Shun-Ryu

htmz

html with targeted manipulation zones

Vebview.JS

Move Beyond the Web Border

V-Hello

Minimal V project using VS Code, mingw gcc and gdb

Meta-Weight-Net_Code-Optimization

A new code framework that uses pytorch to implement meta-learning, and takes Meta-Weight-Net as an example.

awesome-long-tail-learning

tsai

Time series Timeseries Deep Learning Machine Learning Python Pytorch fastai | State-of-the-art Deep Learning library for Time Series and Sequences in Pytorch / fastai

FT_TransFormer

DeepLearning for Tabular Data with FT_Transformer & ResNet

FT_TransFormer

DeepLearning for Tabular Data with FT_Transformer & ResNet

TabTransformerTF

TensorFlow implementation of TabTransformer

tab-transformer-pytorch

Implementation of TabTransformer, attention network for tabular data, in Pytorch

pytorch_tabular

A standard framework for modelling Deep Learning Models for tabular data

pytorch-widedeep

A flexible package for multimodal-deep-learning to combine tabular data with text and images using Wide and Deep models in Pytorch

rtdl-revisiting-models

(NeurIPS 2021) Revisiting Deep Learning Models for Tabular Data

obsidian-annotator

A plugin for reading and annotating PDFs and EPUBs in obsidian.

obsidian-annotator

A plugin for reading and annotating PDFs and EPUBs in obsidian.

google-research

Google Research

Awesome-Long-Tailed

Papers about long-tailed tasks

PRML-Labs

labs for PRML

ImbalancedLittleData

Trying to solve a imbalanced little data in text sentiment analysis

imbalanced-learning

This workshop is part of the "Machine Learning in R" graduate course held at University of Münster, School of Business and Economics (winter term 2020/21). :mortar_board:

imbalanced-learning

Comparison of different imbalanced classification methods with application to credit card fraud

A-Weakly-Supervised-Learning-based-Oversampling-Framework-for-Imbalanced-Classification

This is a program of a new weakly supervised learning based oversampling framework to solve the imbalanced classification proposed by Min Qian and Yanfu Li.

imbalanced-data

Examples of algorithms dealing with imbalanced data.

ImbalancedLearning

[NeurIPS 2022] The official code for our NeurIPS 2022 paper "Inducing Neural Collapse in Imbalanced Learning: Do We Really Need a Learnable Classifier at the End of Deep Neural Network?".

IRon

R Package for Imbalanced Regression

Tricks-for-Handling-Imbalanced-Dataset-Image-Classification

Some trick for handling imbalanced dataset

geometric-smote

Implementation of the Geometric SMOTE over-sampling algorithm.

well-classified-examples-are-underestimated

Code for the AAAI 2022 publication "Well-classified Examples are Underestimated in Classification with Deep Neural Networks"

Awesome-Long-Tailed

Papers about long-tailed tasks

vibration_gan

Implement GANs to generate time-series signals for imbalanced learning problem. The experiments are conducted using CWRU bearing data.