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Lag-Llama: Open-Source Foundation Model for Time Series Forecasting
Towards Data Science
Lag-Llama is built for univariate probabilistic forecasting. It uses a general method for tokenizing time series data that does not rely on frequency.
6 months ago
Bayesian learning for the robust verification of autonomous robots | Communications Engineering
Nature
Autonomous robots used in infrastructure inspection, space exploration and other critical missions operate in highly dynamic environments.
7 months ago
Nixtla Releases StatsForecast 1.7.5: Elevating Time Series Forecasting with MFLES and Scikit-Learn Integration
MarkTechPost
This release introduces the innovative MFLES model and a convenient wrapper for scikit-learn models, allowing users to leverage exogenous features easily.
3 months ago
AAAI-24 Tutorial and Lab List
The Association for the Advancement of Artificial Intelligence
Sponsored by the Association for the Advancement of Artificial Intelligence February 20-21, 2024 | Vancouver Convention Centre – West Building | Vancouver,...
9 months ago
Time Series Augmentations. A simple yet effective way to increase… | by Alexander Nikitin
Towards Data Science
In this tutorial, I will delve into the world of time series augmentations, shedding light on their significance and providing concrete examples of their...
10 months ago
A robust deep learning detector for sleep spindles and K-complexes: towards population norms
Nature
We introduce the Sleep EEG Event Detector (SEED), a deep learning system that outperforms existing approaches in SS and KC detection.
8 months ago
NeuralForecast 1.7.4 Released: Nixtla’s Advanced Library Revolutionizes Neural Forecasting with Usability and Robustness
MarkTechPost
Nixtla has announced the release of NeuralForecast, an advanced library designed to offer a robust and user-friendly collection of neural forecasting models.
1 month ago
Five Practical Applications of the LSTM Model for Time Series, with Code
Towards Data Science
There are five applications for LSTM that I think will all work fantastically using the library: univariate forecasting, multivariate forecasting,...
11 months ago
Darts: A New Python Library for User-Friendly Forecasting and Anomaly Detection on Time Series
MarkTechPost
Darts is Python library that aims to be the scikit-learn for time series analysis. By providing a unified and consistent API, Darts simplifies the end-to-end...
1 month ago
AutoGluon-TimeSeries: Every Time Series Forecasting Model In One Library
Towards Data Science
Last year, Amazon built an extension of its AutoGluon library, which focuses on time-series — known as AutoGluon-Timeseries(AG-TS)[1].
8 months ago