100 citations · 193 across the 10 of their papers we have counts for
5 papers · 1 filter
Vector-Valued Least-Squares Regression under Output Regularity Assumptions
Luc Brogat-Motte, Alessandro Rudi, Céline Brouard +2
We propose and analyse a reduced-rank method for solving least-squares regression problems with infinite dimensional output. We derive learning bounds for our method, and study und…
Learning to Predict Graphs with Fused Gromov-Wasserstein Barycenters
Luc Brogat-Motte, Rémi Flamary, Céline Brouard +2
This paper introduces a novel and generic framework to solve the flagship task of supervised labeled graph prediction by leveraging Optimal Transport tools. We formulate the proble…
Learning Output Embeddings in Structured Prediction
Luc Brogat-Motte, Alessandro Rudi, Céline Brouard +2
A powerful and flexible approach to structured prediction consists in embedding the structured objects to be predicted into a feature space of possibly infinite dimension by means…
Bayesian Metabolic Flux Analysis reveals intracellular flux couplings
Markus Heinonen, Maria Osmala, Henrik Mannerström +4
Metabolic flux balance analyses are a standard tool in analysing metabolic reaction rates compatible with measurements, steady-state and the metabolic reaction network stoichiometr…
Non-Stationary Gaussian Process Regression with Hamiltonian Monte Carlo
Markus Heinonen, Henrik Mannerström, Juho Rousu +2
We present a novel approach for fully non-stationary Gaussian process regression (GPR), where all three key parameters -- noise variance, signal variance and lengthscale -- can be…