mitmath / 18S096SciMLLinks
18.S096 - Applications of Scientific Machine Learning
☆312Updated 3 years ago
Alternatives and similar repositories for 18S096SciML
Users that are interested in 18S096SciML are comparing it to the libraries listed below
Sorting:
- 18.303 - Linear PDEs course☆147Updated 2 years ago
- Repository for the Universal Differential Equations for Scientific Machine Learning paper, describing a computational basis for high perf…☆235Updated 3 years ago
- 18.336 - Fast Methods for Partial Differential and Integral Equations☆187Updated last year
- 18.337 - Parallel Computing and Scientific Machine Learning☆246Updated 2 years ago
- 18.335 - Introduction to Numerical Methods course☆564Updated last week
- Surrogate modeling and optimization for scientific machine learning (SciML)☆361Updated 3 weeks ago
- Scientific machine learning (SciML) benchmarks, AI for science, and (differential) equation solvers. Covers Julia, Python (PyTorch, Jax),…☆335Updated 3 weeks ago
- Data driven modeling and automated discovery of dynamical systems for the SciML Scientific Machine Learning organization☆420Updated last week
- ☆105Updated last week
- Tutorials for doing scientific machine learning (SciML) and high-performance differential equation solving with open source software.☆738Updated 3 weeks ago
- Julia code for the book Numerical Linear Algebra☆126Updated 2 years ago
- Pre-built implicit layer architectures with O(1) backprop, GPUs, and stiff+non-stiff DE solvers, demonstrating scientific machine learnin…☆906Updated last week
- Probabilistic Numerical Differential Equation solvers via Bayesian filtering and smoothing☆130Updated last week
- Nonlinear Dynamics: A concise introduction interlaced with code☆254Updated 5 months ago
- GPU Programming with Julia - course at the Swiss National Supercomputing Centre (CSCS), ETH Zurich☆259Updated 3 years ago
- Solvers for stochastic differential equations which connect with the scientific machine learning (SciML) ecosystem☆305Updated this week
- Documentation for the DiffEq differential equations and scientific machine learning (SciML) ecosystem☆318Updated last week
- Reservoir computing utilities for scientific machine learning (SciML)☆221Updated this week
- Extra materials for *Fundamentals of Numerical Computation* by Driscoll and Braun.☆172Updated 4 months ago
- Linear operators for discretizations of differential equations and scientific machine learning (SciML)☆284Updated 2 years ago
- A Julia package for Gaussian Processes☆316Updated last month
- Julia Jupyter/Colab Notebooks☆165Updated 2 months ago
- A component of the DiffEq ecosystem for enabling sensitivity analysis for scientific machine learning (SciML). Optimize-then-discretize, …☆372Updated last week
- A short course on Julia and open-source software development☆322Updated 2 years ago
- Solving differential equations in Python using DifferentialEquations.jl and the SciML Scientific Machine Learning organization☆586Updated 2 months ago
- Tutorials and information on the Julia language for MIT numerical-computation courses.☆796Updated 10 months ago
- Tools for building fast, hackable, pseudospectral partial differential equation solvers on periodic domains☆212Updated 2 months ago
- 18.S096 three-week course at MIT☆267Updated 2 years ago
- ☆67Updated 6 years ago
- Probabilistic Programming with Gaussian processes in Julia☆346Updated 8 months ago