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Tsinghua University
- Beijing, China
- https://wenweithu.github.io/
Highlights
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Stars
About code release of "Interpretable Weather Forecasting for Worldwide Stations with a Unified Deep Model", Nature Machine Intelligence, 2023. https://www.nature.com/articles/s42256-023-00667-9
Vector (and Scalar) Quantization, in Pytorch
Official implementation for "UniST: A Prompt-Empowered Universal Model for Urban Spatio-Temporal Prediction" (KDD 2024)
Official code, datasets and checkpoints for "Timer: Generative Pre-trained Transformers Are Large Time Series Models" (ICML 2024)
See the official code and checkpoints for "Timer: Generative Pre-trained Transformers Are Large Time Series Models"
NuwaTS: a Foundation Model Mending Every Incomplete Time Series
FITS: Frequency Interpolation Time Series Analysis Baseline
The official GitHub page for the survey paper "A Survey of Large Language Models".
[ICLR 2024] Official implementation of "TimeMixer: Decomposable Multiscale Mixing for Time Series Forecasting"
Code release for "Non-stationary Transformers: Exploring the Stationarity in Time Series Forecasting" (NeurIPS 2022), https://arxiv.org/abs/2205.14415
Chronos: Pretrained (Language) Models for Probabilistic Time Series Forecasting
Official implementation for "AutoTimes: Autoregressive Time Series Forecasters via Large Language Models"
The TinyLlama project is an open endeavor to pretrain a 1.1B Llama model on 3 trillion tokens.
Lag-Llama: Towards Foundation Models for Probabilistic 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
Official code repository for the paper "Pushing the Limits of Pre-training for Time Series Forecasting in the CloudOps Domain"
Revisiting Long-term Time Series Forecasting: An Investigation on Linear Mapping
Code release for "Koopa: Learning Non-stationary Time Series Dynamics with Koopman Predictors" (NeurIPS 2023), https://arxiv.org/abs/2305.18803
Official implementation for "iTransformer: Inverted Transformers Are Effective for Time Series Forecasting" (ICLR 2024 Spotlight), https://openreview.net/forum?id=JePfAI8fah
Unofficial implementation of iTransformer - SOTA Time Series Forecasting using Attention networks, out of Tsinghua / Ant group
Code release for "Supported Policy Optimization for Offline Reinforcement Learning" (NeurIPS 2022), https://arxiv.org/abs/2202.06239
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 …
Repository of Transformer based PyTorch Time Series Models
Code release for "LogME: Practical Assessment of Pre-trained Models for Transfer Learning" (ICML 2021) and Ranking and Tuning Pre-trained Models: A New Paradigm for Exploiting Model Hubs (JMLR 2022)