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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
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
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
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
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
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
Robust forecast aggregation
PNAS
Bayesian experts who are exposed to different evidence often make contradictory probabilistic forecasts. An aggregator, ignorant of the underlying model,...
30 months ago
Forecasting at Uber: An Introduction
Uber
This article is the first in a series dedicated to explaining how Uber leverages forecasting to build better products and services.
72 months ago
TiDE: the ‘embarrassingly’ simple MLP that beats Transformers
Towards Data Science
TiDE is a novel time-series encoder-decoder model that has shown to outperform state-of-the-art Transformer models in long-time horizon forecast.
8 months ago
Novel robust time series analysis for long-term and short-term prediction
Nature
Nonlinear phenomena are universal in ecology. However, their inference and prediction are generally difficult because of autocorrelation and...
38 months ago