111 citations · 801 across the 32 of their papers we have counts for
32 papers
Intrinsic Computational Functionalism: From Observer-Relative Maps to Observer-Independent Structures
Shuqin Ma, Ryota Kanai
Anti-computational arguments show that externally imposed computational interpretations cannot ground consciousness, but they do not establish that all computational organisations…
Euclid Quick Data Release (Q1): Hunting for luminous z > 6 galaxies in the Euclid Deep Fields -- forecasts and first bright detections
Euclid Collaboration, N. Allen, P. A. Oesch +309
The evolution of the rest-frame ultraviolet luminosity function (UV LF) is a powerful probe of early star formation and stellar mass build-up. At z > 6, its bright end (MUV < -21)…
Euclid Quick Data Release (Q1): Identification of massive galaxy candidates at the end of the Epoch of Reionisation
Euclid Collaboration, R. Navarro-Carrera, K. I. Caputi +295
Probing the presence and properties of massive galaxies at high redshift is one of the most critical tests for galaxy formation models. In this work, we search for galaxies with st…
All-optical bubble trap for ultracold atoms in microgravity
Romain Veyron, Clément Métayer, Jean-Baptiste Gérent +5
In this paper, we present an all-optical method to produce shell-shaped traps for ultracold atoms in microgravity. Our scheme exploits optical double dressing of the ground state t…
Euclid preparation. XCI. Validation method for the detections in the Euclid Catalogue of Galaxy Clusters using external data
Euclid Collaboration, J. -B. Melin, S. A. Stanford +315
We present our methodology for identifying known clusters as counterparts to objects in the Euclid Catalogue of Galaxy Clusters (ECGC). Euclid is expected to detect a large number…
Combined machine learning for stock selection strategy based on dynamic weighting methods
Lin Cai, Zhiyang He, Caiya Zhang
This paper proposes a novel stock selection strategy framework based on combined machine learning algorithms. Two types of weighting methods for three representative machine learni…