1 citations · 1 across the 5 of their papers we have counts for
5 papers
Prequential posteriors
Shreya Sinha-Roy, Richard G. Everitt, Christian P. Robert +1
Data assimilation is a fundamental task in updating forecasting models upon observing new data, with applications ranging from weather prediction to online reinforcement learning.…
Signature Kernel Scoring Rule: A Spatio-Temporal Diagnostic for Probabilistic Weather Forecasting
Archer Dodson, Ritabrata Dutta
Modern weather forecasting has increasingly transitioned from numerical weather prediction (NWP) to data-driven machine learning forecasting techniques. While these new models prod…
Generalized Bayesian deep reinforcement learning
Shreya Sinha Roy, Richard G. Everitt, Christian P. Robert +1
Bayesian reinforcement learning (BRL) is a method that merges principles from Bayesian statistics and reinforcement learning to make optimal decisions in uncertain environments. As…
Your copula is a classifier in disguise: classification-based copula density estimation
David Huk, Mark Steel, Ritabrata Dutta
We propose reinterpreting copula density estimation as a discriminative task. Under this novel estimation scheme, we train a classifier to distinguish samples from the joint densit…
Quasi-Bayes meets Vines
David Huk, Yuanhe Zhang, Mark Steel +1
Recently proposed quasi-Bayesian (QB) methods initiated a new era in Bayesian computation by directly constructing the Bayesian predictive distribution through recursion, removing…