mlaprise

"""
draws many samples from a diffusion model by slerp'ing around
the noise space, and dumps frames to a directory. You can then
stitch up the frames with e.g.:

$ ffmpeg -r 10 -f image2 -s 512x512 -i out/frame%04d.jpg -vcodec libx264 -crf 10 -pix_fmt yuv420p test.mp4

THIS FILE IS HACKY AND NOT CONFIGURABLE READ THE CODE, MAKE EDITS TO PATHS AND SETTINGS YOU LIKE
THIS FILE IS HACKY AND NOT CONFIGURABLE READ THE CODE, MAKE EDITS TO PATHS AND SETTINGS YOU LIKE
THIS FILE IS HACKY AND NOT CONFIGURABLE READ THE CODE, MAKE EDITS TO PATHS AND SETTINGS YOU LIKE

mlaprise

Quick List of Resources for Topological Data Analysis with Emphasis on Machine Learning

This is just a quick list of resourses on TDA that I put together for @rickasaurus after he was asking for links to papers, books, etc on Twitter and is by no means an exhaustive list.

Survey Papers

Both Carlsson's and Ghrist's survey papers offer a very good introduction to the subject

• Topology and Data by Gunnar Carlsson
• Barcodes: The Persistent Topology of Data by Robert Ghrist

Other Papers and Web Resources

• Extracting insights from the shape of complex data using topology A good introductory paper in Nature on the Mapper algorithm.