Zobrazeno 1 - 10
of 19 931
pro vyhledávání: '"A. Adeel"'
Publikováno v:
European Physical Journal C: Particles and Fields, Vol 84, Iss 6, Pp 1-13 (2024)
Abstract Building on the Einasto dark matter (DM) density parameterizations, this study explores the possibility of constructing DM black holes (BHs) within the formalism of the Starobinsky gravity model. This approach extends the solutions character
Externí odkaz:
https://doaj.org/article/99617e3185bd486eb5da97bf8232d375
We present TaxaBind, a unified embedding space for characterizing any species of interest. TaxaBind is a multimodal embedding space across six modalities: ground-level images of species, geographic location, satellite image, text, audio, and environm
Externí odkaz:
http://arxiv.org/abs/2411.00683
Publikováno v:
Mod. Phys. Lett. A (2024)
This research paper examines the feasibility and stability of compact stars in the context of $f(\mathcal{Q})$ theory, where $\mathcal{Q}$ represents the non-metricity scalar. To achieve this objective, a static spherical line element is assumed in t
Externí odkaz:
http://arxiv.org/abs/2410.16678
We investigate the supersymmetry breaking soft terms for all the viable models in the complete landscape of three-family supersymmetric Pati-Salam models arising from intersecting D6-branes on a $\mathbb{T}^6/(\mathbb{Z}_2\times \mathbb{Z}_2)$ orient
Externí odkaz:
http://arxiv.org/abs/2410.09093
We propose Scalable Mechanistic Neural Network (S-MNN), an enhanced neural network framework designed for scientific machine learning applications involving long temporal sequences. By reformulating the original Mechanistic Neural Network (MNN) (Perv
Externí odkaz:
http://arxiv.org/abs/2410.06074
We introduce Temporal Attention-enhanced Variational Graph Recurrent Neural Network (TAVRNN), a novel framework for analyzing the evolving dynamics of neuronal connectivity networks in response to external stimuli and behavioral feedback. TAVRNN capt
Externí odkaz:
http://arxiv.org/abs/2410.00665
Autor:
Da Costa, Lancelot, Gavenčiak, Tomáš, Hyland, David, Samiei, Mandana, Dragos-Manta, Cristian, Pattisapu, Candice, Razi, Adeel, Friston, Karl
This paper offers a roadmap for the development of scalable aligned artificial intelligence (AI) from first principle descriptions of natural intelligence. In brief, a possible path toward scalable aligned AI rests upon enabling artificial agents to
Externí odkaz:
http://arxiv.org/abs/2410.00258
Autor:
Kerner, Hannah, Chaudhari, Snehal, Ghosh, Aninda, Robinson, Caleb, Ahmad, Adeel, Choi, Eddie, Jacobs, Nathan, Holmes, Chris, Mohr, Matthias, Dodhia, Rahul, Ferres, Juan M. Lavista, Marcus, Jennifer
Crop field boundaries are foundational datasets for agricultural monitoring and assessments but are expensive to collect manually. Machine learning (ML) methods for automatically extracting field boundaries from remotely sensed images could help real
Externí odkaz:
http://arxiv.org/abs/2409.16252
Publikováno v:
JHEP 10 (2024) 252
Recently, the complete landscape of three-family supersymmetric Pati-Salam models from intersecting D6-branes on a type IIA $\mathbb{T}^6/(\mathbb{Z}_2\times \mathbb{Z}_2)$ orientifold has been enumerated consisting of 33 independent models with dist
Externí odkaz:
http://arxiv.org/abs/2409.09110
Autor:
Malik, Adeel, Ahadi, Mohsen, Kaltenberger, Florian, Warnke, Klaus, Thinh, Nguyen Tien, Bouknana, Nada, Thienot, Cedric, Onche, Godswill, Arora, Sagar
This paper presents, for the first time, an open-source implementation of the 3GPP Uplink Time Difference of Arrival (UL-TDoA) positioning method using the OpenAirInterface (OAI) framework. UL-TDoA is a critical positioning technique in 5G networks,
Externí odkaz:
http://arxiv.org/abs/2409.05217