Zobrazeno 1 - 10
of 54 492
pro vyhledávání: '"SOHAIL, A."'
Measurements of jet substructure in ultra-relativistic heavy-ion collisions indicate that interactions with the quark-gluon plasma quench the jet showering process. Modern data-driven methods have shown promise in probing these modifications in the j
Externí odkaz:
http://arxiv.org/abs/2411.19389
Autor:
Danish, Muhammad Sohail, Munir, Muhammad Akhtar, Shah, Syed Roshaan Ali, Kuckreja, Kartik, Khan, Fahad Shahbaz, Fraccaro, Paolo, Lacoste, Alexandre, Khan, Salman
While numerous recent benchmarks focus on evaluating generic Vision-Language Models (VLMs), they fall short in addressing the unique demands of geospatial applications. Generic VLM benchmarks are not designed to handle the complexities of geospatial
Externí odkaz:
http://arxiv.org/abs/2411.19325
Autor:
Qureshi, Umar Sohail, Elayavalli, Raghav Kunnawalkam, Mozarsky, Luke, Caines, Helen, Mooney, Isaac
We present parameter sets corresponding to new underlying event tunes for the Herwig7.3 Monte Carlo event generator. The existing Herwig tunes are in good agreement with LHC data, however, they are not typically designed for center-of-mass energies b
Externí odkaz:
http://arxiv.org/abs/2411.16897
We present a phenomenology study probing pair production of supersymmetric charginos and neutralinos ("electroweakinos") with the vector boson fusion (VBF) topology in proton-proton collisions at CERN's Large Hadron Collider (LHC). In particular, we
Externí odkaz:
http://arxiv.org/abs/2411.13837
Autor:
Sohail, Shairoz
Kolmogorov-Arnold Networks have recently been introduced as a flexible alternative to multi-layer Perceptron architectures. In this paper, we examine the training dynamics of different KAN architectures and compare them with corresponding MLP formula
Externí odkaz:
http://arxiv.org/abs/2411.05296
Autor:
Bahmani, Sohail
We derive a fundamental trade-off between standard and adversarial risk in a rather general situation that formalizes the following simple intuition: "If no (nearly) optimal predictor is smooth, adversarial robustness comes at the cost of accuracy."
Externí odkaz:
http://arxiv.org/abs/2411.05853
Autor:
Khan, Sohail
These lecture notes provide a comprehensive guide on Grid Modeling of Renewable Energy, offering a foundational overview of power system network modeling, power flow, and load flow algorithms critical for electrical and renewable energy engineering.
Externí odkaz:
http://arxiv.org/abs/2410.22361
Autor:
Obeid, Ahmad, Boumaraf, Said, Sohail, Anabia, Hassan, Taimur, Javed, Sajid, Dias, Jorge, Bennamoun, Mohammed, Werghi, Naoufel
Recent years witnessed remarkable progress in computational histopathology, largely fueled by deep learning. This brought the clinical adoption of deep learning-based tools within reach, promising significant benefits to healthcare, offering a valuab
Externí odkaz:
http://arxiv.org/abs/2410.19820
Autor:
Farhangi, Sohail, Tucker-Drob, Robin
We answer a question of Bergelson and Lesigne by showing that the notion of van der Corput set does not depend on the F\o lner sequence used to define it. This result has been discovered independently by Sa\'ul Rodr\'iguez Mart\'in. Both ours and Rod
Externí odkaz:
http://arxiv.org/abs/2409.00806
Autor:
Khan, Asifullah, Sohail, Anabia, Fiaz, Mustansar, Hassan, Mehdi, Afridi, Tariq Habib, Marwat, Sibghat Ullah, Munir, Farzeen, Ali, Safdar, Naseem, Hannan, Zaheer, Muhammad Zaigham, Ali, Kamran, Sultana, Tangina, Tanoli, Ziaurrehman, Akhter, Naeem
Deep supervised learning models require high volume of labeled data to attain sufficiently good results. Although, the practice of gathering and annotating such big data is costly and laborious. Recently, the application of self supervised learning (
Externí odkaz:
http://arxiv.org/abs/2408.17059