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Thalamocortical dysrhythmia detected by machine learning

Nature communications, 2018-03, Vol.9 (1), p.1103-13, Article 1103

2018

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Fair Learning

Texas law review, 2021-03, Vol.99 (4), p.743-785

2021

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Chemical shifts in molecular solids by machine learning

Nature communications, 2018-10, Vol.9 (1), p.4501-10, Article 4501

2018

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Reconstructing Earth’s atmospheric oxygenation history using machine learning

Nature communications, 2022-10, Vol.13 (1), p.5862-5862, Article 5862

2022

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Physical deep learning with biologically inspired training method: gradient-free approach for physical hardware

Nature communications, 2022-12, Vol.13 (1), p.7847-7847, Article 7847

2022

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Efficient and self-adaptive in-situ learning in multilayer memristor neural networks

Nature communications, 2018-06, Vol.9 (1), p.2385-8, Article 2385

2018

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Discovery of senolytics using machine learning

Nature communications, 2023-06, Vol.14 (1), p.3445-3445, Article 3445

2023

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Differentially private knowledge transfer for federated learning

Nature communications, 2023-06, Vol.14 (1), p.3785-3785, Article 3785

2023

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Deep learning in mental health outcome research: a scoping review

Translational psychiatry, 2020-04, Vol.10 (1), p.116-116, Article 116

2020

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Photonic machine learning with on-chip diffractive optics

Nature communications, 2023-01, Vol.14 (1), p.70-70, Article 70

2023

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A solution to the learning dilemma for recurrent networks of spiking neurons

Nature communications, 2020-07, Vol.11 (1), p.3625-3625, Article 3625

2020

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Brain-inspired global-local learning incorporated with neuromorphic computing

Nature communications, 2022-01, Vol.13 (1), p.65-65, Article 65

2022

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Machine learning: remember the fundamentals

Pediatric research, 2023-01, Vol.93 (2), p.291-292

2023

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Clinically applicable histopathological diagnosis system for gastric cancer detection using deep learning

Nature communications, 2020-08, Vol.11 (1), p.4294-4294, Article 4294

2020

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Integrating deep learning CT-scan model, biological and clinical variables to predict severity of COVID-19 patients

Nature communications, 2021-01, Vol.12 (1), p.634-11, Article 634

2021

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Experimental search for high-temperature ferroelectric perovskites guided by two-step machine learning

Nature communications, 2018-04, Vol.9 (1), p.1668-9, Article 1668

2018

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Learning few-shot imitation as cultural transmission

Nature communications, 2023-11, Vol.14 (1), p.7536-7536, Article 7536

2023

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Machine Learning in Dermatology: Current Applications, Opportunities, and Limitations

Dermatology and therapy, 2020-06, Vol.10 (3), p.365-386

2020

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Clustering earthquake signals and background noises in continuous seismic data with unsupervised deep learning

Nature communications, 2020-08, Vol.11 (1), p.3972-3972, Article 3972

2020

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Accurate recognition of colorectal cancer with semi-supervised deep learning on pathological images

Nature communications, 2021-11, Vol.12 (1), p.6311-6311, Article 6311

2021

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Combining machine learning and nanopore construction creates an artificial intelligence nanopore for coronavirus detection

Nature communications, 2021-06, Vol.12 (1), p.3726-3726, Article 3726

2021

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Machine learning analysis of extreme events in optical fibre modulation instability

Nature communications, 2018-11, Vol.9 (1), p.4923-11, Article 4923

2018

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Clinical applications of artificial intelligence and machine learning in cancer diagnosis: looking into the future

Cancer cell international, 2021-05, Vol.21 (1), p.1-270, Article 270

2021

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Machine learning and structural analysis of Mycobacterium tuberculosis pan-genome identifies genetic signatures of antibiotic resistance

Nature communications, 2018-10, Vol.9 (1), p.4306-9, Article 4306

2018

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Deep Learning for Drug Design: an Artificial Intelligence Paradigm for Drug Discovery in the Big Data Era

The AAPS journal, 2018-03, Vol.20 (3), p.58-58, Article 58

2018

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Thalamocortical dysrhythmia detected by machine learning

Fair Learning

Chemical shifts in molecular solids by machine learning

Reconstructing Earth’s atmospheric oxygenation history using machine learning

Physical deep learning with biologically inspired training method: gradient-free approach for physical hardware

Efficient and self-adaptive in-situ learning in multilayer memristor neural networks

Discovery of senolytics using machine learning

Differentially private knowledge transfer for federated learning

Deep learning in mental health outcome research: a scoping review

Photonic machine learning with on-chip diffractive optics

A solution to the learning dilemma for recurrent networks of spiking neurons

Brain-inspired global-local learning incorporated with neuromorphic computing

Machine learning: remember the fundamentals

Clinically applicable histopathological diagnosis system for gastric cancer detection using deep learning

Integrating deep learning CT-scan model, biological and clinical variables to predict severity of COVID-19 patients

Experimental search for high-temperature ferroelectric perovskites guided by two-step machine learning

Learning few-shot imitation as cultural transmission

Machine Learning in Dermatology: Current Applications, Opportunities, and Limitations

Clustering earthquake signals and background noises in continuous seismic data with unsupervised deep learning

Accurate recognition of colorectal cancer with semi-supervised deep learning on pathological images

Combining machine learning and nanopore construction creates an artificial intelligence nanopore for coronavirus detection

Machine learning analysis of extreme events in optical fibre modulation instability

Clinical applications of artificial intelligence and machine learning in cancer diagnosis: looking into the future

Machine learning and structural analysis of Mycobacterium tuberculosis pan-genome identifies genetic signatures of antibiotic resistance

Deep Learning for Drug Design: an Artificial Intelligence Paradigm for Drug Discovery in the Big Data Era

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