Steffen Schneider's repositories
deeplabcut-docker
Inofficial docker images for DeepLabCut (experimental)
CaImAn
Computational toolbox for large scale Calcium Imaging Analysis, including movie handling, motion correction, source extraction, spike deconvolution and result visualization.
CCC
Code for Continuously Changing Corruptions (CCC) benchmark + evaluation
CEBRA-fork
Learnable latent embeddings for joint behavioral and neural analysis - Official implementation of CEBRA
CLIP
Contrastive Language-Image Pretraining
datajoint-python
Relational data pipelines for the science lab
DeepLabCut
Official implementation of DeepLabCut: Markerless pose estimation of user-defined features with deep learning for all animals
DeepLabCut-core
Headless DeepLabCut (no GUI support)
DeepLabCut-live
SDK for running DeepLabCut on a live video stream
DLC2Kinematics
a module for kinematic analysis of deeplabcut outputs
Efficient-PyTorch
My best practice of training large dataset using PyTorch.
ephysiopy
Analysis of electrophysiological data recorded using Axona and openephys using Python
gdown
Download a large file from Google Drive (curl/wget fails because of the security notice).
largescale_recordings
Urai AE, Doiron B, Leifer AM & Churchland AK (2022) Large-scale neural recordings call for new insights to link brain and behavior. Nature Neuroscience
nbsphinx
:ledger: Sphinx source parser for Jupyter notebooks
NX-414
Coding course materials for Brain-like computation and intelligence
oauth2-proxy
A reverse proxy that provides authentication with Google, Azure, OpenID Connect and many more identity providers.
oauthenticator
OAuth + JupyterHub Authenticator = OAuthenticator
pi-vae
Poisson Identifiable VAE (pi-VAE)
pytorch-image-models
The largest collection of PyTorch image encoders / backbones. Including train, eval, inference, export scripts, and pretrained weights -- ResNet, ResNeXT, EfficientNet, NFNet, Vision Transformer (ViT), MobileNetV4, MobileNet-V3 & V2, RegNet, DPN, CSPNet, Swin Transformer, MaxViT, CoAtNet, ConvNeXt, and more
tta-cvpr2024.github.io
site for the 1st Workshop on Test-Time Adaptation: Model, Adapt Thyself! (MAT)
uda_release
Unsupervised Domain Adaptation through Self-Supervision
webdataset
A high-performance Python-based I/O system for large (and small) deep learning problems, with strong support for PyTorch.