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Title: GitHub - AdaptInfer/Contextualized: An SKLearn-style toolbox for estimating and analyzing models, distributions, and functions with context-specific parameters.

Open Graph Title: GitHub - AdaptInfer/Contextualized: An SKLearn-style toolbox for estimating and analyzing models, distributions, and functions with context-specific parameters.

X Title: GitHub - AdaptInfer/Contextualized: An SKLearn-style toolbox for estimating and analyzing models, distributions, and functions with context-specific parameters.

Description: An SKLearn-style toolbox for estimating and analyzing models, distributions, and functions with context-specific parameters. - AdaptInfer/Contextualized

Open Graph Description: An SKLearn-style toolbox for estimating and analyzing models, distributions, and functions with context-specific parameters. - AdaptInfer/Contextualized

X Description: An SKLearn-style toolbox for estimating and analyzing models, distributions, and functions with context-specific parameters. - AdaptInfer/Contextualized

Opengraph URL: https://github.com/AdaptInfer/Contextualized

X: @github

direct link

Domain: patch-diff.githubusercontent.com

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https://patch-diff.githubusercontent.com/AdaptInfer/Contextualized#related-publications-and-pre-prints
Contextualized Machine Learning (ArXiv '23)https://arxiv.org/abs/2310.11340
Contextualized: Heterogeneous Modeling Toolbox (JOSS '24)https://doi.org/10.21105/joss.06469
Patient-Specific Models of Treatment Effects Explain Heterogeneity in Tuberculosis (ML4H '24)https://arxiv.org/abs/2411.10645
Automated Interpretable Discovery of Heterogeneous Treatment Effectiveness: A COVID-19 Case Study (JBI '22)https://www.sciencedirect.com/science/article/pii/S1532046422001022
Discriminative Subtyping of Lung Cancers from Histopathology Images via Contextual Deep Learning (MedRxiv '22)https://www.medrxiv.org/content/10.1101/2020.06.25.20140053v2
Personalized Survival Prediction with Contextual Explanation Networks (ML4H '17)http://arxiv.org/abs/1801.09810
Contextual Explanation Networks (JMLR '20)https://jmlr.org/papers/v21/18-856.html
Learning to estimate sample-specific transcriptional networks for 7,000 tumors (PNAS '25)https://www.pnas.org/doi/10.1073/pnas.2411930122
NOTMAD: Estimating Bayesian Networks with Sample-Specific Structures and Parameters (ArXiv '23)http://arxiv.org/abs/2111.01104
Contextualized Policy Recovery: Modeling and Interpreting Medical Decisions with Adaptive Imitation Learning (ICML '24)https://arxiv.org/abs/2310.07918
Varying-Coefficient Models (JRStatSoc)https://academic.oup.com/jrsssb/article-abstract/55/4/757/7028270
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Cold Spring Harbor Laboratory: Contextualized Graphical Models Reveal Sample-Specific Transcriptional Networks for 7000 Tumorshttps://www.youtube.com/watch?v=MTcjFK-YwCw
Sample-Specific Models for Interpretable Analysis with Applications to Disease Subtypinghttp://www.birs.ca/events/2022/5-day-workshops/22w5055/videos/watch/202205051559-Lengerich.html
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