About Code release for "Autoformer: Decomposition Transformers with Auto-Correlation for Long-Term Series Forecasting" (NeurIPS 2021), https://arxiv.org/abs/2106.13008

🐟 Code and models for the NeurIPS 2023 paper "Generating Images with Multimodal Language Models".

Google Research

Official implementation for "iTransformer: Inverted Transformers Are Effective for Time Series Forecasting" (ICLR 2024 Spotlight), https://openreview.net/forum?id=JePfAI8fah

Code release for "Koopa: Learning Non-stationary Time Series Dynamics with Koopman Predictors" (NeurIPS 2023), https://arxiv.org/abs/2305.18803

[CVPR2024] ModaVerse: Efficiently Transforming Modalities with LLMs

Code and models for NExT-GPT: Any-to-Any Multimodal Large Language Model

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

Time-MoE: Billion-Scale Time Series Foundation Models with Mixture of Experts

A Library for Advanced Deep Time Series Models.