Kristen A. Severson

Publication Activity (10 Years)

Years Active: 2015-2023
Publications (10 Years): 15

Top Topics

Hidden Markov Models

Unsupervised Learning

Visual Analytics

Top Venues

Comput. Chem. Eng.

Annu. Rev. Control.

Publications

Zongliang Ji, Philip Rosenfield, Christina Eng, Sarah Bettigole, Danielle C. Gibson, Hamid Masoudi, Matthew Hanna, Nicolò Fusi, Kristen A. Severson
Considerations for data acquisition and modeling strategies: Mitosis detection in computational pathology. MIDL (2023)
Uri Kartoun, Paul Myers, Kristen A. Severson, Wangzhi Dai, Kenney Ng, Collin M. Stultz
Feature Selection Based on Subpopulations and Propensity Score Matching: A Coronary Artery Disease Use Case using the UK Biobank. AMIA (2022)
Peter M. Attia, Kristen A. Severson, Jeremy D. Witmer
Statistical learning for accurate and interpretable battery lifetime prediction. CoRR (2021)
Bum Chul Kwon, Vibha Anand, Kristen A. Severson, Soumya Ghosh, Zhaonan Sun, Brigitte I. Frohnert, Markus Lundgren, Kenney Ng
DPVis: Visual Analytics With Hidden Markov Models for Disease Progression Pathways. IEEE Trans. Vis. Comput. Graph. 27 (9) (2021)
Peter M. Attia, Aditya Grover, Norman Jin, Kristen A. Severson, Todor M. Markov, Yang-Hung Liao, Michael H. Chen, Bryan Cheong, Nicholas Perkins, Zi Yang, Patrick K. Herring, Muratahan Aykol, Stephen J. Harris, Richard D. Braatz, Stefano Ermon, William C. Chueh
Closed-loop optimization of fast-charging protocols for batteries with machine learning. Nat. 578 (7795) (2020)
Kristen A. Severson, Lana M. Chahine, Luba Smolensky, Kenney Ng, Jianying Hu, Soumya Ghosh
Personalized Input-Output Hidden Markov Models for Disease Progression Modeling. MLHC (2020)
Paul Myers, Kenney Ng, Kristen A. Severson, Uri Kartoun, Wangzhi Dai, Wei Huang, Fred Anderson, Collin M. Stultz
Identifying unreliable predictions in clinical risk models. npj Digit. Medicine 3 (2020)
Patrick K. Herring, Chirranjeevi Balaji Gopal, Muratahan Aykol, Joseph Montoya, Abraham Anapolsky, Peter M. Attia, William Gent, Jens S. Hummelshøj, Linda Hung, Ha-Kyung Kwon, Patrick Moore, Daniel Schweigert, Kristen A. Severson, Santosh Suram, Zi Yang, Richard D. Braatz, Brian D. Storey
BEEP: A Python library for Battery Evaluation and Early Prediction. SoftwareX 11 (2020)
Wangzhi Dai, Kenney Ng, Kristen A. Severson, Wei Huang, Fred Anderson, Collin Stultz
Generative Oversampling with a Contrastive Variational Autoencoder. ICDM (2019)
Kristen A. Severson, Soumya Ghosh, Kenney Ng
Unsupervised Learning with Contrastive Latent Variable Models. AAAI (2019)
Bum Chul Kwon, Vibha Anand, Kristen A. Severson, Soumya Ghosh, Zhaonan Sun, Brigitte I. Frohnert, Markus Lundgren, Kenney Ng
DPVis: Visual Exploration of Disease Progression Pathways. CoRR (2019)
Moo Sun Hong, Kristen A. Severson, Mo Jiang, Amos E. Lu, J. Christopher Love, Richard D. Braatz
Challenges and opportunities in biopharmaceutical manufacturing control. Comput. Chem. Eng. 110 (2018)
Kristen A. Severson, Soumya Ghosh, Kenney Ng
Unsupervised learning with contrastive latent variable models. CoRR (2018)
Kristen A. Severson, Brinda Monian, J. Christopher Love, Richard D. Braatz
A method for learning a sparse classifier in the presence of missing data for high-dimensional biological datasets. Bioinform. 33 (18) (2017)
Kristen A. Severson, Paphonwit Chaiwatanodom, Richard D. Braatz
Perspectives on process monitoring of industrial systems. Annu. Rev. Control. 42 (2016)
Kristen A. Severson, Jeremy G. VanAntwerp, Venkatesh Natarajan, Chris Antoniou, Jörg Thömmes, Richard D. Braatz
Elastic net with Monte Carlo sampling for data-based modeling in biopharmaceutical manufacturing facilities. Comput. Chem. Eng. 80 (2015)