155 citations · 356 across the 34 of their papers we have counts for
7 papers · 1 filter
Latent Inference-Time Guidance of Time Series Foundation Models
Chloé Hashimoto-Cullen, Amaury Durand, Laurent Bozzi +3
Time Series Foundation Models (TSFMs) currently provide state-of-the-art results in forecasting tasks. They are available out-of-the-box and rely on in-context learning to make the…
Forecasting time series with constraints
Nathan Doumèche, Francis Bach, Éloi Bedek +3
Time series forecasting presents unique challenges that limit the effectiveness of traditional machine learning algorithms. To address these limitations, various approaches have in…
Conformal Prediction for Hierarchical Data
Guillaume Principato, Gilles Stoltz, Yvenn Amara-Ouali +3
We consider conformal prediction for multivariate data and focus on hierarchical data, where some components are linear combinations of others. Intuitively, the hierarchical struct…
Adaptive Conformal Predictions for Time Series
Margaux Zaffran, Aymeric Dieuleveut, Olivier Féron +2
Uncertainty quantification of predictive models is crucial in decision-making problems. Conformal prediction is a general and theoretically sound answer. However, it requires excha…
Nonnegative matrix factorization with side information for time series recovery and prediction
Jiali Mei, Yohann De Castro, Yannig Goude +2
Motivated by the reconstruction and the prediction of electricity consumption, we extend Nonnegative Matrix Factorization~(NMF) to take into account side information (column or row…
Recovering Multiple Nonnegative Time Series From a Few Temporal Aggregates
Jiali Mei, Yohann De Castro, Yannig Goude +1
Motivated by electricity consumption metering, we extend existing nonnegative matrix factorization (NMF) algorithms to use linear measurements as observations, instead of matrix en…
Forecasting electricity consumption by aggregating specialized experts
Marie Devaine, Pierre Gaillard, Yannig Goude +1
We consider the setting of sequential prediction of arbitrary sequences based on specialized experts. We first provide a review of the relevant literature and present two theoretic…