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<!DOCTYPE html>
<html lang="en">
<head>
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<title>Timer: Large Time Series Foundation Model</title>
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<li class="menu-active"><a href="#body">Home</a></li>
<li><a href="#about">About Us</a></li>
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<!-- ======= hero Section ======= -->
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<h2>Analyse <span>Universal</span> Time Series <br> Through <span>Large Model</span></h2>
<div>
<a href="#about" class="btn-get-started scrollto">Get Started</a>
<a href="https://arxiv.org/abs/2402.02368" class="btn-projects scrollto">Our Paper</a>
</div>
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<!-- ======= About Section ======= -->
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<img src="assets/img/about-img-arch.png" alt="">
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<div class="col-lg-6 content">
<h2>Welcome to Timer - Universal Time Series Analysis</h2>
<h3>Timer is the brainchild of a dedicated team of researchers and developers from the <span>School of Software, at Tsinghua University.</span> Our work is inspired by the transformative impact of large language models on natural language processing. We've taken the same approach to time series data, creating a model <span>pre-trained on massive datasets and fine-tuning for specific tasks</span> with remarkable few-shot ability.</h3>
<ul>
<li><i class="bi bi-check-circle"></i> Luxuriant knowledge base based on large-scale pre-training.</li>
<li><i class="bi bi-check-circle"></i> Diverse downstream tasks to adapt to complex industrial scenarios.</li>
<li><i class="bi bi-check-circle"></i> Mighty analytical ability and generalization ability for real-world data.</li>
</ul>
</div>
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<img src="assets/img/about-abilities.png" alt="">
</div>
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<div class="col-lg-6 content">
<h2>Massive High-quality Dataset</h2>
<h3>In pursuit of preeminent analytical prowess within the industry, we have meticulously constructed a vast dataset that harmoniously integrates <span>extensive scale, superior quality, and multifaceted domains.</span> This endeavor has endowed Timer with an expansive repository of high-caliber data, thereby conferring upon it an impressively robust generalization capability across a multitude of tasks.</h3>
</div>
<div class="col-lg-6 about-img">
<img src="assets/img/about-img-data.png" alt="">
</div>
</div>
<div class="row about-img-row">
<div class="about-img">
<h2>Model Scalability</h2>
<img src="assets/img/about-scaling.png" alt="">
</div>
</div>
<div class="row" id="about-demo">
<div class="col-lg-6 about-img">
<video controls autoplay loop>
<source src="assets/img/demo.mp4">
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</video>
</div>
<div class="col-lg-6 content">
<h2>One-Stop Analysis Scheme</h2>
<h3>In alignment with the formidable capabilities of our model, we have engineered a complementary suite of solutions. These solutions enable you to access the advanced analytical services of our large-scale model through a variety of methods, including online API access, platform-based deployment, and even bespoke private deployment options.
<br><span>The front-end API, which is designed for online invocation, is on the cusp of being launched!</span></h3>
</div>
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</section><!-- End About Section -->
<!-- ======= Services Section ======= -->
<section id="services">
<div class="container" data-aos="fade-up">
<div class="section-header">
<h2>scenarios</h2>
<p>
Timer offers a suite of services designed to help businesses and researchers unlock the full potential of their time series data. Our Timer model is pre-trained on vast datasets and fine-tuned for specific tasks, providing a powerful tool for a range of applications.
