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A PyTorch implementation of Neighbourhood Components Analysis.
Benchmark your model on out-of-distribution datasets with carefully collected human comparison data (NeurIPS 2021 Oral)
Data from BAG Tweets made useful.
A python package for simulating movement and spatial cell types (e.g. place cells, grid cells) in continuous environments.
From a body shape, infer the anatomic skeleton.
SDK for running DeepLabCut on a live video stream
Automated 3D cell detection in very large images
Relational data pipelines for the science lab
A very simple and barebones tensor decomposition library for CP decomposition a.k.a. PARAFAC a.k.a. TCA
A script that applies the AdaIN style transfer method to arbitrary datasets
The reference implementation of "Unsupervised Learning of Shape and Pose with Differentiable Point Clouds"
Robustness and adaptation of ImageNet scale models. Pre-Release, stay tuned for updates.
[ICCV 2023] Rethinking pose estimation in crowds: overcoming the detection information-bottleneck and ambiguity
The governance process and model for Project Jupyter
Code for the paper "Contrastive Learning Inverts the Data Generating Process".
Code release for "Adversarial Robustness vs Model Compression, or Both?"
The official implementation of the paper "Reinforcement Learning-Based Motion Imitation for Physiologically Plausible Musculoskeletal Motor Control"
[CVPR 2024] HOISDF: Constraining 3D Hand-Object Pose Estimation with Global Signed Distance Fields
OpenScope databook: a collaborative, versioned, data-centric collection of foundational analyses for reproducible systems neuroscience ππ§ π¬π₯οΈπ
NiceWebRL is a Python library for quickly making human subject experiments that leverage machine reinforcement learning environments.
a Python API to record video & system timestamps from Imaging Source USB cameras
Real-time analysis of intracranial neurophysiology recordings.
GUI to run DeepLabCut on live video feed
a napari plugin for labeling and refining keypoint data within DeepLabCut projects
Blind source separation based on the probabilistic tensor factorisation framework