chenchau

pillow-simd

The friendly PIL fork

probabilistic_unet

A U-Net combined with a variational auto-encoder that is able to learn conditional distributions over semantic segmentations.

Probabilistic_Contrastive_Learning

This repository contains the code for our paper "Probabilistic Contrastive Learning Recovers the Correct Aleatoric Uncertainty of Ambiguous Inputs".

awesome-human-label-variation

A curated list of awesome datasets with human label variation (un-aggregated labels) in Natural Language Processing and Computer Vision, accompanying The 'Problem' of Human Label Variation: On Ground Truth in Data, Modeling and Evaluation (EMNLP 2022)

DUE

Code for "On Feature Collapse and Deep Kernel Learning for Single Forward Pass Uncertainty".

expert_traj

ICCV2021 Expert-Goal Trajectory Prediction

Research_Papers

All papers in this repository are interesting papers regardless of the field. Everything from analytical essays of cultural events to machine learning manuscripts are all valid in this repository. I just want to document and explore all the beautiful thoughts and ideas in the world.

awesome-ml-internships

List of companies offering Machine learning and Data Science internships

UCNet

UC-Net: Uncertainty Inspired RGB-D Saliency Detectionvia Conditional Variational Autoencoders, CVPR2020

CurriculumNet

CurriculumNet: Weakly Supervised Learning from Large-Scale Web Images

VaDE

Python code for paper - Variational Deep Embedding : A Generative Approach to Clustering

GMVAE

Implementation of Gaussian Mixture Variational Autoencoder (GMVAE) for Unsupervised Clustering

Image-Quality-Assessment-Benchmark

A collection of state-of-the-art image quality assessment algorithms

No-Reference-Image-Quality-Assessment-using-BRISQUE-Model

Implementation of the paper "No Reference Image Quality Assessment in the Spatial Domain" by A Mittal et al. in OpenCV (using both C++ and Python)

Autoencoder-Clustering

Replication of "Auto-encoder Based Data Clustering" Song et al

HOC

papers

I categorize, annotate and write comments for all research papers I read (410+ papers since 2018).

softmax_variants

PyTorch code for softmax variants: center loss, cosface loss, large-margin gaussian mixture, COCOLoss, ring loss

align_uniform

Open source code for paper "Understanding Contrastive Representation Learning through Alignment and Uniformity on the Hypersphere" ICML 2020

HeteroscedasticDropoutUncertainty

Demos demonstrating the difference between homoscedastic and heteroscedastic regression with dropout uncertainty.

DropoutUncertaintyCaffeModels

Dropout As A Bayesian Approximation: Code

PyTorch-BayesianCNN

Bayesian Convolutional Neural Network with Variational Inference based on Bayes by Backprop in PyTorch.

Bayesian-Neural-Networks

Pytorch implementations of Bayes By Backprop, MC Dropout, SGLD, the Local Reparametrization Trick, KF-Laplace, SG-HMC and more

cifar-10h

Original dataset release for CIFAR-10H

HowToLiveLonger

程序员延寿指南 | A programmer's guide to live longer

cifar-10-100n

Human annotated noisy labels for CIFAR-10 and CIFAR-100. The website of CIFAR-N is available at http://www.noisylabels.com/.

Awesome-Learning-with-Label-Noise

A curated list of resources for Learning with Noisy Labels

deterministic-uncertainty-quantification

Code for "Uncertainty Estimation Using a Single Deep Deterministic Neural Network"

uncertainty-baselines

High-quality implementations of standard and SOTA methods on a variety of tasks.

deep-learning-uncertainty

Literature survey, paper reviews, experimental setups and a collection of implementations for baselines methods for predictive uncertainty estimation in deep learning models.