130 citations · 290 across the 26 of their papers we have counts for
6 papers · 1 filter
Take It or Leave It: Intent-Controlled Partial Optimal Transport
Salil Parth Tripathi, Bertrand Chapron, Fabrice Collard +2
While optimal transport (OT) enforces a rigid constraint by requiring two measures to be matched exactly, partial optimal transport relaxes this requirement by allowing mass to rem…
Optimal sensor placement for the reconstruction of ocean states using differentiable Gumbel-Softmax sampling operator
Oscar Chapron, Ronan Fablet, Yann Stéphan
Accurately reconstructing and forecasting ocean fields from sparse observations is critical for both operational and scientific purposes. Optimizing sensor placement to maximize re…
Impact of geophysical fields on Deep Learning-based Lagrangian drift simulations
Daria Botvynko, Carlos Granero-Belinchon, Simon Van Gennip +2
We assess the influence of different Eulerian geophysical input fields on Lagrangian drift simulations using DriftNet, a learning-based method designed to simulate Lagrangian drift…
Static and auto-regressive neural emulation of phytoplankton biomass dynamics from physical predictors in the global ocean
Mahima Lakra, Ronan Fablet, Lucas Drumetz +2
Phytoplankton is the basis of marine food webs, driving both ecological processes and global biogeochemical cycles. Despite their ecological and climatic significance, accurately s…
Discovering Data Manifold Geometry through Geometric Properties
David Vigouroux, Lucas Drumetz, Ronan Fablet +1
A prevailing paradigm in modern representation learning is the map-first approach, in which a representation map is learned from reconstruction, embedding, or task objectives. At t…
Majorization-Minimization Networks for Inverse Problems: An Application to EEG Imaging
Le Minh Triet Tran, Sarah Reynaud, Ronan Fablet +3
Inverse problems are often ill-posed and require optimization schemes with strong stability and convergence guarantees. While learning-based approaches such as deep unrolling and m…