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RESEARCH PAPER · Machine Learning Science and Technology · 2021

Scientific intuition inspired by machine learning-generated hypotheses

Pascal Friederich, Mario Krenn, Isaac Tamblyn, Alán Aspuru‐Guzik

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42 direct citing works

Scientific intuition inspired by machine learning-generated hypothesesOriginalTrends in computational molecular catalyst design27Нейросетевое моделирование интуиции0Prediction of Chromatography Conditions for Purification in Organic Synthesis Using Deep Learning18Nanoparticle synthesis assisted by machine learning545Rechargeable Batteries of the Future—The State of the Art from a BATTERY 2030+ Perspective376A Comprehensive Discovery Platform for Organophosphorus Ligands for Catalysis309Modeling the Solid Electrolyte Interphase: Machine Learning as a Game Changer?87Autonomous high-throughput computations in catalysis29Evaluation guidelines for machine learning tools in the chemical sciences180Materiomically Designed Polymeric Vehicles for Nucleic Acids: Quo Vadis?18Computational Catalyst Design for Dry Reforming of Methane: A Review40On scientific understanding with artificial intelligence372Text‐based representations with interpretable machine learning reveal structure–property relationships of polybenzenoid hydrocarbons18COVID-19 Vaccination Intention and Factors Associated with Hesitance and Resistance in the Deep South: Montgomery, Alabama5Graph neural networks for materials science and chemistry860MEGAN: Multi-explanation Graph Attention Network6Knowledge-integrated machine learning for materials: lessons from gameplaying and robotics137Interpretable Deep-Learning Unveils Structure–Property Relationships in Polybenzenoid Hydrocarbons24PREFMoDeL: A Systematic Review and Proposed Taxonomy of Biomolecular Features for Deep Learning0Sizing up feature descriptors for macromolecular machine learning with polymeric biomaterials37Towards Hypothesis Generation for mHealth Applications: A Data Driven Approach1Using an Interpretable Amino Acid-Based Machine Learning Method to Enhance the Diagnosis of Major Depressive Disorder5SCIHYPO - A Deep Learning Framework for Data-Driven Scientific Hypothesis Generation from Extensive Literature Analysis1Comparative optimization of polysaccharide-based nanoformulations for cardiac RNAi therapy25AI-driven research in pure mathematics and theoretical physics15The Artificial Intelligence-Powered New Era in Pharmaceutical Research and Development: A Review77The Silicon Architect: Transformation Towards a Data-Centric Mindset2What values best distinguish the world's cultures? The machine learning-based cultural values inventory0Dataism, skepticism, and intuition for interpretable machine learning2Mars rovers serve as scientists’ eyes and ears from millions of miles away – here are the tools Perseverance used to spot a potential sign of ancient life0Gaining scientific understanding with small data machine learning: explainable molecule representations and their consensus2

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  1. Trends in computational molecular catalyst design

    Dalton Transactions · 2021-01-01

    Ademola Soyemi, Tibor Szilvási

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  2. Нейросетевое моделирование интуиции

    Естественные и Технические Науки · 2021-01-01

    Силун Сунь

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  3. Prediction of Chromatography Conditions for Purification in Organic Synthesis Using Deep Learning

    Molecules · 2021-04-23

    Mantas Vaškevičius, Jurgita Kapočiūtė-Dzikienė, Liudas Šlepikas

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  4. Nanoparticle synthesis assisted by machine learning

    Nature Reviews Materials · 2021-07-13

    Huachen Tao, Tianyi Wu, Matteo Aldeghi, Tony Wu, Alán Aspuru‐Guzik, Eugenia Kumacheva

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  5. Rechargeable Batteries of the Future—The State of the Art from a BATTERY 2030+ Perspective

