yulewang97/ERDiff
[NeurIPS 2023 Spotlight] Official Repo for "Extraction and Recovery of Dpatio-temporal Structure in Latent Dynamics Alignment with Diffusion Models"
Uses diffusion models as a generative prior to align neural latent dynamics across sessions while preserving spatio-temporal structure. The approach combines diffusion-guided maximum likelihood alignment with linear probing layers initialized for stability, enabling recovery of consistent neural representations without requiring explicit correspondence. Targets neuroscience applications analyzing neural recordings across multiple recording sessions or experimental conditions.
Stars
51
Forks
6
Language
Python
License
MIT
Category
Last pushed
Feb 23, 2026
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/diffusion/yulewang97/ERDiff"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
xie-lab-ml/Golden-Noise-for-Diffusion-Models
[ICCV2025] The code of our work "Golden Noise for Diffusion Models: A Learning Framework".
UNIC-Lab/RadioDiff
This is the code for the paper "RadioDiff: An Effective Generative Diffusion Model for...
pantheon5100/pid_diffusion
This repository is the official implementation of the paper: Physics Informed Distillation for...
zju-pi/diff-sampler
An open-source toolbox for fast sampling of diffusion models. Official implementations of our...
dome272/Paella
Official Implementation of Paella https://arxiv.org/abs/2211.07292v2