Trending repositories for topic forecasting

Platform for building AI that can learn and answer questions over federated data.

State-of-the-Art Deep Learning scripts organized by models - easy to train and deploy with reproducible accuracy and performance on enterprise-grade infrastructure.

Tool for producing high quality forecasts for time series data that has multiple seasonality with linear or non-linear growth.

Statsmodels: statistical modeling and econometrics in Python

Fast and Accurate ML in 3 Lines of Code

Scalable and user friendly neural :brain: forecasting algorithms.

The GitHub repository for the paper "Informer" accepted by AAAI 2021.

TimeGPT-1: production ready pre-trained Time Series Foundation Model for forecasting and anomaly detection. Generative pretrained transformer for time series trained on over 100B data points. It's ca...

Time series Timeseries Deep Learning Machine Learning Python Pytorch fastai | State-of-the-art Deep Learning library for Time Series and Sequences in Pytorch / fastai

Chronos: Pretrained Models for Probabilistic Time Series Forecasting

A professionally curated list of awesome resources (paper, code, data, etc.) on transformers in time series.

Probabilistic time series modeling in Python

Unified Training of Universal Time Series Forecasting Transformers

Resources about time series forecasting and deep learning.

A Python toolkit/library for reality-centric machine/deep learning and data mining on partially-observed time series, including SOTA neural network models for scientific analysis tasks of imputation/c...

Postgres with GPUs for ML/AI apps.

A professional list on Large (Language) Models and Foundation Models (LLM, LM, FM) for Time Series, Spatiotemporal, and Event Data.

[AAAI-23 Oral] Official implementation of the paper "Are Transformers Effective for Time Series Forecasting?"

Time series forecasting with PyTorch

Curated list of Machine Learning, NLP, Vision, Recommender Systems Project Ideas

Access to Sulie foundation models for time-series forecasting 📈

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

Resources about time series forecasting and deep learning.

A professional list of Papers, Tutorials, and Surveys on AI for Time Series in top AI conferences and journals.

Unified Training of Universal Time Series Forecasting Transformers

TimeGPT-1: production ready pre-trained Time Series Foundation Model for forecasting and anomaly detection. Generative pretrained transformer for time series trained on over 100B data points. It's ca...

Scalable and user friendly neural :brain: forecasting algorithms.

A Python toolkit/library for reality-centric machine/deep learning and data mining on partially-observed time series, including SOTA neural network models for scientific analysis tasks of imputation/c...

A professional list on Large (Language) Models and Foundation Models (LLM, LM, FM) for Time Series, Spatiotemporal, and Event Data.

A professionally curated list of awesome resources (paper, code, data, etc.) on transformers in time series.

Chronos: Pretrained Models for Probabilistic Time Series Forecasting

A unified multi-task time series model.

Modeltime unlocks time series forecast models and machine learning in one framework

The GitHub repository for the paper "Informer" accepted by AAAI 2021.

Time series Timeseries Deep Learning Machine Learning Python Pytorch fastai | State-of-the-art Deep Learning library for Time Series and Sequences in Pytorch / fastai

Fast and Accurate ML in 3 Lines of Code

State-of-the-Art Deep Learning scripts organized by models - easy to train and deploy with reproducible accuracy and performance on enterprise-grade infrastructure.

Statsmodels: statistical modeling and econometrics in Python

Probabilistic time series modeling in Python

[AAAI-23 Oral] Official implementation of the paper "Are Transformers Effective for Time Series Forecasting?"

Platform for building AI that can learn and answer questions over federated data.

State-of-the-Art Deep Learning scripts organized by models - easy to train and deploy with reproducible accuracy and performance on enterprise-grade infrastructure.

Scalable and user friendly neural :brain: forecasting algorithms.

Tool for producing high quality forecasts for time series data that has multiple seasonality with linear or non-linear growth.

Chronos: Pretrained Models for Probabilistic Time Series Forecasting

The GitHub repository for the paper "Informer" accepted by AAAI 2021.

Fast and Accurate ML in 3 Lines of Code

Statsmodels: statistical modeling and econometrics in Python

Time series Timeseries Deep Learning Machine Learning Python Pytorch fastai | State-of-the-art Deep Learning library for Time Series and Sequences in Pytorch / fastai

TimeGPT-1: production ready pre-trained Time Series Foundation Model for forecasting and anomaly detection. Generative pretrained transformer for time series trained on over 100B data points. It's ca...

Unified Training of Universal Time Series Forecasting Transformers

Lightning ⚡️ fast forecasting with statistical and econometric models.

Curated list of Machine Learning, NLP, Vision, Recommender Systems Project Ideas

A professionally curated list of awesome resources (paper, code, data, etc.) on transformers in time series.

A Python toolkit/library for reality-centric machine/deep learning and data mining on partially-observed time series, including SOTA neural network models for scientific analysis tasks of imputation/c...

