AI Chat AI Image Generator AI Video Text to Speech

Lorenz Trajectories Prediction: Travel Through Time

03/18/2019

∙

by Denisa Roberts, et al.

∙

∙

In this article the Lorenz dynamical system is revived and revisited and the current state of the art results for one step ahead forecasting for the Lorenz trajectories are published. The article is a reflection upon the evolution of neural networks with regards to the prediction performance on this canonical task.

research

∙ 08/04/2021

Reconstructing a dynamical system and forecasting time series by self-consistent deep learning

We introduce a self-consistent deep-learning framework which, for a nois...

18 Zhe Wang, et al. ∙

research

∙ 12/02/2020

Graph Neural Networks for Improved El Niño Forecasting

Deep learning-based models have recently outperformed state-of-the-art s...

0 Salva Rühling Cachay, et al. ∙

research

∙ 06/07/2023

Unlocking Insights into Business Trajectories with Transformer-based Spatio-temporal Data Analysis

The world of business is constantly evolving and staying ahead of the cu...

0 Muhammad Arslan, et al. ∙

research

∙ 02/03/2020

Error-feedback Stochastic Configuration Strategy on Convolutional Neural Networks for Time Series Forecasting

Despite the superiority of convolutional neural networks demonstrated in...

0 Xinze Zhang, et al. ∙

research

∙ 12/12/2019

Improved Activity Forecasting for Generating Trajectories

An efficient inverse reinforcement learning for generating trajectories ...

0 Daisuke Ogawa, et al. ∙

research

∙ 07/12/2021

PonderNet: Learning to Ponder

In standard neural networks the amount of computation used grows with th...

0 Andrea Banino, et al. ∙