</p>
</div>
<div class="row gy-4">
<div class="col-lg-6" data-aos="fade-up" data-aos-delay="100">
<div class="box">
<div class="icon"><i class="bi bi-graph-up"></i></div>
<h4 class="title"><a href="">Forecasting</a></h4>
<p class="description">Eliminate the headaches of missing data. Timer fills in the gaps, ensuring continuity and integrity in your time series datasets.</p>
</div>
</div>
<div class="col-lg-6" data-aos="fade-up" data-aos-delay="200">
<div class="box">
<div class="icon"><i class="bi bi-bar-chart"></i></div>
<h4 class="title"><a href="">Data Imputation</a></h4>
<p class="description">Eliminate the headaches of missing data. Timer fills in the gaps, ensuring continuity and integrity in your time series datasets.</p>
</div>
</div>
<div class="col-lg-6" data-aos="fade-up" data-aos-delay="300">
<div class="box">
<div class="icon"><i class="bi bi-lightning"></i></div>
<h4 class="title"><a href="">Anomaly Detection</a></h4>
<p class="description">We provide anomaly detection capabilities based on autoregressive analysis, and Timer will provide real-time alerts for possible abnormal data.</p>
</div>
</div>
<div class="col-lg-6" data-aos="fade-up" data-aos-delay="400">
<div class="box">
<div class="icon"><i class="bi bi-upload"></i></div>
<h4 class="title"><a href="">Unified Generative Framework</a></h4>
<p class="description">Our services operate under a unified generative approach, streamlining complex tasks for diverse applications and domains.</p>
</div>
</div>
</div>
</div>
</section><!-- End Services Section -->
<!-- ======= Clients Section ======= -->
<!-- <section id="clients">
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<div class="section-header">
<h2>Clients</h2>
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<div class="clients-slider swiper" data-aos="fade-up" data-aos-delay="100">
<div class="swiper-wrapper align-items-center">
<div class="swiper-slide"><img src="assets/img/clients/client-1.png" class="img-fluid" alt=""></div>
<div class="swiper-slide"><img src="assets/img/clients/client-2.png" class="img-fluid" alt=""></div>
<div class="swiper-slide"><img src="assets/img/clients/client-3.png" class="img-fluid" alt=""></div>
<div class="swiper-slide"><img src="assets/img/clients/client-4.png" class="img-fluid" alt=""></div>
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</div>
<div class="swiper-pagination"></div>
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</div>
</section> -->
<!-- ======= Portfolio Section ======= -->
<section id="portfolio" class="portfolio">
<div class="container" data-aos="fade-up">
<div class="section-header">
<h2>Showcases</h2>
<!-- Timer拥有较强的泛化性，能够适应多种不同领域和场景的真实时序数据，在各种任务上拥有优异的处理效果，这里展现了Timer在不同数据上的真实表现 -->
<p>
Timer boasts an exceptional generalization capacity, adeptly accommodating a myriad of authentic time series datasets from diverse sectors and scenarios. It consistently delivers superior performance across a spectrum of tasks, showcasing its robust adaptability and efficacy. The following demonstration illustrates the tangible prowess of Timer when applied to a variety of data sets.
<br>The following visualization results are all from fine-tuning results under extremely low sample usage rates.
</p>
</div>
<div class="row" data-aos="fade-up" data-aos-delay="100">
<div class="col-lg-12 d-flex justify-content-center">
<ul id="portfolio-flters">
<li data-filter="*" class="filter-active">All</li>
<li data-filter=".filter-forecast">Forecast</li>
<li data-filter=".filter-imputation">Imputation</li>
<li data-filter=".filter-detection">Detection</li>
</ul>
</div>
</div>
<div class="row portfolio-container" data-aos="fade-up" data-aos-delay="200">
<div class="col-lg-4 col-md-6 portfolio-item filter-forecast">
<img src="assets/img/portfolio/forecast_ECL_0.2_0.pdf.png" class="img-fluid" alt="">
<div class="portfolio-info">
<h4>Forecast on ECL Dataset</h4>
<p>20% Samples Fine-tuned</p>
<a href="assets/img/portfolio/forecast_ECL_0.2_0.pdf.png" data-gallery="portfolioGallery" class="portfolio-lightbox preview-link"><i class="bx bx-plus"></i></a>
</div>
</div>
<div class="col-lg-4 col-md-6 portfolio-item filter-forecast">
<img src="assets/img/portfolio/forecast_Traffic_0.2_10_0.pdf.png" class="img-fluid" alt="">
<div class="portfolio-info">
<h4>Forecast on Traffic Dataset</h4>
<p>20% Samples Fine-tuned</p>
<a href="assets/img/portfolio/forecast_Traffic_0.2_10_0.pdf.png" data-gallery="portfolioGallery" class="portfolio-lightbox preview-link"><i class="bx bx-plus"></i></a>
</div>
</div>
<div class="col-lg-4 col-md-6 portfolio-item filter-forecast">