A python library for user-friendly forecasting and anomaly detection on time series.

Probabilistic time series modeling in Python

Time series forecasting with machine learning models

A pip-installable PyTorch implementation of TSMixer, providing an easy-to-use and efficient solution for time-series forecasting.

Resources about time series forecasting and deep learning.

A pip-installable PyTorch implementation of TSMixer, providing an easy-to-use and efficient solution for time-series forecasting.

Access to Sulie foundation models for time-series forecasting 📈

The official code for "TEMPO: Prompt-based Generative Pre-trained Transformer for Time Series Forecasting (ICLR 2024)". TEMPO is one of the very first open source Time Series Foundation Models for fo...

Datasets for time series forecasting

Official implementation for "UniST: A Prompt-Empowered Universal Model for Urban Spatio-Temporal Prediction" (KDD 2024)

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

[ICML 2024] A novel, efficient approach combining convolutional operations with adaptive spectral analysis as a foundation model for different time series tasks

Unified Training of Universal Time Series Forecasting Transformers

Resources about time series forecasting and deep learning.

MOMENT: A Family of Open Time-series Foundation Models

Scalable and user friendly neural :brain: forecasting algorithms.

Chronos: Pretrained Models for Probabilistic Time Series Forecasting

A Python toolkit/library for reality-centric machine/deep learning and data mining on partially-observed time series, including SOTA neural network models for scientific analysis tasks of imputation/c...

A unified multi-task time series model.

{mvgam} R 📦 to fit Dynamic Bayesian Generalized Additive Models for multivariate modeling and forecasting

Time series forecasting with machine learning models

A professional list on Large (Language) Models and Foundation Models (LLM, LM, FM) for Time Series, Spatiotemporal, and Event Data.

TimeGPT-1: production ready pre-trained Time Series Foundation Model for forecasting and anomaly detection. Generative pretrained transformer for time series trained on over 100B data points. It's ca...

A professional list of Papers, Tutorials, and Surveys on AI for Time Series in top AI conferences and journals.

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Chronos: Pretrained Models for Probabilistic Time Series Forecasting

Platform for building AI that can learn and answer questions over federated data.

Fast and Accurate ML in 3 Lines of Code

Tool for producing high quality forecasts for time series data that has multiple seasonality with linear or non-linear growth.

State-of-the-Art Deep Learning scripts organized by models - easy to train and deploy with reproducible accuracy and performance on enterprise-grade infrastructure.

The GitHub repository for the paper "Informer" accepted by AAAI 2021.

Statsmodels: statistical modeling and econometrics in Python

Scalable and user friendly neural :brain: forecasting algorithms.

TimeGPT-1: production ready pre-trained Time Series Foundation Model for forecasting and anomaly detection. Generative pretrained transformer for time series trained on over 100B data points. It's ca...

A python library for user-friendly forecasting and anomaly detection on time series.

Time series Timeseries Deep Learning Machine Learning Python Pytorch fastai | State-of-the-art Deep Learning library for Time Series and Sequences in Pytorch / fastai

Unified Training of Universal Time Series Forecasting Transformers

A unified framework for machine learning with time series

A Python toolkit/library for reality-centric machine/deep learning and data mining on partially-observed time series, including SOTA neural network models for scientific analysis tasks of imputation/c...

A professionally curated list of awesome resources (paper, code, data, etc.) on transformers in time series.

Lightning ⚡️ fast forecasting with statistical and econometric models.

Probabilistic time series modeling in Python

Curated list of Machine Learning, NLP, Vision, Recommender Systems Project Ideas

MOMENT: A Family of Open Time-series Foundation Models

[AAAI-23 Oral] Official implementation of the paper "Are Transformers Effective for Time Series Forecasting?"

Access to Sulie foundation models for time-series forecasting 📈

scores: Metrics for the verification, evaluation and optimisation of forecasts, predictions or models.

The official code for "TEMPO: Prompt-based Generative Pre-trained Transformer for Time Series Forecasting (ICLR 2024)". TEMPO is one of the very first open source Time Series Foundation Models for fo...

A pip-installable PyTorch implementation of TSMixer, providing an easy-to-use and efficient solution for time-series forecasting.

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

MOMENT: A Family of Open Time-series Foundation Models

Wind Power Forecasting Based on Hybrid CEEMDAN-EWT Deep Learning Method

Scripts and notebooks to accompany the book Data-Driven Methods for Dynamic Systems

[ICML 2024] A novel, efficient approach combining convolutional operations with adaptive spectral analysis as a foundation model for different time series tasks

Unified Training of Universal Time Series Forecasting Transformers

Easy to Deploy Prediction Market Platform

A unified multi-task time series model.

Package for Time Series Forecasting and Anomaly Detection Problems.