    Advanced Energy Materials · 2021-12-05

    Maximilian Fichtner, Kristina Edström, Elixabete Ayerbe, Maitane Berecibar, Arghya Bhowmik, Ivano E. Castelli, Simon Clark, Robert Dominko, Merve Erakca, Alejandro A. Franco, Alexis Grimaud, Birger Horstmann, Arnulf Latz, Henning Lorrmann, Marcel Meeus, Rekha Narayan, Frank Pammer, Janna Ruhland, Helge Sören Stein, Tejs Vegge, Marcel Weil

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  6. A Comprehensive Discovery Platform for Organophosphorus Ligands for Catalysis

    Journal of the American Chemical Society · 2022-01-12

    Tobias Gensch, Gabe Gomes, Pascal Friederich, Ellyn Peters, Théophile Gaudin, Robert Pollice, Kjell Jorner, AkshatKumar Nigam, Michael Lindner-D’Addario, Matthew S. Sigman, Alán Aspuru‐Guzik

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  7. Modeling the Solid Electrolyte Interphase: Machine Learning as a Game Changer?

    Advanced Materials Interfaces · 2022-01-30

    Diddo Diddens, Williams Agyei Appiah, Youssef Mabrouk, Andreas Heuer, Tejs Vegge, Arghya Bhowmik

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  8. Autonomous high-throughput computations in catalysis

    Chem Catalysis · 2022-03-14

    Stephan N. Steinmann, Angga Hermawan, Mohammed Bin Jassar, Zhi Wei Seh

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  9. Evaluation guidelines for machine learning tools in the chemical sciences

    Nature Reviews Chemistry · 2022-05-24

    Andreas Bender, Nadine Schneider, Marwin Segler, W. Patrick Walters, Ola Engkvist, Tiago Rodrigues

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  10. Materiomically Designed Polymeric Vehicles for Nucleic Acids: Quo Vadis?

    ACS Applied Bio Materials · 2022-06-01

    Ramya Kumar

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  11. Computational Catalyst Design for Dry Reforming of Methane: A Review

    Energy & Fuels · 2022-08-22

    Yeongjun Yoon, Hyo Min You, Hyung Jun Kim, Matthew T. Curnan, Kyeounghak Kim, Jeong Woo Han

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  12. On scientific understanding with artificial intelligence

    Nature Reviews Physics · 2022-10-11

    Mario Krenn, Robert Pollice, Si Yue Guo, Matteo Aldeghi, Alba Cervera-Lierta, Pascal Friederich, Gabe Gomes, Florian Häse, Adrián Jinich, AkshatKumar Nigam, Zhenpeng Yao, Alán Aspuru‐Guzik

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  13. Text‐based representations with interpretable machine learning reveal structure–property relationships of polybenzenoid hydrocarbons

    Journal of Physical Organic Chemistry · 2022-10-17

    Shachar Fite, Alexandra Wahab, Eno Paenurk, Zeev Gross, Renana Gershoni‐Poranne

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  14. COVID-19 Vaccination Intention and Factors Associated with Hesitance and Resistance in the Deep South: Montgomery, Alabama

    Tropical Medicine and Infectious Disease · 2022-10-25

    Cicily A. Gray, Grace Lesser, Yuqi Guo, Swapn Shah, Shauntice Allen, Larrell L. Wilkinson, Omar T. Sims

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  15. Graph neural networks for materials science and chemistry

    Communications Materials · 2022-11-26

    Patrick Reiser, Marlen Neubert, André Eberhard, Luca Torresi, Chen Zhou, Chen Shao, Houssam Metni, Clint van Hoesel, Henrik Schopmans, Timo Sommer, Pascal Friederich

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  16. MEGAN: Multi-explanation Graph Attention Network

    Communications in computer and information science · 2023-01-01

    Jonas Teufel, Luca Torresi, Patrick Reiser, Pascal Friederich

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  17. Knowledge-integrated machine learning for materials: lessons from gameplaying and robotics