<img src="assets/img/portfolio/forecast_PEMS03_0.2_30_0.pdf.png" class="img-fluid" alt="">
<div class="portfolio-info">
<h4>Forecast on PEMS03 Dataset</h4>
<p>20% Samples Fine-tuned</p>
<a href="assets/img/portfolio/forecast_PEMS03_0.2_30_0.pdf.png" data-gallery="portfolioGallery" class="portfolio-lightbox preview-link"><i class="bx bx-plus"></i></a>
</div>
</div>
<div class="col-lg-4 col-md-6 portfolio-item filter-forecast">
<img src="assets/img/portfolio/forecast_ECL_0.05_10_0.pdf.png" class="img-fluid" alt="">
<div class="portfolio-info">
<h4>Forecast on ECL Dataset</h4>
<p>5% Samples Fine-tuned</p>
<a href="assets/img/portfolio/forecast_ECL_0.05_10_0.pdf.png" data-gallery="portfolioGallery" class="portfolio-lightbox preview-link"><i class="bx bx-plus"></i></a>
</div>
</div>
<div class="col-lg-4 col-md-6 portfolio-item filter-forecast">
<img src="assets/img/portfolio/forecast_Traffic_0.05_10_0.pdf.png" class="img-fluid" alt="">
<div class="portfolio-info">
<h4>Forecast on Traffic Dataset</h4>
<p>5% Samples Fine-tuned</p>
<a href="assets/img/portfolio/forecast_Traffic_0.05_10_0.pdf.png" data-gallery="portfolioGallery" class="portfolio-lightbox preview-link"><i class="bx bx-plus"></i></a>
</div>
</div>
<div class="col-lg-4 col-md-6 portfolio-item filter-forecast">
<img src="assets/img/portfolio/forecast_PEMS03_0.05_30_0.pdf.png" class="img-fluid" alt="">
<div class="portfolio-info">
<h4>Forecast on PEMS03 Dataset</h4>
<p>5% Samples Fine-tuned</p>
<a href="assets/img/portfolio/forecast_PEMS03_0.05_30_0.pdf.png" data-gallery="portfolioGallery" class="portfolio-lightbox preview-link"><i class="bx bx-plus"></i></a>
</div>
</div>
<div class="col-lg-4 col-md-6 portfolio-item filter-imputation">
<img src="assets/img/portfolio/imputation_ETTh2_0.2_400.pdf.png" class="img-fluid" alt="">
<div class="portfolio-info">
<h4>Imputation on ETTh2 Dataset</h4>
<p>20% Samples Fine-tuned</p>
<a href="assets/img/portfolio/imputation_ETTh2_0.2_400.pdf.png" data-gallery="portfolioGallery" class="portfolio-lightbox preview-link"><i class="bx bx-plus"></i></a>
</div>
</div>
<div class="col-lg-4 col-md-6 portfolio-item filter-imputation">
<img src="assets/img/portfolio/imputation_ECL_0.2_140.pdf.png" class="img-fluid" alt="">
<div class="portfolio-info">
<h4>Imputation on ECL Dataset</h4>
<p>20% Samples Fine-tuned</p>
<a href="assets/img/portfolio/imputation_ECL_0.2_140.pdf.png" data-gallery="portfolioGallery" class="portfolio-lightbox preview-link"><i class="bx bx-plus"></i></a>
</div>
</div>
<div class="col-lg-4 col-md-6 portfolio-item filter-imputation">
<img src="assets/img/portfolio/imputation_Traffic_0.2_180.pdf.png" class="img-fluid" alt="">
<div class="portfolio-info">
<h4>Imputation on Traffic Dataset</h4>
<p>20% Samples Fine-tuned</p>
<a href="assets/img/portfolio/imputation_Traffic_0.2_180.pdf.png" data-gallery="portfolioGallery" class="portfolio-lightbox preview-link"><i class="bx bx-plus"></i></a>
</div>
</div>
<div class="col-lg-4 col-md-6 portfolio-item filter-imputation">
<img src="assets/img/portfolio/imputation_ETTh2_0.05_400.pdf.png" class="img-fluid" alt="">
<div class="portfolio-info">
<h4>Imputation on ETTh2 Dataset</h4>
<p>5% Samples Fine-tuned</p>
<a href="assets/img/portfolio/imputation_ETTh2_0.05_400.pdf.png" data-gallery="portfolioGallery" class="portfolio-lightbox preview-link"><i class="bx bx-plus"></i></a>
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<h4>Imputation on ECL Dataset</h4>
<p>5% Samples Fine-tuned</p>
<a href="assets/img/portfolio/imputation_ECL_0.05_140.pdf.png" data-gallery="portfolioGallery" class="portfolio-lightbox preview-link"><i class="bx bx-plus"></i></a>
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<img src="assets/img/portfolio/imputation_Traffic_0.05_180.pdf.png" class="img-fluid" alt="">
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<h4>Imputation on Traffic Dataset</h4>
<p>5% Samples Fine-tuned</p>
<a href="assets/img/portfolio/imputation_Traffic_0.05_180.pdf.png" data-gallery="portfolioGallery" class="portfolio-lightbox preview-link"><i class="bx bx-plus"></i></a>
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<h4>Detection on ECG4 Dataset</h4>
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<h4>Detection on insectEPG5 Dataset</h4>
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<h4>Detection on CHARISten Dataset</h4>
<a href="assets/img/portfolio/detection_206_UCR_Anomaly_CHARISten_25130_29080_29140.pdf.png" data-gallery="portfolioGallery" class="portfolio-lightbox preview-link"><i class="bx bx-plus"></i></a>
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