awesome-repositories.com
Blog
MCP
awesome-repositories.com

Discover the best open-source repositories with AI-powered search.

ExploreCurated searchesOpen-source alternativesSelf-hosted softwareBlogSitemap
ProjectMCP serverAboutHow we rankPress
LegalPrivacyTerms
© 2026 Bringes Technology SRL·VAT RO45896025·hello@awesome-repositories.com
A

adityalab/camul

0
View on GitHub↗
0 stars·0 forks·12 views

Camul

We require you to have anaconda or miniconda installed. Run the script ./scripts/setup.sh to setup the virtual environment with all the required packages.

Features

  • Forecasting Models - Calibrated multi-view forecasting for time series data.

Star history

Star history chart for adityalab/camulStar history chart for adityalab/camul

How this analysis was created: This summary and feature list are AI-generated from collected project material and can contain mistakes. Stars, license and language are imported from GitHub. Inclusion does not mean that we have tested or audited this project. Check the source documentation for any feature you depend on. Learn more on our About page.

AI search

Explore more awesome repositories

Describe what you need in plain English — the AI ranks thousands of curated open-source projects by relevance.

Start searching with AI

Projects sharing features with Camul

These projects share indexed features with Camul. Shared tags can include platform or build tooling; verify the primary use case before treating a result as a replacement.
  • lyhue1991/eat_tensorflow2_in_30_dayslyhue1991 avatar

    lyhue1991/eat_tensorflow2_in_30_days

    9,933View on GitHub↗

    This project is a structured learning curriculum and technical reference for mastering deep learning with TensorFlow. It provides a comprehensive guide for building, training, and deploying neural networks, combining theoretical fundamentals with practical implementation examples. The repository distinguishes itself by covering the end-to-end machine learning workflow, from low-level tensor mathematics and linear algebra to the creation of complex model architectures. It includes specific guidance on developing data pipelines for diverse data types, such as images, text, and time-series seque

    Pythontensorflowtensorflow-examplestensorflow-tutorial
    View on GitHub↗9,933
  • adityalab/epifnpA

    AdityaLab/EpiFNP

    0View on GitHub↗

    Paper Link: https://arxiv.org/abs/2106.03904

    View on GitHub↗0
  • adityalab/foilAdityaLab avatar

    AdityaLab/FOIL

    46View on GitHub↗

    Dependencies can be installed using the following file: newtimelibenvironment.yml You can obtain the well pre-processed datasets from [Google Drive](https://drive.google.com/drive/folders/13Cg1KYOlzM5C7K8gK8NfC-F3EYxkM3D2?usp=sharing) or [[Baidu…

    Python
    View on GitHub↗46
  • adityalab/back2futureAdityaLab avatar

    AdityaLab/Back2Future

    7View on GitHub↗

    Link to paper: https://arxiv.org/abs/2106.04420

    Python
    View on GitHub↗7
Compare all 30 related projects→

Frequently asked questions

What does adityalab/camul do?

We require you to have anaconda or miniconda installed. Run the script ./scripts/setup.sh to setup the virtual environment with all the required packages.

What are the main features of adityalab/camul?

The main features of adityalab/camul are: Forecasting Models.

Which projects share features with adityalab/camul?

Projects with overlapping indexed features include: lyhue1991/eat_tensorflow2_in_30_days — This project is a structured learning curriculum and technical reference for mastering deep learning with TensorFlow.… adityalab/epifnp — Paper Link: https://arxiv.org/abs/2106.03904. adityalab/foil — Dependencies can be installed using the following file: newtimelibenvironment.yml You can obtain the well… adityalab/lstprompt — Implementation of the paper "LSTPrompt: Large Language Models as Zero-Shot Time Series Forecasters by Long-Short-Term… adityalab/pets — Implementation of the paper "Performative Time-Series Forecasting.". adityalab/back2future — Link to paper: https://arxiv.org/abs/2106.04420.