    Nature Reviews Materials · 2023-01-24

    Kedar Hippalgaonkar, Qianxiao Li, Xiaonan Wang, John Sheridan Fisher, James Kirkpatrick, Tonio Buonassisi

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  18. Interpretable Deep-Learning Unveils Structure–Property Relationships in Polybenzenoid Hydrocarbons

    The Journal of Organic Chemistry · 2023-01-25

    Tomer Weiss, Alexandra Wahab, Alex M. Bronstein, Renana Gershoni‐Poranne

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  19. PREFMoDeL: A Systematic Review and Proposed Taxonomy of Biomolecular Features for Deep Learning

    Applied Sciences · 2023-03-29

    Jacob L. North, Victor L. Hsu

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  20. Sizing up feature descriptors for macromolecular machine learning with polymeric biomaterials

    npj Computational Materials · 2023-06-12

    Samantha Stuart, Jeffrey Watchorn, Frank Gu

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  21. Towards Hypothesis Generation for mHealth Applications: A Data Driven Approach

    IFIP advances in information and communication technology · 2023-12-12

    Vibha Prabhu, Rajesh R. Pai, N. Sumith

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  22. Using an Interpretable Amino Acid-Based Machine Learning Method to Enhance the Diagnosis of Major Depressive Disorder

    Journal of Clinical Medicine · 2024-02-21

    Cyrus S. H. Ho, Trevor Wei Kiat Tan, Howard Cai Hao Khoe, Yee Ling Chan, Gabrielle Wann Nii Tay, Tong Boon Tang

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  23. SCIHYPO - A Deep Learning Framework for Data-Driven Scientific Hypothesis Generation from Extensive Literature Analysis

    International Conference on Expert Clouds and Applications (ICOECA) · 2024-04-18

    Mothilal Tadiparthi, Sindhu Pasupuleti, Sita Venkata Sathwika Talluri, Subramanyam Raju Sangaraju, Manikanta Mogili

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  24. Comparative optimization of polysaccharide-based nanoformulations for cardiac RNAi therapy

    Nature Communications · 2024-06-26

    Han Jie Gao, Sen Li, Zhengyi Lan, Da Pan, Gonna Somu Naidu, Dan Peer, Chenyi Ye, Hangrong Chen, Ming Ma, Zehua Liu, Hélder A. Santos

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  25. AI-driven research in pure mathematics and theoretical physics

    Nature Reviews Physics · 2024-08-05

    Yang‐Hui He

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  26. The Artificial Intelligence-Powered New Era in Pharmaceutical Research and Development: A Review

    AAPS PharmSciTech · 2024-08-15

    Phuvamin Suriyaamporn, Boonnada Pamornpathomkul, Prasopchai Patrojanasophon, Tanasait Ngawhirunpat, Theerasak Rojanarata, Praneet Opanasopit

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  27. The Silicon Architect: Transformation Towards a Data-Centric Mindset

    Journal of Architectural/Planning Research and Studies (JARS) · 2024-10-01

    Wasin Kemkomnerd, Chamnarn Tirapas

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  28. What values best distinguish the world's cultures? The machine learning-based cultural values inventory

    PNAS Nexus · 2025-07-31

    Abhishek Sheetal, Shilpa Madan, Rui Ling Lee, Krishna Savani

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  29. Dataism, skepticism, and intuition for interpretable machine learning

    AI and Ethics · 2025-08-28

    Mohannad Zeyad Naser

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  30. Mars rovers serve as scientists’ eyes and ears from millions of miles away – here are the tools Perseverance used to spot a potential sign of ancient life

    Unknown journal · 2025-09-17

    Ari Koeppel

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  31. Gaining scientific understanding with small data machine learning: explainable molecule representations and their consensus

    npj Materials Degradation · 2025-12-12

    Can Özkan, Lisa Sahlmann, Tim Würger, Christian Feiler, Sviatlana V. Lamaka, Mikhail L. Zheludkevich, Peyman Taheri, J.M.C. Mol

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