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Is there anything we can't make Bayesian?

Bayesian quantile regression in Julia

Transliterate Beta Code Greek to Unicode Greek

Learning state-space targets in dynamical systems

A prototype of a reactive Webapp for bitemporal data management of insurance contracts.

BOSS (Bayesian Optimization with Semiparametric Surrogate)

A Julia package for building, and running Biochemical Systems Theory (BST) models

A package for working with BioVisionHierarchy files (motion capture data)

A package to calibrate atmospheric turbulence and convection parameterizations using gradient-free ensemble Kalman methods

Stochastic Optimization, Learning, Uncertainty and Sampling

Causal inference, graphical models and structure learning in Julia

A decision-making framework for the cost-efficient design of experiments, balancing the value of acquired experimental evidence and incurred costs.

Visualization for Flux.Chain neural networks

Interface package for featurizing atomic structures

Quantitative analysis of chemicals

Repository that containts climate relevant ML datasets from the Climate Modeling Alliance.

Clima's Land Model

Pure Julia implementation of tools used in Coding Theory

Compressed belief-state MDPs in Julia compatible with POMDPs.jl

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Predictive Uncertainty Quantification through Conformal Prediction for Machine Learning models trained in MLJ.

A Julia package for people that love to learn new things about constraints

Implementations of Infinitesimal Continuous Normalizing Flows Algorithms in Julia

A Julia package supplying abstractions and operations for efficiently working with parcels, or regions of interest, on a CorticalSurface

A package for Counterfactual Explanations and Algorithmic Recourse in Julia.

Lazy, structured, and efficient operations with kernel matrices.

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Julia library for deep reinforcement learning

Julia code of CycleGAN based on pytorch implementation

Data driven acoustic propagation models

Data driven modeling and automated discovery of dynamical systems for the SciML Scientific Machine Learning organization

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DeepForest Impletmentation in Julia

Implementation of the Deep Q-learning algorithm to solve MDPs

Unfolded convolutional learning for motif discovery

Julia package for "Degrees of Freedom: Search Cost and Self-consistency"

Extension functionality which uses Stan.jl, DynamicHMC.jl, and Turing.jl to estimate the parameters to differential equations and perform Bayesian probabilistic scientific machine learning

Stan only version of DiffEqBayes.jl

Tutorials for doing scientific machine learning (SciML) and high-performance differential equation solving with open source software.