iqbal Bin Belal, Md. Arif Hossain Chowdhury Anik, Ahmed Sharif

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