40 citations · 185 across the 15 of their papers we have counts for
15 papers
Remote Sensing Data Assimilation with a Chained Hydrologic-hydraulic Model for Flood Forecasting
Thanh Huy Nguyen, Andrea Piacentini, Sophie Ricci +4
A chained hydrologic-hydraulic model is implemented using predicted runoff from a large-scale hydrologic model (namely ISBA-CTRIP) as inputs to local hydrodynamic models (TELEMAC-2…
Assimilation of SWOT Altimetry and Sentinel-1 Flood Extent Observations for Flood Reanalysis -- A Proof-of-Concept
Thanh Huy Nguyen, Sophie Ricci, Andrea Piacentini +3
In spite of astonishing advances and developments in remote sensing technologies, meeting the spatio-temporal requirements for flood hydrodynamic modeling remains a great challenge…
Gaussian Anamorphosis for Ensemble Kalman Filter Analysis of SAR-Derived Wet Surface Ratio Observations
Thanh Huy Nguyen, Sophie Ricci, Andrea Piacentini +3
Flood simulation and forecast capability have been greatly improved thanks to advances in data assimilation (DA) strategies incorporating various types of observations; many are de…
Enhancing Flood Forecasting with Dual State-Parameter Estimation and Ensemble-based SAR Data Assimilation
Thanh Huy Nguyen, Sophie Ricci, Andrea Piacentini +4
Ensemble data assimilation in flood forecasting depends strongly on the density, frequency and statistics of errors associated with the observation network. This work focuses on th…
Assimilation of SAR-derived Flood Observations for Improving Fluvial Flood Forecast
Thanh Huy Nguyen, Sophie Ricci, Andrea Piacentini +5
As the severity and occurrence of flood events tend to intensify with climate change, the need for flood forecasting capability increases. In this regard, the Flood Detection, Aler…
Validation and Improvement of Data Assimilation for Flood Hydrodynamic Modelling Using SAR Imagery Data
Thanh Huy Nguyen, Anthéa Delmotte, Christophe Fatras +3
Relevant comprehension of flood hazards has emerged as a crucial necessity, especially as the severity and the occurrence of flood events intensify with climate changes. Flood simu…
Improvement of Flood Extent Representation with Remote Sensing Data and Data Assimilation
Thanh Huy Nguyen, Sophie Ricci, Christophe Fatras +4
Flood simulation and forecast capability have been greatly improved thanks to advances in data assimilation. Such an approach combines in-situ gauge measurements with numerical hyd…
Super-Resolution-based Snake Model -- An Unsupervised Method for Large-Scale Building Extraction using Airborne LiDAR Data and Optical Image
Thanh Huy Nguyen, Sylvie Daniel, Didier Gueriot +2
Automatic extraction of buildings in urban and residential scenes has become a subject of growing interest in the domain of photogrammetry and remote sensing, particularly since mi…
On the Heavy-Tailed Theory of Stochastic Gradient Descent for Deep Neural Networks
Umut Şimşekli, Mert Gürbüzbalaban, Thanh Huy Nguyen +2
The gradient noise (GN) in the stochastic gradient descent (SGD) algorithm is often considered to be Gaussian in the large data regime by assuming that the \emph{classical} central…
Coarse-to-Fine Registration of Airborne LiDAR Data and Optical Imagery on Urban Scenes
Thanh Huy Nguyen, Sylvie Daniel, Didier Gueriot +2
Applications based on synergistic integration of optical imagery and LiDAR data are receiving a growing interest from the remote sensing community. However, a misaligned integratio…
Unsupervised Automatic Building Extraction Using Active Contour Model on Unregistered Optical Imagery and Airborne LiDAR Data
Thanh Huy Nguyen, Sylvie Daniel, Didier Gueriot +2
Automatic extraction of buildings in urban scenes has become a subject of growing interest in the domain of photogrammetry and remote sensing, particularly with the emergence of Li…
First Exit Time Analysis of Stochastic Gradient Descent Under Heavy-Tailed Gradient Noise
Thanh Huy Nguyen, Umut Şimşekli, Mert Gürbüzbalaban +1
Stochastic gradient descent (SGD) has been widely used in machine learning due to its computational efficiency and favorable generalization properties. Recently, it has been empiri…
Robust Building-based Registration of Airborne LiDAR Data and Optical Imagery on Urban Scenes
Thanh Huy Nguyen, Sylvie Daniel, Didier Gueriot +2
The motivation of this paper is to address the problem of registering airborne LiDAR data and optical aerial or satellite imagery acquired from different platforms, at different ti…
Non-Asymptotic Analysis of Fractional Langevin Monte Carlo for Non-Convex Optimization
Thanh Huy Nguyen, Umut Şimşekli, Gaël Richard
Recent studies on diffusion-based sampling methods have shown that Langevin Monte Carlo (LMC) algorithms can be beneficial for non-convex optimization, and rigorous theoretical gua…
Asynchronous Stochastic Quasi-Newton MCMC for Non-Convex Optimization
Umut Şimşekli, Çağatay Yıldız, Thanh Huy Nguyen +2
Recent studies have illustrated that stochastic gradient Markov Chain Monte Carlo techniques have a strong potential in non-convex optimization, where local and global convergence…