143 citations
- Fukushima UniversityJP2 papers
- University of Agriculture FaisalabadPK2 papers
- Centre Antoine LacassagneFR1 paper
- COMSATS University IslamabadPK1 paper
- Government College University, FaisalabadPK1 paper
- Institut de Biologie ValroseFR1 paper
- Jazan UniversitySA1 paper
- King Saud UniversitySA1 paper
- Laboratoire Jean-Alexandre DieudonnéFR1 paper
- L. N. Gumilyov Eurasian National UniversityKZ1 paper
- Observatoire de la Côte d’AzurFR1 paper
- Shaheed Zulfiqar Ali Bhutto Institute of Science and TechnologyPK1 paper
9 papers
Physical constraints on the Maldacena-Shenker-Stanford chaos-bound in black hole spacetimes
Terkaa Victor Targema, Kazuharu Bamba, Riasat Ali +1
Chaotic motion near black holes has recently been examined through the lens of the Maldacena-Shenker-Stanford (MSS) chaos-bound, but reported violations remain contradictory. A sig…
Quantum-Enhanced Generative Models for Rare Event Prediction
M. Z. Haider, M. U. Ghouri, Tayyaba Noreen +1
Rare events such as financial crashes, climate extremes, and biological anomalies are notoriously difficult to model due to their scarcity and heavy-tailed distributions. Classical…
Charged Fuzzy Dark Matter Black Holes
Z. Yousaf, Bander Almutairi, S. Khan +1
We investigate the impact of fuzzy dark matter (FDM) on supermassive black holes (SMBHs) characterized by a spherical charge distribution. This work introduces a new class of spher…
Completely Deformed Complexity-free Anisotropic Fluid Sphere
Z. Yousaf, Kazuharu Bamba, M. Z. Bhatti +1
In this work, we investigate the emergence of compact, anisotropic stellar structures through the gravitational decoupling scheme within the framework of complete geometric deforma…
Ergodicity of some stochastic Fokker-Planck equations with additive common noise
François Delarue, Etienne Tanré, Raphaël Maillet
In this paper we consider stochastic Fokker-Planck Partial Differential Equations (PDEs), obtained as the mean-field limit of weakly interacting particle systems subjected to both…
Are labels informative in semi-supervised learning? -- Estimating and leveraging the missing-data mechanism
Aude Sportisse, Hugo Schmutz, Olivier Humbert +2
Semi-supervised learning is a powerful technique for leveraging unlabeled data to improve machine learning models, but it can be affected by the presence of ``informative'' labels,…