9 citations
- École Normale Supérieure - PSLFR20 papers
- Centre National de la Recherche ScientifiqueFR3 papers
- Écologie Marine Tropicale des Océans Pacifique et IndienRE2 papers
- Université Paris CitéFR2 papers
- Université Paris-SudFR2 papers
- Arcetri Astrophysical ObservatoryIT1 paper
- Bordeaux Population HealthFR1 paper
- Centre Universitaire de MilaDZ1 paper
- Consejo Superior de Investigaciones CientíficasES1 paper
- Courant Institute of Mathematical SciencesUS1 paper
- Délégation Paris 6FR1 paper
- Département d'InformatiqueFR1 paper
21 papers
JWST observations of cosmic-ray-excited H in Barnard 68: spatial variations and constraints on cosmic-ray attenuation
David A. Neufeld, Kedron Silsbee, Alexei V. Ivlev +9
We present James Webb Space Telescope (JWST) NIRSpec observations of the starless dark cloud Barnard 68 that reveal the spatially-resolved signature of cosmic-ray excited molecular…
Fractional balanced chromatic number of signed subcubic graphs
Xiaolan Hu, Luis Kuffner, Jiaao Li +4
A signed graph is a pair , where is a graph and , called signature, is an assignment of signs to the edges. Given a signed graph wit…
PhenDiff: Revealing Subtle Phenotypes with Diffusion Models in Real Images
Anis Bourou, Thomas Boyer, Kévin Daupin +4
For the past few years, deep generative models have increasingly been used in biological research for a variety of tasks. Recently, they have proven to be valuable for uncovering s…
Unboxed data constructors -- or, how cpp decides a halting problem
Nicolas Chataing, Stephen Dolan, Gabriel Scherer +1
We propose a new language feature for ML-family languages, the ability to selectively unbox certain data constructors, so that their runtime representation gets compiled away to ju…
Implicit regularization of deep residual networks towards neural ODEs
Pierre Marion, Yu-Han Wu, Michael E. Sander +1
Residual neural networks are state-of-the-art deep learning models. Their continuous-depth analog, neural ordinary differential equations (ODEs), are also widely used. Despite thei…
Detecting Methane Plumes using PRISMA: Deep Learning Model and Data Augmentation
Alexis Groshenry, Clement Giron, Thomas Lauvaux +2
The new generation of hyperspectral imagers, such as PRISMA, has improved significantly our detection capability of methane (CH4) plumes from space at high spatial resolution (30m)…