9 citations · 22 across the 4 of their papers we have counts for
6 papers
AIFS-CRPS: Ensemble forecasting using a model trained with a loss function based on the Continuous Ranked Probability Score
Simon Lang, Mihai Alexe, Mariana C. A. Clare +15
Over the last three decades, ensemble forecasts have become an integral part of forecasting the weather. They provide users with more complete information than single forecasts as…
Probabilistic Rainfall Downscaling: Joint Generalized Neural Models with Censored Spatial Gaussian Copula
David Huk, Rilwan A. Adewoyin, Ritabrata Dutta
This work introduces a novel approach for generating conditional probabilistic rainfall forecasts with temporal and spatial dependence. A two-step procedure is employed. Firstly, m…
RSTGen: Imbuing Fine-Grained Interpretable Control into Long-FormText Generators
Rilwan A. Adewoyin, Ritabrata Dutta, Yulan He
In this paper, we study the task of improving the cohesion and coherence of long-form text generated by language models. To this end, we propose RSTGen, a framework that utilises R…
Probabilistic Forecasting with Generative Networks via Scoring Rule Minimization
Lorenzo Pacchiardi, Rilwan Adewoyin, Peter Dueben +1
Probabilistic forecasting relies on past observations to provide a probability distribution for a future outcome, which is often evaluated against the realization using a scoring r…
TRU-NET: A Deep Learning Approach to High Resolution Prediction of Rainfall
Rilwan Adewoyin, Peter Dueben, Peter Watson +2
Climate models (CM) are used to evaluate the impact of climate change on the risk of floods and strong precipitation events. However, these numerical simulators have difficulties r…
Part 1: Training Sets & ASG Transforms
Rilwan Adewoyin
In this paper, I discuss a method to tackle the issues arising from the small data-sets available to data-scientists when building price predictive algorithms that use monthly/quar…