Standout Papers

Systematic softening in universal machine lea... 2023 2026 2024352
  1. Systematic softening in universal machine learning interatomic potentials (2025)
    Bowen Deng, Peichen Zhong et al. npj Computational Materials
  2. CHGNet as a pretrained universal neural network potential for charge-informed atomistic modelling (2023)
    Bowen Deng, Peichen Zhong et al. Nature Machine Intelligence
  3. A framework to evaluate machine learning crystal stability predictions (2025)
    Janosh Riebesell, Rhys E. A. Goodall et al. Nature Machine Intelligence

Immediate Impact

5 standout
Sub-graph 1 of 3

Citing Papers

Integrating artificial intelligence in energy transition: A comprehensive review
2025 Standout
A review of machine learning applications in polymer composites: advancements, challenges, and future prospects
2025 Standout
2 intermediate papers

Works of Janosh Riebesell being referenced

CHGNet as a pretrained universal neural network potential for charge-informed atomistic modelling
2023 Standout

Author Peers

Author Last Decade Papers Cites
Janosh Riebesell 334 6 6 118 68 6 425
Kevin Tibbetts 329 2 6 101 61 5 432
Anthony Wang 384 7 4 102 86 5 488
Henning Glawe 379 3 3 77 123 5 453
Cher Tian Ser 264 29 4 111 81 4 422
Max C. Gallant 256 31 4 103 38 8 396
Marcus Schwarting 270 22 2 80 44 14 373
Bernardus Rendy 231 33 4 100 38 6 374
Henrik Schopmans 255 2 4 63 124 7 378
Luca Torresi 254 9 4 80 130 5 397
David Milsted 230 33 4 92 38 4 384

All Works

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2026