Ray is a unified framework for scaling AI and Python applications. Ray consists of a core distributed runtime and a set of AI Libraries for accelerating ML workloads.
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Updated
May 10, 2024 - Python
Ray is a unified framework for scaling AI and Python applications. Ray consists of a core distributed runtime and a set of AI Libraries for accelerating ML workloads.
ML hyperparameters tuning and features selection, using evolutionary algorithms.
A machine learning method to determine the age of abalone from physical measurements of size and weight
EvalML is an AutoML library written in python.
[ICDE 2024] a Web-app for Evaluation of Model selection for Anomaly Detection in Time Series
Uncertainty-penalized Bayesian information criterion (UBIC) for PDE Discovery
Regression model building and forecasting in R
Bayesian X-ray analysis (nested sampling for Xspec and Sherpa)
💪 🤔 Modern Super Learning with Machine Learning Pipelines
A Python Automated Machine Learning tool that optimizes machine learning pipelines using genetic programming.
Variable Selection with Knockoffs
A Python Automated Machine Learning tool that optimizes machine learning pipelines using genetic programming.
Fit and compare complex models reliably and rapidly. Advanced nested sampling.
Probabilistic programming framework that facilitates objective model selection for time-varying parameter models.
BAS R package https://merliseclyde.github.io/BAS/
Model selection by leveraging relative stability constraints derived from the developmental landscape of cell types
Kullback-Leibler projections for Bayesian model selection in Python
The code repository for "Model Spider: Learning to Rank Pre-Trained Models Efficiently"
[ICLR 2023, ICLR DG oral] PAIR, the optimizer and model selection criteria for OOD Generalization
Proximal Nested Sampling for high-dimensional Bayesian model selection
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