RobotPsychologist / bg_control
Improving short-term prandial blood glucose outcomes for people with type 1 diabetes, a complex disease that affects nearly 10 million people worldwide. We aim to leverage semi-supervised learning to identify unlabelled meals in time-series blood glucose data, develop meal-scoring functions, and explore causal machine-learning techniques.
☆18Updated this week
Related projects ⓘ
Alternatives and complementary repositories for bg_control
- A Python 3 package for learning Bayesian Networks (DAGs) from data. Official implementation of the paper "DAGMA: Learning DAGs via M-matr…☆103Updated 10 months ago
- ☆441Updated last month
- [Experimental] Global causal discovery algorithms☆89Updated this week
- Python package for causal discovery based on LiNGAM.☆380Updated 3 weeks ago
- Python package for Causal Discovery by learning the graphical structure of Bayesian networks. Structure Learning, Parameter Learning, Inf…☆480Updated 3 weeks ago
- A Type-1 Diabetes simulator implemented in Python for Reinforcement Learning purpose☆247Updated last week
- Comparative analysis of pairwise interactions in multivariate time series.☆207Updated 2 months ago
- Makes algorithms/code in Tetrad available in Python via JPype☆60Updated this week
- A Python package for modular causal inference analysis and model evaluations☆735Updated 3 months ago
- Quantile Regression Forests compatible with scikit-learn.☆210Updated this week
- Granger causality discovery for neural networks.☆197Updated 3 years ago
- Python implementation of the GES algorithm for causal discovery, from the 2002 paper "Optimal Structure Identification With Greedy Search…☆54Updated 9 months ago
- Causal discovery algorithms and tools for implementing new ones☆195Updated this week
- Patient-specific blood glucose prediction using deep learning, considering the challenges of "small dataset" and "data imbalance"☆41Updated 3 weeks ago
- 👖 Conformal Tights adds conformal prediction of coherent quantiles and intervals to any scikit-learn regressor or Darts forecaster☆86Updated last month
- A resource list for causality in statistics, data science and physics☆255Updated this week
- DoubleML - Double Machine Learning in Python☆499Updated this week
- Causal discovery for time series☆90Updated 2 years ago
- Scikit-learn compatible decision trees beyond those offered in scikit-learn☆67Updated this week
- A Python package for causal inference in quasi-experimental settings☆917Updated this week
- A package for statistically rigorous scientific discovery using machine learning. Implements prediction-powered inference.☆206Updated 2 weeks ago
- Fast and modular sklearn replacement for generalized linear models☆158Updated 2 weeks ago
- An experimental language for causal reasoning☆172Updated this week
- Causal Neural Nerwork☆82Updated 7 months ago
- Conformalized Quantile Regression☆251Updated 2 years ago
- Neural Causal Model (NCM) implementation by the authors of The Causal Neural Connection.☆22Updated last year
- Multi Comparison Matrix: A long term approach to benchmark evaluations☆20Updated 2 weeks ago
- Examples of PyMC models, including a library of Jupyter notebooks.☆291Updated last month
- DAGs with NO TEARS: Continuous Optimization for Structure Learning☆605Updated 6 months ago
- Official code for: Conformal prediction interval for dynamic time-series (conference, ICML 21 Long Presentation) AND Conformal prediction…☆98Updated 11 months ago