vboussange / jaxscapeLinks
A minimal JAX library for connectivity analysis at scales
☆10Updated 4 months ago
Alternatives and similar repositories for jaxscape
Users that are interested in jaxscape are comparing it to the libraries listed below
Sorting:
- A Review of Sensitivity Methods for Differential Equations☆31Updated 9 months ago
- Physics-Enhanced Regression for Initial Value Problems☆20Updated last year
- Efficient, Accurate, and Streamlined Training of Physics-Informed Neural Networks☆58Updated 5 months ago
- Probabilistic ODE solvers are fun, but are they fast? See also: https://github.com/pnkraemer/probdiffeq for JAX code or https://github.c…☆21Updated last year
- Taylor-mode automatic differentiation for higher-order derivatives☆80Updated 3 weeks ago
- Probabilistic Numerical Differential Equation solvers via Bayesian filtering and smoothing☆129Updated 3 weeks ago
- DeepONets, (Fourier) Neural Operators, Physics-Informed Neural Operators, and more in Julia☆25Updated last week
- Inverse modelling framework for dynamical systems characterised by complex dynamics.☆13Updated 2 months ago
- Lectures, code and material for the Modelling and Machine Learning of Dynamical Systems in Julia lecture at Technical University Munich☆12Updated last month
- No need to train, he's a smooth operator☆45Updated 3 weeks ago
- A Julia package to construct orthogonal polynomials, their quadrature rules, and use it with polynomial chaos expansions.☆123Updated 3 weeks ago
- Structure Preserving Machine Learning Models in Julia☆50Updated 3 weeks ago
- Implicit Layer Machine Learning via Deep Equilibrium Networks, O(1) backpropagation with accelerated convergence.☆57Updated last month
- Automates steady and unsteady adjoints (general solvers and ODEs respectively). Forward and reverse mode algorithmic differentiation arou…☆29Updated last month
- Implements Optimization and approximate uncertainty quantification algorithms, Ensemble Kalman Inversion, and Ensemble Kalman Processes.☆106Updated this week
- Fast uncertainty quantification for scientific machine learning (SciML) and differential equations☆69Updated last week
- Stochastic Optimization, Learning, Uncertainty and Sampling☆88Updated 3 weeks ago
- A Julia package for Deep Backwards Stochastic Differential Equation (Deep BSDE) and Feynman-Kac methods to solve high-dimensional PDEs wi…☆81Updated 3 weeks ago
- Training materials for ModelingToolkit and JuliaSim☆38Updated 2 years ago
- StateSpaceLearning.jl is a Julia package for time-series analysis using state space learning framework.☆20Updated 3 weeks ago
- Coloring algorithms for sparse Jacobian and Hessian matrices☆28Updated this week
- Comparsion of Julia's GPU Kernel based ODE solvers with other open-source GPU ODE solvers☆27Updated last year
- ☆20Updated 2 years ago
- Checkpointing for Automatic Differentiation☆56Updated last week
- A tutorial on how to work around ‘Mutating arrays is not supported’ error while performing automatic differentiation (AD) using the Julia…☆30Updated 4 years ago
- Symbolic-Numeric Neural DAEs and Universal Differential Equations for Automating Scientific Machine Learning (SciML)☆34Updated this week
- Learning to optimize (L2O) package that provides basic functionalities to help fit proxy models for optimization.☆15Updated 5 months ago
- Optimization framework for nonlinear, gradient-based constrained, sparse optimization problems.☆30Updated 3 weeks ago
- Website for the book "The Elements of Differentiable Programming".☆14Updated 2 months ago
- Implementations of Infinitesimal Continuous Normalizing Flows Algorithms in Julia☆27Updated this week