Standout Papers

Interpretable and Explainable Machine Learning for Materials Science and Chemistry 2022 2026 2023 2024156
  1. Interpretable and Explainable Machine Learning for Materials Science and Chemistry (2022)
    Felipe Oviedo, Juan Lavista Ferres et al. Accounts of Materials Research

Immediate Impact

24 from Science/Nature 64 standout
Sub-graph 1 of 22

Citing Papers

Nonalloyed α-phase formamidinium lead triiodide solar cells through iodine intercalation
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A review of machine learning applications in polymer composites: advancements, challenges, and future prospects
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1 intermediate paper

Works of Felipe Oviedo being referenced

Interpretable and Explainable Machine Learning for Materials Science and Chemistry
2022 Standout
Accelerated Development of Perovskite-Inspired Materials via High-Throughput Synthesis and Machine-Learning Diagnosis
2019

Author Peers

Author Last Decade Papers Cites
Felipe Oviedo 804 483 130 162 27 1.2k
Siyu Tian 630 363 84 94 41 1.3k
Edward O. Pyzer‐Knapp 890 236 219 332 40 1.5k
Yong Zhao 591 226 80 148 33 1.1k
Weike Ye 1185 430 93 331 14 1.5k
Leigh Weston 1060 372 96 150 16 1.4k
Gabriel R. Schleder 893 325 113 102 45 1.5k
Anna M. Hiszpanski 685 515 49 112 35 1.2k
Christoph Kreisbeck 814 332 311 266 25 1.6k
Sorelle A. Friedler 881 254 73 209 12 1.4k
Xiangyu Sun 621 397 90 63 35 1.1k

All Works

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2026