CassieMai's repositories
Brancher
A python library for stochastic variational inference and differentiable probabilistic programming
CAGrad
Official PyTorch Implementation for Conflict-Averse Gradient Descent (CAGrad)
cassiemai-blog.github.io
My new blog
cassiemai.github.io
Use this template if you need a quick developer / data science portfolio! Based on a Minimal Jekyll theme for GitHub Pages.
cassiemai2.github.io
:triangular_ruler: Jekyll theme for building a personal site, blog, project documentation, or portfolio.
CoMatch
Code for CoMatch: Semi-supervised Learning with Contrastive Graph Regularization
ContrastiveSeg
ICCV2021 (Oral) - Exploring Cross-Image Pixel Contrast for Semantic Segmentation
CVPR2022-Papers-with-Code
CVPR 2022 论文和开源项目合集
denoising-diffusion-pytorch
Implementation of Denoising Diffusion Probabilistic Model in Pytorch
EPOSearch
Exact Pareto Optimal solutions for preference based Multi-Objective Optimization
git-tips
:trollface:Git的奇技淫巧
google-research
Google Research
Gpuspline
Software library for the calculation of multidimensional cubic splines
grad-cam-pytorch
PyTorch implementation of Grad-CAM, vanilla/guided backpropagation, deconvnet, and occlusion sensitivity maps
Kalman-and-Bayesian-Filters-in-Python
Kalman Filter book using Jupyter Notebook. Focuses on building intuition and experience, not formal proofs. Includes Kalman filters,extended Kalman filters, unscented Kalman filters, particle filters, and more. All exercises include solutions.
Lion-vs-Adam
Lion and Adam optimization comparison
mean-teacher
A state-of-the-art semi-supervised method for image recognition
Non-Local-NN-Pytorch
PyTorch implementation of Non-Local Neural Networks (https://arxiv.org/pdf/1711.07971.pdf)
Object-Detection-Train-Test-Split
When you have image data and corresponding xml files, this script will help in splitting the data in two folders - train and test -
sr-gan
Semi-supervised Regression GAN
SUA_crowd_counting
ICCV2021: Code for 'Spatial Uncertainty-Aware Semi-Supervised Crowd Counting'
transformers
🤗 Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.
UA-MT
code for MICCAI 2019 paper 'Uncertainty-aware Self-ensembling Model for Semi-supervised 3D Left Atrium Segmentation'.
Unsupervised-Classification
SCAN: Learning to Classify Images without Labels, incl. SimCLR. [ECCV 2020]
Visualizer
assistant tools for attention visualization in deep learning