- Temporal dynamics of user activities🔍
- Predicting the temporal dynamics of turbulent channels through ...🔍
- Temporal dynamics in deep neural networks🔍
- Deep Learning Abilities to Classify Intricate Variations in Temporal ...🔍
- Exploring Temporal Information Dynamics in Spiking Neural Networks🔍
- A dynamic spatial–temporal deep learning framework for traffic ...🔍
- Temporal Graph Networks for Deep Learning on Dynamic Graphs🔍
- Modeling Temporal Dynamics and Spatial Configurations of Actions ...🔍
Temporal dynamics in deep neural networks
Temporal dynamics of user activities: deep learning strategies and ...
In this paper, we will discuss the profiling problem from two perspectives; how to mathematically model and track user's behavior over short and long periods.
Predicting the temporal dynamics of turbulent channels through ...
In their case, the model reduction is achieved through a convolutional neural-network auto-encoder (CNN–AE) and the training and prediction of the temporal ...
Temporal dynamics in deep neural networks - KU Leuven Research
An important goal of cognitive sciences is to connect cognition with underlying neural processes. Deep neural networks (DNNs) are a modern tool for ...
Predicting the temporal dynamics of turbulent channels through ...
Title:Predicting the temporal dynamics of turbulent channels through deep learning ... Abstract:The success of recurrent neural networks (RNNs) ...
Deep Learning Abilities to Classify Intricate Variations in Temporal ...
The aim of this work is to investigate the ability of deep learning (DL) architectures to learn temporal dynamics in multivariate time series.
Exploring Temporal Information Dynamics in Spiking Neural Networks
Most existing Spiking Neural Network (SNN) works state that. SNNs may utilize temporal information dynamics of spikes. However, an explicit analysis of temporal ...
A dynamic spatial–temporal deep learning framework for traffic ...
In this paper, we address the problem of multi-step traffic speed prediction, including both short- and long-term predictions.
Temporal Graph Networks for Deep Learning on Dynamic Graphs
In this paper, we present Temporal Graph Networks (TGNs), a generic, efficient framework for deep learning on dynamic graphs represented as ...
Modeling Temporal Dynamics and Spatial Configurations of Actions ...
Inspired by the great success of deep learning for RG-. B based action recognition [39, 26, 21], there is a grow- ing trend of using deep neural networks for ...
Comparison of deep neural networks to spatio-temporal cortical ...
Our results provide an algorithmically informed view on the spatio-temporal dynamics of visual object recognition in the human visual brain.
Temporal dynamics of user activities: deep learning strategies and ...
A dataset consisting of 30,000 tweets was built and manually annotated into 10 topic categories. Bi-LSTM and GRU models are applied to classify ...
Temporal Dynamics in Training Spiking Neural Networks - YouTube
Speakers, institutes & titles 1. Jason Eshraghian, University of California, Santa Cruz, Leveraging Temporal Dynamics in Training Spiking ...
Characterizing the temporal dynamics of object recognition by deep ...
Convolutional neural networks (CNNs) have recently emerged as promising models of human vision based on their ability to predict hemodynamic brain responses ...
Learning non-linear spatio-temporal dynamics with convolutional ...
popularized the use of Neural ODEs (NODEs), which permit differential equations to be easily integrated within a deep-learning framework [13]. The ability to ...
Knowledge-Guided Learning of Temporal Dynamics and its ...
Instead, a viable alternative is to learn the system dynamics directly from data, for example with deep learning models. However, traditional ...
Characterizing the temporal dynamics of object recognition by deep ...
Convolutional neural networks (CNNs) have recently emerged as promising models of human vision based on their ability to predict hemodynamic ...
Deep Neural Networks explain spatio-temporal dynamics of visual ...
Then, to explain how scene size representations might emerge in the brain, we trained a DNN on scene categorization. Representations of scene size emerged ...
Neural Point Process for Learning Spatiotemporal Event Dynamics
temporal point processes with deep learning to model continuous-time event sequences, see a recent review on neural TPP (Shchur et al.,. 2021). However, most ...
(PDF) Comparison of deep neural networks to spatio-temporal ...
Together our results provide an algorithmically informed view on the spatio-temporal dynamics of visual object recognition in the human visual brain.
Comparison of deep neural networks to spatio-temporal cortical ...
Together our results provide an algorithmically informed view on the spatio-temporal dynamics of visual object recognition in the human visual brain. Date ...