# amazon-science/unconditional-time-series-diffusion

<https://repo.masters-masters.com/en/repos/amazon-science/unconditional-time-series-diffusion>

[Home](https://repo.masters-masters.com/en) › [amazon-science](https://repo.masters-masters.com/en/owners/amazon-science) › [unconditional-time-series-diffusion](https://repo.masters-masters.com/en/repos/amazon-science/unconditional-time-series-diffusion)

amazon-science/unconditional-time-series-diffusion has 261 stars on GitHub. Its RepoMasters card: Alpha tier. Official PyTorch implementation of TSDiff models…

| Field | Value |
| --- | --- |
| Owner | [amazon-science](https://repo.masters-masters.com/en/owners/amazon-science) |
| Stars | 261 |
| Forks | 40 |
| Language | [Python](https://repo.masters-masters.com/en/languages/python) |
| License | Apache-2.0 |
| Created | 2023 |
| Topics | diffusion-models, neurips, neurips-2023, pytorch, time-series, time-series-forecasting |
| Tier | [Alpha (250 to 699 ★)](https://repo.masters-masters.com/en/ranks/b_movie) |
| View on GitHub | [amazon-science/unconditional-time-series-diffusion](https://github.com/amazon-science/unconditional-time-series-diffusion) |

## Repository

Official PyTorch implementation of TSDiff models presented in the NeurIPS 2023 paper "Predict, Refine, Synthesize: Self-Guiding Diffusion Models for Probabilistic Time Series Forecasting"

The tier for repos with 250 to 699 ★. Published odds per card pulled: 20%. Rarity: Uncommon.

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Data: GitHub · Illustration drawn by RepoMasters from the repo’s ID and its language color.