research
∙
08/05/2023
A generative model for surrogates of spatial-temporal wildfire nowcasting
Recent increase in wildfires worldwide has led to the need for real-time...
share
research
∙
07/03/2023
A novel approach for predicting epidemiological forecasting parameters based on real-time signals and Data Assimilation
This paper proposes a novel approach to predict epidemiological paramete...
research
∙
06/07/2023
Generative Text-Guided 3D Vision-Language Pretraining for Unified Medical Image Segmentation
Vision-Language Pretraining (VLP) has demonstrated remarkable capabiliti...
research
∙
04/29/2023
Analyzing drop coalescence in microfluidic device with a deep learning generative model
Predicting drop coalescence based on process parameters is crucial for e...
research
∙
03/22/2023
Frozen Language Model Helps ECG Zero-Shot Learning
The electrocardiogram (ECG) is one of the most commonly used non-invasiv...
research
∙
03/18/2023
Machine learning with data assimilation and uncertainty quantification for dynamical systems: a review
Data Assimilation (DA) and Uncertainty quantification (UQ) are extensive...
research
∙
04/07/2022
Generalised Latent Assimilation in Heterogeneous Reduced Spaces with Machine Learning Surrogate Models
Reduced-order modelling and low-dimensional surrogate models generated u...
research
∙
01/07/2022
Forecasting emissions through Kaya identity using Neural Ordinary Differential Equations
Starting from the Kaya identity, we used a Neural ODE model to predict t...
research
∙
10/27/2021
A Scalable Inference Method For Large Dynamic Economic Systems
The nature of available economic data has changed fundamentally in the l...
research
∙
05/29/2021
Correcting public opinion trends through Bayesian data assimilation
Measuring public opinion is a key focus during democratic elections, ena...
research
∙
04/13/2021
Adversarial autoencoders and adversarial LSTM for improved forecasts of urban air pollution simulations
This paper presents an approach to improve the forecast of computational...
research
∙
02/03/2021
Digital twins based on bidirectional LSTM and GAN for modelling COVID-19
The outbreak of the coronavirus disease 2019 (COVID-19) has now spread t...
research
∙
01/06/2021
Attention-based Convolutional Autoencoders for 3D-Variational Data Assimilation
We propose a new 'Bi-Reduced Space' approach to solving 3D Variational D...
research
∙
01/05/2021
Adversarially trained LSTMs on reduced order models of urban air pollution simulations
This paper presents an approach to improve computational fluid dynamics ...
research
∙
12/22/2020
Data Assimilation in the Latent Space of a Neural Network
There is an urgent need to build models to tackle Indoor Air Quality iss...
research
∙
04/25/2020