From the 2 of 3.7k papers with an AI index.
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- Centre National de la Recherche ScientifiqueFR773 papers
- Sorbonne UniversitéFR404 papers
- Aix-Marseille UniversitéFR375 papers
- Istituto Nazionale di Fisica Nucleare, Sezione di Roma IIT371 papers
- Université Paris CitéFR371 papers
- University of OxfordGB371 papers
- Université Paris-SaclayFR367 papers
- Istituto Nazionale di Fisica Nucleare, Sezione di BolognaIT363 papers
- University of ZurichCH361 papers
- Institut National de Physique Nucléaire et de Physique des ParticulesFR357 papers
- Institute for High Energy PhysicsES356 papers
- University of CambridgeGB355 papers
78 papers · 1 filter
Unraveling real-time chemical shifts in the ultrafast regime
Daniel E. Rivas, Lorenzo Paoloni, Rebecca Boll +21
Traditional x-ray photoelectron spectroscopy (XPS) relies upon a direct mapping between the photoelectron binding energies and the local chemical environment, which is well-charact…
Euclid preparation. Review of forecast constraints on dark energy and modified gravity
Euclid Collaboration, N. Frusciante, M. Martinelli +326
The Euclid mission has been designed to provide, as one of its main deliverables, information on the nature of the gravitational interaction, which determines the expansion of the…
Euclid Quick Data Release (Q1). From simulations to sky: Advancing machine-learning lens detection with real Euclid data
Euclid Collaboration, N. E. P. Lines, T. E. Collett +301
In the era of large-scale surveys like Euclid, machine learning has become an essential tool for identifying rare yet scientifically valuable objects, such as strong gravitational…
Resolving the molecular gas emission of the z~2.5-2.8 starburst galaxies SPT0125-47 and SPT 2134-50
K. Kade, M. Bredberg, K. Knudsen +4
The comoving cosmic star formation rate density peaks at z~2-3, with dusty star-forming galaxies being significant contributors to this peak. These galaxies are characterized by th…
A Fast Volumetric Capture and Reconstruction Pipeline for Dynamic Point Clouds and Gaussian Splats
Athanasios Charisoudis, Simone Croci, Lam Kit Yung +2
We present a fast and efficient volumetric capture and reconstruction system that processes either RGB-D or RGB-only input to generate 3D representations in the form of point cloud…
Adaptive Pruning for Increased Robustness and Reduced Computational Overhead in Gaussian Process Accelerated Saddle Point Searches
Rohit Goswami, Hannes Jónsson
Gaussian process (GP) regression provides a strategy for accelerating saddle point searches on high-dimensional energy surfaces by reducing the number of times the energy and its d…