Yannic Lops

Orcid: 0000-0002-2594-7845

According to our database1, Yannic Lops authored at least 11 papers between 2020 and 2023.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of five.

Timeline

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PhD thesis 
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Links

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Bibliography

2023
Spatiotemporal estimation of TROPOMI NO<sub>2</sub> column with depthwise partial convolutional neural network.
Neural Comput. Appl., July, 2023

A Deep Convolutional Neural Network Model for Improving WRF Simulations.
IEEE Trans. Neural Networks Learn. Syst., February, 2023

2022
Spatiotemporal Estimation of TROPOMI NO2 Column with Depthwise Partial Convolutional Neural Network.
CoRR, 2022

Deep learning solver for solving advection-diffusion​ equation in comparison to finite difference methods.
Commun. Nonlinear Sci. Numer. Simul., 2022

2021
Efficient PM<sub>2.5</sub> forecasting using geographical correlation based on integrated deep learning algorithms.
Neural Comput. Appl., 2021

2020
Using a deep convolutional neural network to predict 2017 ozone concentrations, 24 hours in advance.
Neural Networks, 2020

Real-time 7-day forecast of pollen counts using a deep convolutional neural network.
Neural Comput. Appl., 2020

A data ensemble approach for real-time air quality forecasting using extremely randomized trees and deep neural networks.
Neural Comput. Appl., 2020

A real-time hourly ozone prediction system using deep convolutional neural network.
Neural Comput. Appl., 2020

A Deep Convolutional Neural Network Model for improving WRF Forecasts.
CoRR, 2020

A Novel CMAQ-CNN Hybrid Model to Forecast Hourly Surface-Ozone Concentrations Fourteen Days in Advance.
CoRR, 2020


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