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

Julia implementation of Byte Pair Encoding for NLP

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

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

Deep-learning sliding window attention with circular boundary conditions. No tokenization, no patchify-ing.

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

Clima's Land Model

Climate Machine: an Earth System Model that automatically learns from data

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 package for the development and implementation of continuous-time policy gradient (CTPG) methods.

A package for Counterfactual Explanations and Algorithmic Recourse in Julia.

Lazy, structured, and efficient operations with kernel matrices.

A plugin to Dagger with various fancy or experimental features.

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Julia library for deep reinforcement learning

Direct transcription of an optimal control problem and resolution

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A Curious Cumulation of CUDA Cuisine

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Julia code of CycleGAN based on pytorch implementation

A framework for out-of-core and parallel execution

GPU integrations for Dagger.jl

Data driven acoustic propagation models

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

Package for fitting models according to the deep compartment modeling framework for pharmacometric applications.

Implicit Layer Machine Learning via Deep Equilibrium Networks, O(1) backpropagation with accelerated convergence.

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

Pre-built implicit layer architectures with O(1) backprop, GPUs, and stiff+non-stiff DE solvers, demonstrating scientific machine learning (SciML) and physics-informed machine learning methods

Linear operators for discretizations of differential equations and scientific machine learning (SciML)

A component of the DiffEq ecosystem for enabling sensitivity analysis for scientific machine learning (SciML). Optimize-then-discretize, discretize-then-optimize, adjoint methods, and more for ODEs, SDEs, DDEs, DAEs, etc.