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A code implementation of new papers in the time series forecasting field.
About Code release for "PatchMixer: A Patch-Mixing Architecture for Long-Term Time Series Forecasting"
Neural Time Series Analysis with Fourier Transform: A Survey
FITS: Frequency Interpolation Time Series Analysis Baseline
Official implementation of the paper "Frequency-domain MLPs are More Effective Learners in Time Series Forecasting"
An offical implementation of PatchTST: "A Time Series is Worth 64 Words: Long-term Forecasting with Transformers." (ICLR 2023) https://arxiv.org/abs/2211.14730
Revisiting Long-term Time Series Forecasting: An Investigation on Linear Mapping
MTS-Mixers: Multivariate Time Series Forecasting via Factorized Temporal and Channel Mixing
This repository contains a reading list of papers on Time Series Forecasting/Prediction (TSF) and Spatio-Temporal Forecasting/Prediction (STF). These papers are mainly categorized according to the …
Google Research
Deep Learning model(Image classfication, BeautyGAN) using Flask Swagger Based flask-restplus
This is a simple project to elaborate how to deploy a Machine Learning model using Flask API.
Parallel TTS web demo based on Flask + Vue (Vuetify). 基于 Flask + Vue 的语音合成单网页演示项目。
后端+前端+算法模型，机器学习项目 demo。Flask + vue + ML, full stack machine learning project construction.
"Covid-19 AI in Docker" demo deployment including Flask, FastAPI, Tensorflow Serving and HA Proxy etc etc
📈 Coronavirus (COVID-19) dashboard to show the dynamics of Сoronavirus distribution per country
🤖 Interactive Machine Learning experiments: 🏋️models training + 🎨models demo
A demo site to get in touch with ai and nerual networks
北京 青年大学习 使用Github Actions自动完成
Robust machine learning for responsible AI
Self-supervised contrastive learning for time series via time-frequency consistency
Multivariate Time Series Transformer, public version
Fast and memory-efficient exact attention