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The repo is the official implementation for the paper: iTransformer: Inverted Transformers Are Effective for Time Series Forecasting. [Slides](https://cloud.tsinghua.edu.cn/f/175ff98f7e2d44fbbe8e/), [Poster](https://cloud.tsinghua.edu.cn/f/36a2ae6c132d44c0bd8c/), [[Intro…
TimesFM is a time series foundation model designed to generalize across diverse temporal datasets for forecasting and anomaly detection. It functions as a pretrained model for predicting future values in univariate time series data, eliminating the need for manual training from scratch. The project includes a framework for adapting pretrained weights to specific datasets using low-rank adaptation to improve accuracy. It also provides specialized capabilities for integrating time-series predictions as tools within autonomous AI agent architectures and automated workflows. The system supports
This repository is a collection of practical deep learning implementations and examples built using the TensorFlow framework. It provides a variety of neural network architectures focusing on natural language processing, recommendation systems, reinforcement learning, and time series prediction. The project features a range of specialized models, including sequence-to-sequence and transformer architectures for text processing, and factorization machines for personalized ranking and retrieval. It also includes implementations of reinforcement learning agents using actor-critic and policy gradi
This code is a PyTorch implementation of our ICLR'24 paper "Pathformer: Multi-scale Transformers with Adaptive Pathways for Time Series Forecasting". [[arXiv]](https://arxiv.org/abs/2402.05956)
The main features of decisionintelligence/pathformer are: Forecasting Models, Time Series Forecasting Models.
Projects with overlapping indexed features include: thuml/itransformer — The repo is the official implementation for the paper: iTransformer: Inverted Transformers Are Effective for Time… wxie9/card. google-research/timesfm — TimesFM is a time series foundation model designed to generalize across diverse temporal datasets for forecasting and… lyhue1991/eat_tensorflow2_in_30_days — This project is a structured learning curriculum and technical reference for mastering deep learning with TensorFlow.… princewen/tensorflow_practice — This repository is a collection of practical deep learning implementations and examples built using the TensorFlow… adityalab/lstprompt — Implementation of the paper "LSTPrompt: Large Language Models as Zero-Shot Time Series Forecasters by Long-Short-Term…
