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Nature machine intelligence

Showing results (121-130 of 148) with videos related to

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Nature Machine Intelligence|June 26, 2025
Dimensions underlying the representational alignment of deep neural networks with humansFlorian P Mahner, Lukas Muttenthaler, Umut Güçlü, et al.
Nature Machine Intelligence|October 27, 2025
Resolving data bias improves generalization in binding affinity predictionDavid Graber, Peter Stockinger, Fabian Meyer, et al.
Nature Machine Intelligence|November 9, 2020
Quantum approximate Bayesian computation for NMR model inferenceDries Sels, Hesam Dashti, Samia Mora, et al.
Nature Machine Intelligence|December 26, 2022
Deep learning models for predicting RNA degradation via dual crowdsourcingHannah K Wayment-Steele, Wipapat Kladwang, Andrew M Watkins, et al.
Nature Machine Intelligence|July 29, 2021
Improving representations of genomic sequence motifs in convolutional networks with exponential activationsPeter K Koo, Matt Ploenzke
Nature Machine Intelligence|November 27, 2020
Competitive performance of a modularized deep neural network compared to commercial algorithms for low-dose CT image reconstructionHongming Shan, Atul Padole, Fatemeh Homayounieh, et al.
Nature Machine Intelligence|July 22, 2021
A neural network trained for prediction mimics diverse features of biological neurons and perceptionWilliam Lotter, Gabriel Kreiman, David Cox
Nature Machine Intelligence|May 23, 2022
Stop Explaining Black Box Machine Learning Models for High Stakes Decisions and Use Interpretable Models InsteadCynthia Rudin
Nature Machine Intelligence|August 10, 2019
Educational strategies to foster diversity and inclusion in machine intelligenceShannon Wongvibulsin
Nature Machine Intelligence|October 22, 2021
A Versatile Deep Learning Architecture for Classification and Label-Free Prediction of Hyperspectral ImagesBryce Manifold, Shuaiqian Men, Ruoqian Hu, et al.
Pageof 15

Showing results (121-130 of 148) with videos related to

Sort By:
Pageof 15
Nature Machine Intelligence|June 26, 2025
Dimensions underlying the representational alignment of deep neural networks with humansFlorian P Mahner, Lukas Muttenthaler, Umut Güçlü, et al.
Nature Machine Intelligence|October 27, 2025
Resolving data bias improves generalization in binding affinity predictionDavid Graber, Peter Stockinger, Fabian Meyer, et al.
Nature Machine Intelligence|November 9, 2020
Quantum approximate Bayesian computation for NMR model inferenceDries Sels, Hesam Dashti, Samia Mora, et al.
Nature Machine Intelligence|December 26, 2022
Deep learning models for predicting RNA degradation via dual crowdsourcingHannah K Wayment-Steele, Wipapat Kladwang, Andrew M Watkins, et al.
Nature Machine Intelligence|July 29, 2021
Improving representations of genomic sequence motifs in convolutional networks with exponential activationsPeter K Koo, Matt Ploenzke
Nature Machine Intelligence|November 27, 2020
Competitive performance of a modularized deep neural network compared to commercial algorithms for low-dose CT image reconstructionHongming Shan, Atul Padole, Fatemeh Homayounieh, et al.
Nature Machine Intelligence|July 22, 2021
A neural network trained for prediction mimics diverse features of biological neurons and perceptionWilliam Lotter, Gabriel Kreiman, David Cox
Nature Machine Intelligence|May 23, 2022
Stop Explaining Black Box Machine Learning Models for High Stakes Decisions and Use Interpretable Models InsteadCynthia Rudin
Nature Machine Intelligence|August 10, 2019
Educational strategies to foster diversity and inclusion in machine intelligenceShannon Wongvibulsin
Nature Machine Intelligence|October 22, 2021
A Versatile Deep Learning Architecture for Classification and Label-Free Prediction of Hyperspectral ImagesBryce Manifold, Shuaiqian Men, Ruoqian Hu, et al.
Pageof 15