score_sde
SDE
Our great sponsors
score_sde | SDE | |
---|---|---|
6 | 1 | |
1,242 | 153 | |
- | 0.0% | |
0.0 | 0.0 | |
over 1 year ago | over 2 years ago | |
Jupyter Notebook | MATLAB | |
Apache License 2.0 | MIT License |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
score_sde
- Ask HN: How to get back into AI?
-
[D] Why is the diffution model so powerful? but the math behind it is so simple.
Turns out that diffusion models also define a certain differential equation, making it a neural ODE. Then you can just integrate the ODE in the other direction to get the exact inverse for the DDPM (it's not entirely exact b/c of numerical error in the solver, but close enough)
-
Diffusion Models Beat GANs on Image Synthesis
This new approach to generative modelling looks very intriguing.
In a similar ilk, there's this ICLR paper from this year using stochastic differential equations for generative modelling: https://arxiv.org/abs/2011.13456
SDE
We haven't tracked posts mentioning SDE yet.
Tracking mentions began in Dec 2020.
What are some alternatives?
guided-diffusion
pytorch-generative - Easy generative modeling in PyTorch.
Financial-Models-Numerical-Methods - Collection of notebooks about quantitative finance, with interactive python code.
score_sde_pytorch - PyTorch implementation for Score-Based Generative Modeling through Stochastic Differential Equations (ICLR 2021, Oral)
best-of-ml-python - 🏆 A ranked list of awesome machine learning Python libraries. Updated weekly.
Compositional-Visual-Generation-with-Composable-Diffusion-Models-PyTorch - [ECCV 2022] Compositional Generation using Diffusion Models
DifferentialEquations.jl - 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.
pyprobml - Python code for "Probabilistic Machine learning" book by Kevin Murphy
gramm - Gramm is a complete data visualization toolbox for Matlab. It provides an easy to use and high-level interface to produce publication-quality plots of complex data with varied statistical visualizations. Gramm is inspired by R's ggplot2 library.
course-content - NMA Computational Neuroscience course
NNfSiX - Neural Networks from Scratch in various programming languages