Nixtla / neuralforecast
Scalable and user friendly neural forecasting algorithms.
β3,487Updated this week
Alternatives and similar repositories for neuralforecast:
Users that are interested in neuralforecast are comparing it to the libraries listed below
- Scalable machine π€ learning for time series forecasting.β1,015Updated last month
- Time series forecasting with PyTorchβ4,280Updated last week
- Deep learning PyTorch library for time series forecasting, classification, and anomaly detection (originally for flood forecasting).β2,176Updated this week
- Lightning β‘οΈ fast forecasting with statistical and econometric models.β4,347Updated this week
- An offical implementation of PatchTST: "A Time Series is Worth 64 Words: Long-term Forecasting with Transformers." (ICLR 2023) https://arβ¦β1,929Updated 8 months ago
- Time series Timeseries Deep Learning Machine Learning Python Pytorch fastai | State-of-the-art Deep Learning library for Time Series anβ¦β5,605Updated 2 months ago
- TimeGPT-1: production ready pre-trained Time Series Foundation Model for forecasting and anomaly detection. Generative pretrained transfβ¦β2,723Updated last week
- Unified Training of Universal Time Series Forecasting Transformersβ1,123Updated last month
- Probabilistic time series modeling in Pythonβ4,863Updated 2 weeks ago
- Automated Time Series Forecastingβ1,273Updated 3 weeks ago
- Probabilistic Hierarchical forecasting π with statistical and econometric methods.β652Updated this week
- PyTorch based Probabilistic Time Series forecasting framework based on GluonTS backendβ1,305Updated 10 months ago
- A professionally curated list of awesome resources (paper, code, data, etc.) on transformers in time series.β2,741Updated 9 months ago
- [AAAI-23 Oral] Official implementation of the paper "Are Transformers Effective for Time Series Forecasting?"β2,201Updated last year
- A Python toolkit/library for reality-centric machine/deep learning and data mining on partially-observed time series, including SOTA neurβ¦β1,404Updated last week
- Multivariate Time Series Forecasting with efficient Transformers. Code for the paper "Long-Range Transformers for Dynamic Spatiotemporal β¦β847Updated last year
- [ICLR 2024] Official implementation of " π¦ Time-LLM: Time Series Forecasting by Reprogramming Large Language Models"β1,981Updated 6 months ago
- Resources about time series forecasting and deep learning.β654Updated last week
- About Code release for "Autoformer: Decomposition Transformers with Auto-Correlation for Long-Term Series Forecasting" (NeurIPS 2021), htβ¦β2,147Updated 2 months ago
- Official implementation for "iTransformer: Inverted Transformers Are Effective for Time Series Forecasting" (ICLR 2024 Spotlight), https:β¦β1,610Updated last month
- Keras/Pytorch implementation of N-BEATS: Neural basis expansion analysis for interpretable time series forecasting.β881Updated 2 years ago
- Lag-Llama: Towards Foundation Models for Probabilistic Time Series Forecastingβ1,431Updated last week
- A professional list of Papers, Tutorials, and Surveys on AI for Time Series in top AI conferences and journals.β1,401Updated last year
- A python library for user-friendly forecasting and anomaly detection on time series.β8,570Updated this week
- β772Updated 8 months ago
- N-BEATS is a neural-network based model for univariate timeseries forecasting. N-BEATS is a ServiceNow Research project that was started β¦β541Updated 2 years ago
- About Code release for "TimesNet: Temporal 2D-Variation Modeling for General Time Series Analysis" (ICLR 2023), https://openreview.net/pdβ¦β852Updated last year
- NeuralProphet: A simple forecasting packageβ4,073Updated 4 months ago
- Official code, datasets and checkpoints for "Timer: Generative Pre-trained Transformers Are Large Time Series Models" (ICML 2024)β609Updated 3 weeks ago
- MOMENT: A Family of Open Time-series Foundation Modelsβ509Updated last month