295 citations · 503 across the 5 of their papers we have counts for
8 papers
Robust detection and attribution of climate change under interventions
Enikő Székely, Sebastian Sippel, Nicolai Meinshausen +2
Fingerprints are key tools in climate change detection and attribution (D&A) that are used to determine whether changes in observations are different from internal climate variabil…
Empirical Bayes Transductive Meta-Learning with Synthetic Gradients
Shell Xu Hu, Pablo G. Moreno, Yang Xiao +4
We propose a meta-learning approach that learns from multiple tasks in a transductive setting, by leveraging the unlabeled query set in addition to the support set to generate a mo…
Tensor Decompositions for temporal knowledge base completion
Timothée Lacroix, Guillaume Obozinski, Nicolas Usunier
Most algorithms for representation learning and link prediction in relational data have been designed for static data. However, the data they are applied to usually evolves with ti…
A direct approach to detection and attribution of climate change
Eniko Székely, Sebastian Sippel, Reto Knutti +2
We present here a novel statistical learning approach for detection and attribution (D&A) of climate change. Traditional optimal D&A studies try to directly model the observations…
Integer programming on the junction tree polytope for influence diagrams
Axel Parmentier, Victor Cohen, Vincent Leclère +2
Influence Diagrams (ID) are a flexible tool to represent discrete stochastic optimization problems, including Markov Decision Process (MDP) and Partially Observable MDP as standard…
Learning the effect of latent variables in Gaussian Graphical models with unobserved variables
Marina Vinyes, Guillaume Obozinski
The edge structure of the graph defining an undirected graphical model describes precisely the structure of dependence between the variables in the graph. In many applications, the…