42 citations · 76 across the 8 of their papers we have counts for
10 papers
WaveTransfer: A Flexible End-to-end Multi-instrument Timbre Transfer with Diffusion
Teysir Baoueb, Xiaoyu Bie, Hicham Janati +1
As diffusion-based deep generative models gain prevalence, researchers are actively investigating their potential applications across various domains, including music synthesis and…
Unbalanced CO-Optimal Transport
Quang Huy Tran, Hicham Janati, Nicolas Courty +4
Optimal transport (OT) compares probability distributions by computing a meaningful alignment between their samples. CO-optimal transport (COOT) takes this comparison further by in…
Averaging Spatio-temporal Signals using Optimal Transport and Soft Alignments
Hicham Janati, Marco Cuturi, Alexandre Gramfort
Several fields in science, from genomics to neuroimaging, require monitoring populations (measures) that evolve with time. These complex datasets, describing dynamics with both tim…
Inter-generational comparison of quantum annealers in solving hard scheduling problems
Bibek Pokharel, Zoe Gonzalez Izquierdo, P. Aaron Lott +6
We compare the performance of four quantum annealers, the D-Wave Two, 2X, 2000Q, and Advantage in solving an identical ensemble of a parametrized family of scheduling problems. The…
Debiased Sinkhorn barycenters
Hicham Janati, Marco Cuturi, Alexandre Gramfort
Entropy regularization in optimal transport (OT) has been the driver of many recent interests for Wasserstein metrics and barycenters in machine learning. It allows to keep the app…
Entropic Optimal Transport between Unbalanced Gaussian Measures has a Closed Form
Hicham Janati, Boris Muzellec, Gabriel Peyré +1
Although optimal transport (OT) problems admit closed form solutions in a very few notable cases, e.g. in 1D or between Gaussians, these closed forms have proved extremely fecund f…
Spatio-Temporal Alignments: Optimal transport through space and time
Hicham Janati, Marco Cuturi, Alexandre Gramfort
Comparing data defined over space and time is notoriously hard, because it involves quantifying both spatial and temporal variability, while at the same time taking into account th…
Multi-subject MEG/EEG source imaging with sparse multi-task regression
Hicham Janati, Thomas Bazeille, Bertrand Thirion +2
Magnetoencephalography and electroencephalography (M/EEG) are non-invasive modalities that measure the weak electromagnetic fields generated by neural activity. Estimating the loca…
Group level MEG/EEG source imaging via optimal transport: minimum Wasserstein estimates
Hicham Janati, Thomas Bazeille, Bertrand Thirion +2
Magnetoencephalography (MEG) and electroencephalogra-phy (EEG) are non-invasive modalities that measure the weak electromagnetic fields generated by neural activity. Inferring the…
Wasserstein regularization for sparse multi-task regression
Hicham Janati, Marco Cuturi, Alexandre Gramfort
We focus in this paper on high-dimensional regression problems where each regressor can be associated to a location in a physical space, or more generally a generic geometric space…