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RESEARCH PAPER · Digital Discovery · 2022

Bayesian optimization in continuous spaces via virtual process embeddings

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

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

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42 direct citing works

Bayesian optimization in continuous spaces via virtual process embeddingsOriginalThe decade of artificial intelligence in chemistry and materials6Optimizing training trajectories in variational autoencoders via latent Bayesian optimization approach *13Mechanisms of Biomolecular Self‐Assembly Investigated Through In Situ Observations of Structures and Dynamics36Mechanisms of Biomolecular Self‐Assembly Investigated Through In Situ Observations of Structures and Dynamics2Deep kernel methods learn better: from cards to process optimization8A dynamic Bayesian optimized active recommender system for curiosity-driven partially Human-in-the-loop automated experiments45The amorphous state as a frontier in computational materials design74Machine-learning-guided design of electroanalytical pulse waveforms15Active deep kernel learning of molecular properties from structural embeddings1Physically constrained autoencoder-assisted Bayesian optimization for refinement of high-dimensional defect-sensitive single crystalline structure1Toward predictable hydrochar properties at scale: a critical review of design of experiments-guided machine learning in hydrothermal carbonization0

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11 direct citing papers saved.

  1. The decade of artificial intelligence in chemistry and materials

    Digital Discovery · 2023-01-01

    Alán Aspuru‐Guzik

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  2. Optimizing training trajectories in variational autoencoders via latent Bayesian optimization approach *

    Machine Learning Science and Technology · 2023-01-13

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

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  3. Mechanisms of Biomolecular Self‐Assembly Investigated Through In Situ Observations of Structures and Dynamics

    Angewandte Chemie International Edition · 2023-09-13

    Sakshi B. Yadav, Kacper J. Lachowski, Huat Thart Chiang, Lilo D. Pozzo, Jim De Yoreo, Shuai Zhang

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  4. Mechanisms of Biomolecular Self‐Assembly Investigated Through In Situ Observations of Structures and Dynamics

    Angewandte Chemie · 2023-09-13

    Sakshi B. Yadav, Kacper J. Lachowski, Huat Thart Chiang, Lilo D. Pozzo, Jim De Yoreo, Shuai Zhang

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  5. Deep kernel methods learn better: from cards to process optimization

    Machine Learning Science and Technology · 2024-01-03

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

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  6. A dynamic Bayesian optimized active recommender system for curiosity-driven partially Human-in-the-loop automated experiments

    npj Computational Materials · 2024-02-03

    Arpan Biswas, Yongtao Liu, Nicole Creange, Yuchen Liu, Stephen Jesse, Jan‐Chi Yang, Sergei V. Kalinin, Maxim A Ziatdinov, Rama Krishnan Vasudevan

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  7. The amorphous state as a frontier in computational materials design

    Nature Reviews Materials · 2024-12-16

    Yuanbin Liu, Ata Madanchi, Andy S. Anker, Lena Simine, Volker L. Deringer

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  8. Machine-learning-guided design of electroanalytical pulse waveforms

    Digital Discovery · 2025-01-01

    Cameron S. Movassaghi, Katie A. Perrotta, Maya E. Curry, Audrey N. Nashner, K. Nguyen, Mila E. Wesely, Miguel Alcañiz-Fillol, Chong Liu, Aaron S. Meyer, Anne Milasincic Andrews

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  9. Active deep kernel learning of molecular properties from structural embeddings

    APL Machine Learning · 2025-10-22

    Ayana Ghosh, Maxim A Ziatdinov, Sergei V. Kalinin

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  10. Physically constrained autoencoder-assisted Bayesian optimization for refinement of high-dimensional defect-sensitive single crystalline structure

    APL Machine Learning · 2026-06-01

    Joseph Oche Agada, Andrew McAninch, Haley A. Day, Yasemin Tanyu, Ewan McCombs, S. M. Koohpayeh, Brian H. Toby, Yishu Wang, Arpan Biswas

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  11. Toward predictable hydrochar properties at scale: a critical review of design of experiments-guided machine learning in hydrothermal carbonization

    Frontiers in Chemical Engineering · 2026-08-18

    Faiçal El Ouadrhiri, Amal Lahkimi

    Read original paper ↗ ·
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