{mvgam} R 📦 to fit Dynamic Bayesian Generalized Additive Models for multivariate modeling and forecasting

Datasets for time series forecasting

Chronos: Pretrained Models for Probabilistic Time Series Forecasting

This is an official implementation code for paper "A Survey on Time-Series Pre-Trained Models" (TKDE-24).

A Python toolkit/library for reality-centric machine/deep learning and data mining on partially-observed time series, including SOTA neural network models for scientific analysis tasks of imputation/c...

Bootstrap your large scale forecasting solution on Databricks with Many Models Forecasting (MMF) Project.

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

Chronos: Pretrained Models for Probabilistic Time Series Forecasting

Lag-Llama: Towards Foundation Models for Probabilistic Time Series Forecasting

Unified Training of Universal Time Series Forecasting Transformers

A unified multi-task time series model.

MOMENT: A Family of Open Time-series Foundation Models

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

Official implementation for "UniST: A Prompt-Empowered Universal Model for Urban Spatio-Temporal Prediction" (KDD 2024)

[ICML 2024] A novel, efficient approach combining convolutional operations with adaptive spectral analysis as a foundation model for different time series tasks

👖 Conformal Tights adds conformal prediction of coherent quantiles and intervals to any scikit-learn regressor or Darts forecaster

The official code for "TEMPO: Prompt-based Generative Pre-trained Transformer for Time Series Forecasting (ICLR 2024)". TEMPO is one of the very first open source Time Series Foundation Models for fo...

Materials for the Deploy and Monitor ML Pipelines with Python, Docker and GitHub Actions workshop at the PyData NYC 2024 conference

Access to Sulie foundation models for time-series forecasting 📈

Platform for building AI that can learn and answer questions over federated data.

Chronos: Pretrained Models for Probabilistic Time Series Forecasting

State-of-the-Art Deep Learning scripts organized by models - easy to train and deploy with reproducible accuracy and performance on enterprise-grade infrastructure.

Fast and Accurate ML in 3 Lines of Code

A python library for user-friendly forecasting and anomaly detection on time series.

Tool for producing high quality forecasts for time series data that has multiple seasonality with linear or non-linear growth.

Postgres with GPUs for ML/AI apps.

TimeGPT-1: production ready pre-trained Time Series Foundation Model for forecasting and anomaly detection. Generative pretrained transformer for time series trained on over 100B data points. It's ca...

Lag-Llama: Towards Foundation Models for Probabilistic Time Series Forecasting

Scalable and user friendly neural :brain: forecasting algorithms.

Time series Timeseries Deep Learning Machine Learning Python Pytorch fastai | State-of-the-art Deep Learning library for Time Series and Sequences in Pytorch / fastai

Statsmodels: statistical modeling and econometrics in Python

The GitHub repository for the paper "Informer" accepted by AAAI 2021.

Unified Training of Universal Time Series Forecasting Transformers

A unified framework for machine learning with time series

Lightning ⚡️ fast forecasting with statistical and econometric models.

A professionally curated list of awesome resources (paper, code, data, etc.) on transformers in time series.

Probabilistic time series modeling in Python

Curated list of Machine Learning, NLP, Vision, Recommender Systems Project Ideas

Time series forecasting with PyTorch

Chronos: Pretrained Models for Probabilistic Time Series Forecasting

MOMENT: A Family of Open Time-series Foundation Models

Lag-Llama: Towards Foundation Models for Probabilistic Time Series Forecasting

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

scores: Metrics for the verification, evaluation and optimisation of forecasts, predictions or models.

A pip-installable PyTorch implementation of TSMixer, providing an easy-to-use and efficient solution for time-series forecasting.

A repository for COVID-19 factors and impacts on US economy presented at HICSS-55 Conference

Access to Sulie foundation models for time-series forecasting 📈

Wind Power Forecasting Based on Hybrid CEEMDAN-EWT Deep Learning Method

Bootstrap your large scale forecasting solution on Databricks with Many Models Forecasting (MMF) Project.

The fastest way to make and track predictions

This repo contains my work & The code base for this TensorFlow Developer specialization offered by deeplearning.AI

Autoregressive Denoising Diffusion Models for Multivariate Probabilistic Time Series to benchmark datasets from different domains

Performed comparative analysis of BiLSTM, CNN-BiLSTM and CNN-BiLSTM with attention models for forecasting cases.

TimeGPT-1: production ready pre-trained Time Series Foundation Model for forecasting and anomaly detection. Generative pretrained transformer for time series trained on over 100B data points. It's ca...

A Python toolkit/library for reality-centric machine/deep learning and data mining on partially-observed time series, including SOTA neural network models for scientific analysis tasks of imputation/c...

Automated Bayesian model discovery for time series data

Resources about time series forecasting and deep learning.

Datasets for time series forecasting

Microsoft Finance Time Series Forecasting Framework (FinnTS) is a forecasting package that utilizes cutting-edge time series forecasting and parallelization on the cloud to produce accurate forecasts ...