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Generative probabilistic prediction of precipitation induced landslide deformation with variational autoencoder and gated recurrent unit
Frontiers
This paper introduces an innovative probabilistic prediction method using a Variational Autoencoder (VAE) combined with Gated Recurrent Unit (GRU) to forecast...
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.
6 months ago
Researchers from CMU and NYU Propose LLMTime: An Artificial Intelligence Method for Zero-Shot Time Series Forecasting with Large Language Models (LLMs)
MarkTechPost
Researchers from CMU and NYU Propose LLMTime: An Artificial Intelligence Method for Zero-Shot Time Series Forecasting with Large Language...
9 months ago
AAAI-24 Tutorial and Lab List
The Association for the Advancement of Artificial Intelligence
This tutorial, tailored for machine learning and applied math researchers and practitioners, focuses on emerging computational imaging applications.
8 months ago
Temporal Fusion Transformer: A Primer on Deep Forecasting in Python
Towards Data Science
End-to-End Example: Probabilistic Time Series Forecasts Using the TFT, an Attention-Based Neural Network. Heiko Onnen. Towards Data Science.
31 months ago
Exploring MSR Asia’s contributions to ICLR 2023: From robust machine learning to responsible AI
Microsoft
ICLR is recognized as one of the most influential international academic conferences in machine learning. At this year's conference,...
14 months ago
N-BEATS Unleashed: Deep Forecasting Using Neural Basis Expansion Analysis in Python
Towards Data Science
end-to-end example in Python: N-BEATS probabilistic forecast of a multivariate time series.
30 months ago
Facebook Prophet falls out of favour
Analytics India Magazine
In 2017, Meta open-sourced Prophet, a tool for producing high quality forecasts for time series data that has multiple seasonality with...
25 months ago
Probabilistic Prediction Intervals of Wind Speed Based on Explainable Neural Network
Frontiers
With the rapid growth of wind power penetration into modern power grids, wind speed forecasting plays an increasingly significant role in...
24 months ago
7 libraries that help in time-series problems
Towards Data Science
AutoTS is an automated time series forecasting library that can train multiple time series models using straightforward code.
37 months ago