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Gradient-Based Attribution Methods

Explainable AI: Interpreting, Explaining and Visualizing Deep Learning, p.169-191

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"Hello AI": Uncovering the Onboarding Needs of Medical Practitioners for Human-AI Collaborative Decision-Making

Proceedings of the ACM on human-computer interaction, 2019-11, Vol.3 (CSCW), p.1-24

2019

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A survey on Deep Learning based bearing fault diagnosis

Neurocomputing (Amsterdam), 2019-03, Vol.335, p.327-335

2019

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Grundprinzipien der künstlichen Intelligenz in der Dermatologie erklärt am Beispiel des Melanoms

Journal der Deutschen Dermatologischen Gesellschaft, 2024-03, Vol.22 (3), p.339-349

2024

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Crystal Structure Prediction via Deep Learning

Journal of the American Chemical Society, 2018-08, Vol.140 (32), p.10158-10168

2018

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Making the Case for Safety of Machine Learning in Highly Automated Driving

Computer Safety, Reliability, and Security, p.5-16

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The promise of artificial intelligence in chemical engineering: Is it here, finally?

AIChE journal, 2019-02, Vol.65 (2), p.466-478

Venkatasubramanian, Venkat

2019

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A survey on semi-supervised learning

Machine learning, 2020-02, Vol.109 (2), p.373-440

2020

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A hybrid deep learning based traffic flow prediction method and its understanding

Transportation research. Part C, Emerging technologies, 2018-05, Vol.90, p.166-180

2018

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Continual lifelong learning with neural networks: A review

Neural networks, 2019-05, Vol.113, p.54-71

2019

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Remaining useful life estimation of engineered systems using vanilla LSTM neural networks

Neurocomputing (Amsterdam), 2018-01, Vol.275, p.167-179

2018

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Neural‐Symbolic Machine Learning for Retrosynthesis and Reaction Prediction

Chemistry : a European journal, 2017-05, Vol.23 (25), p.5966-5971

2017

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Deep learning in spiking neural networks

Neural networks, 2019-03, Vol.111, p.47-63

2019

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A review of deep learning for renewable energy forecasting

Energy conversion and management, 2019-10, Vol.198, p.111799, Article 111799

2019

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Aleatoric and epistemic uncertainty in machine learning: an introduction to concepts and methods

Machine learning, 2021-03, Vol.110 (3), p.457-506

2021

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Machine learning: Overview of the recent progresses and implications for the process systems engineering field

Computers & chemical engineering, 2018-06, Vol.114, p.111-121

2018

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Deep neural networks, gradient-boosted trees, random forests: Statistical arbitrage on the S&P 500

European journal of operational research, 2017-06, Vol.259 (2), p.689-702

2017

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A Survey on Distributed Machine Learning

ACM computing surveys, 2020-06, Vol.53 (2), p.1-33, Article 30

2020

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Machine learning methods for wind turbine condition monitoring: A review

Renewable energy, 2019-04, Vol.133, p.620-635

2019

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Machine learning methods for solar radiation forecasting: A review

Renewable energy, 2017-05, Vol.105, p.569-582

2017

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An intelligent diagnosis scheme based on generative adversarial learning deep neural networks and its application to planetary gearbox fault pattern recognition

Neurocomputing (Amsterdam), 2018-10, Vol.310, p.213-222

2018

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A review on the long short-term memory model

The Artificial intelligence review, 2020-12, Vol.53 (8), p.5929-5955

2020

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A non-volatile organic electrochemical device as a low-voltage artificial synapse for neuromorphic computing

Nature materials, 2017-04, Vol.16 (4), p.414-418

2017

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Convolutional Neural Network Based Fault Detection for Rotating Machinery

Journal of sound and vibration, 2016-09, Vol.377, p.331-345

2016

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Real-Time Adaptive Machine-Learning-Based Predictive Control of Nonlinear Processes

Industrial & engineering chemistry research, 2020-02, Vol.59 (6), p.2275-2290

2020

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Gradient-Based Attribution Methods

"Hello AI": Uncovering the Onboarding Needs of Medical Practitioners for Human-AI Collaborative Decision-Making

A survey on Deep Learning based bearing fault diagnosis

Grundprinzipien der künstlichen Intelligenz in der Dermatologie erklärt am Beispiel des Melanoms

Crystal Structure Prediction via Deep Learning

Making the Case for Safety of Machine Learning in Highly Automated Driving

The promise of artificial intelligence in chemical engineering: Is it here, finally?

A survey on semi-supervised learning

A hybrid deep learning based traffic flow prediction method and its understanding

Continual lifelong learning with neural networks: A review

Remaining useful life estimation of engineered systems using vanilla LSTM neural networks

Neural‐Symbolic Machine Learning for Retrosynthesis and Reaction Prediction

Deep learning in spiking neural networks

A review of deep learning for renewable energy forecasting

Aleatoric and epistemic uncertainty in machine learning: an introduction to concepts and methods

Machine learning: Overview of the recent progresses and implications for the process systems engineering field

Deep neural networks, gradient-boosted trees, random forests: Statistical arbitrage on the S&P 500

A Survey on Distributed Machine Learning

Machine learning methods for wind turbine condition monitoring: A review

Machine learning methods for solar radiation forecasting: A review

An intelligent diagnosis scheme based on generative adversarial learning deep neural networks and its application to planetary gearbox fault pattern recognition

A review on the long short-term memory model

A non-volatile organic electrochemical device as a low-voltage artificial synapse for neuromorphic computing

Convolutional Neural Network Based Fault Detection for Rotating Machinery

Real-Time Adaptive Machine-Learning-Based Predictive Control of Nonlinear Processes

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