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Data-driven prediction of battery cycle life before capacity degradation

Nature energy, 2019-05, Vol.4 (5), p.383-391

2019

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Closed-loop optimization of fast-charging protocols for batteries with machine learning

Nature (London), 2020-02, Vol.578 (7795), p.397-402

2020

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Opportunities and challenges of real‐time release testing in biopharmaceutical manufacturing

Biotechnology and bioengineering, 2017-11, Vol.114 (11), p.2445-2456

2017

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Challenges and opportunities in biopharmaceutical manufacturing control

Computers & chemical engineering, 2018-02, Vol.110, p.106-114

2018

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DPVis: Visual Analytics With Hidden Markov Models for Disease Progression Pathways

IEEE transactions on visualization and computer graphics, 2021-09, Vol.27 (9), p.3685-3700

2021

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Discovery of Parkinson's disease states and disease progression modelling: a longitudinal data study using machine learning

The Lancet. Digital health, 2021-09, Vol.3 (9), p.e555-e564

2021

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A method for learning a sparse classifier in the presence of missing data for high-dimensional biological datasets

Bioinformatics (Oxford, England), 2017-09, Vol.33 (18), p.2897-2905

2017

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Principal Component Analysis of Process Datasets with Missing Values

Processes, 2017-09, Vol.5 (4), p.38

2017

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Vasopressin Administration Is Associated With Rising Serum Lactate Levels in Patients With Sepsis

Journal of intensive care medicine, 2020-09, Vol.35 (9), p.881-888

2020

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Perspectives on process monitoring of industrial systems

Annual reviews in control, 2016, Vol.42, p.190-200

2016

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Identifying unreliable predictions in clinical risk models

NPJ digital medicine, 2020-01, Vol.3 (1), p.8-8, Article 8

2020

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Statistical Learning for Accurate and Interpretable Battery Lifetime Prediction

Journal of the Electrochemical Society, 2021-09, Vol.168 (9), p.90547

2021

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BEEP: A Python library for Battery Evaluation and Early Prediction

SoftwareX, 2020-01, Vol.11, p.100506, Article 100506

2020

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Bayesian design of concrete with amortized Gaussian processes and multi-objective optimization

Cement and concrete research, 2024-03, Vol.177, p.107406, Article 107406

2024

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Generative Oversampling with a Contrastive Variational Autoencoder

2019 IEEE International Conference on Data Mining (ICDM), 2019, p.101-109

2019

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Improving Mitosis Detection on Histopathology Images Using Large Vision-Language Models

2024 IEEE International Symposium on Biomedical Imaging (ISBI), 2024, p.1-5

2024

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Optimal integration for biodiesel production using bioethanol

AIChE journal, 2013-03, Vol.59 (3), p.834-844

2013

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Elastic net with Monte Carlo sampling for data-based modeling in biopharmaceutical manufacturing facilities

Computers & chemical engineering, 2015-09, Vol.80, p.30-36

2015

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Identifying unreliable predictions in clinical risk models

NPJ digital medicine, 2020-01, Vol.3 (1), p.8

2020

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Machine Learning for Applications in Chemical and Biological Engineering

Severson, Kristen Ann

2018

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Unsupervised Learning with Contrastive Latent Variable Models

Proceedings of the ... AAAI Conference on Artificial Intelligence, 2019, Vol.33 (1), p.4862-4869

2019

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Perspectives on Process Monitoring of Industrial Systems ★ ★BP is acknowledged for funding

IFAC-PapersOnLine, 2015, Vol.48 (21), p.931-939

2015

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Emergency Department Physical Therapist Service: A Pilot Study Examining Physician Perceptions

The Internet journal of allied health sciences and practice, 2010

2010

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Closed-Loop Optimization of Battery Fast Charging Procedures

Meeting abstracts (Electrochemical Society), 2019-02, Vol.MA2019-03 (2), p.227-227

2019

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Data-driven prediction of battery cycle life before capacity degradation

Closed-loop optimization of fast-charging protocols for batteries with machine learning

Opportunities and challenges of real‐time release testing in biopharmaceutical manufacturing

Challenges and opportunities in biopharmaceutical manufacturing control

DPVis: Visual Analytics With Hidden Markov Models for Disease Progression Pathways

Discovery of Parkinson's disease states and disease progression modelling: a longitudinal data study using machine learning

A method for learning a sparse classifier in the presence of missing data for high-dimensional biological datasets

Principal Component Analysis of Process Datasets with Missing Values

Vasopressin Administration Is Associated With Rising Serum Lactate Levels in Patients With Sepsis

Perspectives on process monitoring of industrial systems

Identifying unreliable predictions in clinical risk models

Statistical Learning for Accurate and Interpretable Battery Lifetime Prediction

BEEP: A Python library for Battery Evaluation and Early Prediction

Bayesian design of concrete with amortized Gaussian processes and multi-objective optimization

Generative Oversampling with a Contrastive Variational Autoencoder

Improving Mitosis Detection on Histopathology Images Using Large Vision-Language Models

Optimal integration for biodiesel production using bioethanol

A foundation model for clinical-grade computational pathology and rare cancers detection

Elastic net with Monte Carlo sampling for data-based modeling in biopharmaceutical manufacturing facilities

Identifying unreliable predictions in clinical risk models

Machine Learning for Applications in Chemical and Biological Engineering

Unsupervised Learning with Contrastive Latent Variable Models

Perspectives on Process Monitoring of Industrial Systems ★ ★BP is acknowledged for funding

Emergency Department Physical Therapist Service: A Pilot Study Examining Physician Perceptions

Closed-Loop Optimization of Battery Fast Charging Procedures

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