Collection of notebooks about quantitative finance, with interactive python code.
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Updated
Oct 22, 2024 - Jupyter Notebook
Collection of notebooks about quantitative finance, with interactive python code.
Multi-language suite for high-performance solvers of differential equations and scientific machine learning (SciML) components. Ordinary differential equations (ODEs), stochastic differential equations (SDEs), delay differential equations (DDEs), differential-algebraic equations (DAEs), and more in Julia.
PyTorch implementation for Score-Based Generative Modeling through Stochastic Differential Equations (ICLR 2021, Oral)
Differentiable SDE solvers with GPU support and efficient sensitivity analysis.
Official code for Score-Based Generative Modeling through Stochastic Differential Equations (ICLR 2021, Oral)
An acausal modeling framework for automatically parallelized scientific machine learning (SciML) in Julia. A computer algebra system for integrated symbolics for physics-informed machine learning and automated transformations of differential equations
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
Tutorials for doing scientific machine learning (SciML) and high-performance differential equation solving with open source software.
Image Restoration with Mean-Reverting Stochastic Differential Equations, ICML 2023. Winning solution of the NTIRE 2023 Image Shadow Removal Challenge.
Solving differential equations in Python using DifferentialEquations.jl and the SciML Scientific Machine Learning organization
Generate realizations of stochastic processes in python.
The lightweight Base library for shared types and functionality for defining differential equation and scientific machine learning (SciML) problems
Rectified Flow Inversion (RF-Inversion)
Linear operators for discretizations of differential equations and scientific machine learning (SciML)
Solvers for stochastic differential equations which connect with the scientific machine learning (SciML) ecosystem
Example codes for the book Applied Stochastic Differential Equations
Code for "Infinitely Deep Bayesian Neural Networks with Stochastic Differential Equations"
📦 Python library for Stochastic Processes Simulation and Visualisation
Official Code Repository for the paper "Score-based Generative Modeling of Graphs via the System of Stochastic Differential Equations" (ICML 2022)
Solving differential equations in R using DifferentialEquations.jl and the SciML Scientific Machine Learning ecosystem
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