Zobrazeno 1 - 10
of 15
pro vyhledávání: '"Shah Rukh"'
Autor:
Patil, Snehal, Humayoun, Shah Rukh
Social Media platforms (e.g., Twitter, Facebook, etc.) are used heavily by public to provide news, opinions, and reactions towards events or topics. Integrating such data with the event or topic factual data could provide a more comprehensive underst
Externí odkaz:
http://arxiv.org/abs/2309.04724
Twitter is one of the popular social media platforms where people share news or reactions towards an event or topic using short text messages called "tweets". Emotion analysis in these tweets can play a vital role in understanding peoples' feelings t
Externí odkaz:
http://arxiv.org/abs/2309.04722
Visual exploration of multi-classification models with large number of classes would help machine learning experts in identifying the root cause of a problem that occurs during learning phase such as miss-classification of instances. Most of the prev
Externí odkaz:
http://arxiv.org/abs/2309.05676
The recent advancements in machine learning have motivated researchers to generate classification models dealing with hundreds of classes such as in the case of image datasets. However, visualization of classification models with high number of class
Externí odkaz:
http://arxiv.org/abs/2309.05672
Autor:
Qasim, Shah Rukh, Chernyavskaya, Nadezda, Kieseler, Jan, Long, Kenneth, Viazlo, Oleksandr, Pierini, Maurizio, Nawaz, Raheel
Publikováno v:
Eur. Phys. J. C 82, 753 (2022)
We present an end-to-end reconstruction algorithm to build particle candidates from detector hits in next-generation granular calorimeters similar to that foreseen for the high-luminosity upgrade of the CMS detector. The algorithm exploits a distance
Externí odkaz:
http://arxiv.org/abs/2204.01681
Autor:
Bhattacharya, Saptaparna, Chernyavskaya, Nadezda, Ghosh, Saranya, Gray, Lindsey, Kieseler, Jan, Klijnsma, Thomas, Long, Kenneth, Nawaz, Raheel, Pedro, Kevin, Pierini, Maurizio, Pradhan, Gauri, Qasim, Shah Rukh, Viazlo, Oleksander, Zehetner, Philipp
We present the current stage of research progress towards a one-pass, completely Machine Learning (ML) based imaging calorimeter reconstruction. The model used is based on Graph Neural Networks (GNNs) and directly analyzes the hits in each HGCAL endc
Externí odkaz:
http://arxiv.org/abs/2203.01189
Recently, a new window to explore tweet data has been opened in TExVis tool through visualizing the relations between the frequent keywords. However, timeline exploration of tweet data, not present in TExVis, could play a critical factor in understan
Externí odkaz:
http://arxiv.org/abs/2107.04799
The high-luminosity upgrade of the LHC will come with unprecedented physics and computing challenges. One of these challenges is the accurate reconstruction of particles in events with up to 200 simultaneous proton-proton interactions. The planned CM
Externí odkaz:
http://arxiv.org/abs/2106.01832
Autor:
Cashman, Dylan, Xu, Shenyu, Das, Subhajit, Heimerl, Florian, Liu, Cong, Humayoun, Shah Rukh, Gleicher, Michael, Endert, Alex, Chang, Remco
Most visual analytics systems assume that all foraging for data happens before the analytics process; once analysis begins, the set of data attributes considered is fixed. Such separation of data construction from analysis precludes iteration that ca
Externí odkaz:
http://arxiv.org/abs/2009.02865
Autor:
Iiyama, Yutaro, Cerminara, Gianluca, Gupta, Abhijay, Kieseler, Jan, Loncar, Vladimir, Pierini, Maurizio, Qasim, Shah Rukh, Rieger, Marcel, Summers, Sioni, Van Onsem, Gerrit, Wozniak, Kinga, Ngadiuba, Jennifer, Di Guglielmo, Giuseppe, Duarte, Javier, Harris, Philip, Rankin, Dylan, Jindariani, Sergo, Liu, Mia, Pedro, Kevin, Tran, Nhan, Kreinar, Edward, Wu, Zhenbin
Publikováno v:
Frontiers in Big Data 3 (2021) 44
Graph neural networks have been shown to achieve excellent performance for several crucial tasks in particle physics, such as charged particle tracking, jet tagging, and clustering. An important domain for the application of these networks is the FGP
Externí odkaz:
http://arxiv.org/abs/2008.03601