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Nature Machine Intelligence
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2019~2025
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2024, vol.6, no.1
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2024, vol.6, no.2
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年卷期
AI protein shake-up
Nature Machine Intelligence
2024
2024, vol.6, no.2
What comparing deep neural networks can teach us about human vision
Katja Seeliger; Martin N. Hebart
2024
2024, vol.6, no.2
Neural multi-task learning in drug design
Stephan Allenspach; Jan A. Hiss; Gisbert Schneider
2024
2024, vol.6, no.2
A causal perspective on dataset bias in machine learning for medical imaging
Charles Jones; Daniel C. Castro; Fabio De Sousa Ribeiro; Ozan Oktay; Melissa McCradden; Ben Glocker
2024
2024, vol.6, no.2
Variational autoencoder for design of synthetic viral vector serotypes
Suyue Lyu; Shahin Sowlati-Hashjin; Michael Garton
2024
2024, vol.6, no.2
Leveraging large language models for predictive chemistry
Kevin Maik Jablonka; Philippe Schwaller; Andres Ortega-Guerrero; Berend Smit
2024
2024, vol.6, no.2
Codon language embeddings provide strong signals for use in protein engineering
Carlos Outeiral; Charlotte M. Deane
2024
2024, vol.6, no.2
Weak signal extraction enabled by deep neural network denoising of diffraction data
Jens Oppliger; M. Michael Denner; Julia Kuspert; Ruggero Frison; Qisi Wang; Alexander Morawietz; Oleh Ivashko; Ann-Christin Dippel; Martin von Zimmermann; Izabela Bialo; Leonardo Martinelli; Benoit Fauque; Jaewon Choi; Mirian Garcia-Fernandez; Ke-Jin Zhou; Niels Bech Christensen; Tohru Kurosawa; Naoki Momono; Migaku Oda; Fabian D. Natterer; Mark H. Fischer; Titus Neupert; Johan Chang
2024
2024, vol.6, no.2
Mitigating allocative tradeoffs and harms in an environmental justice data tool
Benjamin Q. Huynh; Elizabeth T. Chin; Allison Koenecke; Derek Ouyang; Daniel E. Ho; Mathew V. Kiang; David H. Rehkopf
2024
2024, vol.6, no.2
State-specific protein-ligand complex structure prediction with a multiscale deep generative model
Zhuoran Qiao; Weili Nie; Arash Vahdat; Thomas F. Miller III; Animashree Anandkumar
2024
2024, vol.6, no.2
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