Stars
A coding-free framework built on PyTorch for reproducible deep learning studies. 🏆25 knowledge distillation methods presented at CVPR, ICLR, ECCV, NeurIPS, ICCV, etc are implemented so far. 🎁 Train…
[IJCAI 2022] FQ-ViT: Post-Training Quantization for Fully Quantized Vision Transformer
a program to do dimensional deduction using Singular-Value Decomposition (SVD) with best rank k with minimum Frobenius norm.
Compressing Large Language Models using Low Precision and Low Rank Decomposition
Yet another PCA package. This one focuses on rank selection.
Bayesian Optimization-Based Global Optimal Rank Selection for Compression of Convolutional Neural Networks, IEEE Access
Code for the paper "Tensor Regression Networks with various Low-Rank Tensor Approximations"
this code library is mainly about applying graph neural networks to intelligent diagnostic and prognostic.
A light-weight transformer model for Kaggle House Prices Regression Competition
Caffe for Sparse and Low-rank Deep Neural Networks
🍀 Pytorch implementation of various Attention Mechanisms, MLP, Re-parameter, Convolution, which is helpful to further understand papers.⭐⭐⭐
《代码随想录》LeetCode 刷题攻略：200道经典题目刷题顺序，共60w字的详细图解，视频难点剖析，50余张思维导图，支持C++，Java，Python，Go，JavaScript等多语言版本，从此算法学习不再迷茫！🔥🔥 来看看，你会发现相见恨晚！🚀
Multivariate time series (MTS) analysis project: selection and prediction. Study of variable selection and prediction algorithms, and their impact on performance. Exploration of relationships betwe…
Model compression by constrained optimization, using the Learning-Compression (LC) algorithm
The machine learning toolkit for time series analysis in Python
This toolbox offers 13 wrapper feature selection methods (PSO, GA, GWO, HHO, BA, WOA, and etc.) with examples. It is simple and easy to implement.
Group Sparsity: The Hinge Between Filter Pruning and Decomposition for Network Compression. CVPR2020.
Approximately optimal core shapes for tensor decompositions (ICML 2023)
Repository for the feature selection with tabular models
Research on Tabular Deep Learning: Papers & Packages
PyImpetus is a Markov Blanket based feature subset selection algorithm that considers features both separately and together as a group in order to provide not just the best set of features but also…
[TMLR] Supervised Feature Selection with Neuron Evolution in Sparse Neural Networks
A python-based framework for multi-target prediction
A curated list of neural network pruning resources.