yixuan/temperflow
Efficient Multimodal Sampling via Tempered Distribution Flow
This project offers an implementation of the TemperFlow algorithm, designed to enhance multimodal sampling for research purposes. It takes pre-trained model files and computational resources (GPU, Python, R) as input, generating model data, image files, and statistical tables/plots as output. It is primarily for researchers and computational statisticians evaluating or applying advanced sampling techniques.
No commits in the last 6 months.
Use this if you are a researcher or computational statistician working with complex probability distributions and need to efficiently generate samples from multimodal target distributions.
Not ideal if you are looking for an out-of-the-box solution for general data analysis or a simple statistical package, as it requires a specific computational environment and expertise in advanced statistical methods.
Stars
11
Forks
2
Language
Python
License
—
Category
Last pushed
Apr 11, 2023
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/yixuan/temperflow"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
lucidrains/rectified-flow-pytorch
Implementation of rectified flow and some of its followup research / improvements in Pytorch
probabilists/zuko
Normalizing flows in PyTorch
davidnabergoj/torchflows
Modern normalizing flows in Python. Simple to use and easily extensible.
keishihara/flow-matching
Flow Matching implemented in PyTorch
LukasRinder/normalizing-flows
Implementation of normalizing flows in TensorFlow 2 including a small tutorial.