swansealeo Goto Github PK
Type: User
Type: User
Active Learning on Image Data using Bayesian ConvNets
Adjust Decision Boundary for Class Imbalanced Learning
Adversarial Active Learning for Deep Networks
A wizard's guide to Adversarial Autoencoders
Agency Theme for Jekyll
Accompanying repository for Let's make a DQN / A3C series.
Adversarially Learned One-Class Classifier for Novelty Detection (ALOCC)
Keras implementation of Adversarially Learned One-Class Classifier or ALOCC for short.
Tensorflow implementation of OCGAN: One-class Novelty Detection Using GANs with Constrained Latent Representations
An alternative library for the Arduboy miniature game system
AugMix: A Simple Data Processing Method to Improve Robustness and Uncertainty
accessible AutoML for deep learning.
A curated list of awesome imbalanced learning papers, codes, frameworks and libraries. | 类别不平衡学习:论文/代码/框架/库
PyTorch implementation of "Weight Uncertainty in Neural Networks"
Bayesian Methods for Machine Learning
Bayes by Backprop implemented in a CNN in PyTorch
Bayesian Convolutional Neural Networks with Bernoulli Approximate Variational Inference
a repo sharing Bayesian Neural Network recent papers
pytorch implementation of ICML 17 paper "Dropout inference in Bayesian neural networks with alpha-divergences"
Automatically exported from code.google.com/p/beliefbox
A book to introduce blockchain related techniques.
Implementation of SegNet: A Deep Convolutional Encoder-Decoder Architecture for Semantic Pixel-Wise Labelling
Class-Balanced Loss Based on Effective Number of Samples. CVPR 2019
Pytorch implementation of the paper "Class-Balanced Loss Based on Effective Number of Samples"
Classification models trained on ImageNet. Keras.
This repository contains code for the paper "Decoupling Representation and Classifier for Long-Tailed Recognition", published at ICLR 2020
Finding label errors in datasets and learning with noisy labels.
An adversarial example library for constructing attacks, building defenses, and benchmarking both
NeurIPS'18: Co-teaching: Robust Training of Deep Neural Networks with Extremely Noisy Labels
Official data release to reproduce Confident Learning paper results
A declarative, efficient, and flexible JavaScript library for building user interfaces.
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
An Open Source Machine Learning Framework for Everyone
The Web framework for perfectionists with deadlines.
A PHP framework for web artisans
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
Some thing interesting about web. New door for the world.
A server is a program made to process requests and deliver data to clients.
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
Some thing interesting about visualization, use data art
Some thing interesting about game, make everyone happy.
We are working to build community through open source technology. NB: members must have two-factor auth.
Open source projects and samples from Microsoft.
Google ❤️ Open Source for everyone.
Alibaba Open Source for everyone
Data-Driven Documents codes.
China tencent open source team.