194 citations · 331 across the 7 of their papers we have counts for
7 papers
Latent diffusion models for generative precipitation nowcasting with accurate uncertainty quantification
Jussi Leinonen, Ulrich Hamann, Daniele Nerini +2
Diffusion models have been widely adopted in image generation, producing higher-quality and more diverse samples than generative adversarial networks (GANs). We introduce a latent…
Thunderstorm nowcasting with deep learning: a multi-hazard data fusion model
Jussi Leinonen, Ulrich Hamann, Ioannis V. Sideris +1
Predictions of thunderstorm-related hazards are needed in several sectors, including first responders, infrastructure management and aviation. To address this need, we present a de…
Seamless lightning nowcasting with recurrent-convolutional deep learning
Jussi Leinonen, Ulrich Hamann, Urs Germann
A deep learning model is presented to nowcast the occurrence of lightning at a five-minute time resolution 60 minutes into the future. The model is based on a recurrent-convolution…
Improvements to short-term weather prediction with recurrent-convolutional networks
Jussi Leinonen
The Weather4cast 2021 competition gave the participants a task of predicting the time evolution of two-dimensional fields of satellite-based meteorological data. This paper describ…
Spatiotemporal Weather Data Predictions with Shortcut Recurrent-Convolutional Networks: A Solution for the Weather4cast challenge
Jussi Leinonen
This paper presents the neural network model that was used by the author in the Weather4cast 2021 Challenge Stage 1, where the objective was to predict the time evolution of satell…
Stochastic Super-Resolution for Downscaling Time-Evolving Atmospheric Fields with a Generative Adversarial Network
Jussi Leinonen, Daniele Nerini, Alexis Berne
Generative adversarial networks (GANs) have been recently adopted for super-resolution, an application closely related to what is referred to as "downscaling" in the atmospheric sc…
HARK Side of Deep Learning -- From Grad Student Descent to Automated Machine Learning
Oguzhan Gencoglu, Mark van Gils, Esin Guldogan +5
Recent advancements in machine learning research, i.e., deep learning, introduced methods that excel conventional algorithms as well as humans in several complex tasks, ranging fro…