Abulfatah Akram Sayeed

Autor: Sayeed, Reza

Publikováno v: BMJ: British Medical Journal, 2008 Jun . 336(7658), 1443-1443.

Externí odkaz: https://www.jstor.org/stable/20510119

A quantized anomalous Hall effect above 4.2 K in stacked topological insulator/magnet bilayers

Autor: Jain, Rakshit, Roddy, Matthew, Gupta, Vishakha, Huang, Benjamin, Sayeed, Hasan M., Alnaser, Husain F., Vashist, Amit, Watanabe, Kenji, Taniguchi, Takashi, Deshpande, Vikram V., Sparks, Taylor D., Ralph, Daniel C.

Quantized anomalous Hall effects (QAHEs) occur in remarkable electronic states which possess not only quantized Hall signals but in some cases regions of dissipationless electron transport. The initial demonstrations of a QAHE in a magnetically-doped

Externí odkaz: http://arxiv.org/abs/2412.05380

A strategy to control synchronized dynamics in swarmalator systems

Autor: Sar, Gourab Kumar, Anwar, Md Sayeed, Moriamé, Martin, Ghosh, Dibakar, Carletti, Timoteo

Synchronization forms the basis of many coordination phenomena in natural systems, enabling them to function cohesively and support their fundamental operations. However, there are scenarios where synchronization disrupts a system's proper functionin

Externí odkaz: http://arxiv.org/abs/2411.19605

Reflections from the 2024 Large Language Model (LLM) Hackathon for Applications in Materials Science and Chemistry

Autor: Zimmermann, Yoel, Bazgir, Adib, Afzal, Zartashia, Agbere, Fariha, Ai, Qianxiang, Alampara, Nawaf, Al-Feghali, Alexander, Ansari, Mehrad, Antypov, Dmytro, Aswad, Amro, Bai, Jiaru, Baibakova, Viktoriia, Biswajeet, Devi Dutta, Bitzek, Erik, Bocarsly, Joshua D., Borisova, Anna, Bran, Andres M, Brinson, L. Catherine, Calderon, Marcel Moran, Canalicchio, Alessandro, Chen, Victor, Chiang, Yuan, Circi, Defne, Charmes, Benjamin, Chaudhary, Vikrant, Chen, Zizhang, Chiu, Min-Hsueh, Clymo, Judith, Dabhadkar, Kedar, Daelman, Nathan, Datar, Archit, Evans, Matthew L., Fard, Maryam Ghazizade, Fisicaro, Giuseppe, Gangan, Abhijeet Sadashiv, George, Janine, Gonzalez, Jose D. Cojal, Götte, Michael, Gupta, Ankur K., Harb, Hassan, Hong, Pengyu, Ibrahim, Abdelrahman, Ilyas, Ahmed, Imran, Alishba, Ishimwe, Kevin, Issa, Ramsey, Jablonka, Kevin Maik, Jones, Colin, Josephson, Tyler R., Juhasz, Greg, Kapoor, Sarthak, Kang, Rongda, Khalighinejad, Ghazal, Khan, Sartaaj, Klawohn, Sascha, Kuman, Suneel, Ladines, Alvin Noe, Leang, Sarom, Lederbauer, Magdalena, Liao, Sheng-Lun Mark, Liu, Hao, Liu, Xuefeng, Lo, Stanley, Madireddy, Sandeep, Maharana, Piyush Ranjan, Maheshwari, Shagun, Mahjoubi, Soroush, Márquez, José A., Mills, Rob, Mohanty, Trupti, Mohr, Bernadette, Moosavi, Seyed Mohamad, Moßhammer, Alexander, Naghdi, Amirhossein D., Naik, Aakash, Narykov, Oleksandr, Näsström, Hampus, Nguyen, Xuan Vu, Ni, Xinyi, O'Connor, Dana, Olayiwola, Teslim, Ottomano, Federico, Ozhan, Aleyna Beste, Pagel, Sebastian, Parida, Chiku, Park, Jaehee, Patel, Vraj, Patyukova, Elena, Petersen, Martin Hoffmann, Pinto, Luis, Pizarro, José M., Plessers, Dieter, Pradhan, Tapashree, Pratiush, Utkarsh, Puli, Charishma, Qin, Andrew, Rajabi, Mahyar, Ricci, Francesco, Risch, Elliot, Ríos-García, Martiño, Roy, Aritra, Rug, Tehseen, Sayeed, Hasan M, Scheidgen, Markus, Schilling-Wilhelmi, Mara, Schloz, Marcel, Schöppach, Fabian, Schumann, Julia, Schwaller, Philippe, Schwarting, Marcus, Sharlin, Samiha, Shen, Kevin, Shi, Jiale, Si, Pradip, D'Souza, Jennifer, Sparks, Taylor, Sudhakar, Suraj, Talirz, Leopold, Tang, Dandan, Taran, Olga, Terboven, Carla, Tropin, Mark, Tsymbal, Anastasiia, Ueltzen, Katharina, Unzueta, Pablo Andres, Vasan, Archit, Vinchurkar, Tirtha, Vo, Trung, Vogel, Gabriel, Völker, Christoph, Weinreich, Jan, Yang, Faradawn, Zaki, Mohd, Zhang, Chi, Zhang, Sylvester, Zhang, Weijie, Zhu, Ruijie, Zhu, Shang, Janssen, Jan, Foster, Ian, Blaiszik, Ben

Here, we present the outcomes from the second Large Language Model (LLM) Hackathon for Applications in Materials Science and Chemistry, which engaged participants across global hybrid locations, resulting in 34 team submissions. The submissions spann

Externí odkaz: http://arxiv.org/abs/2411.15221

Impact of Missing Values in Machine Learning: A Comprehensive Analysis

Autor: Ahmad, Abu Fuad, Sayeed, Md Shohel, Alshammari, Khaznah, Ahmed, Istiaque

Machine learning (ML) has become a ubiquitous tool across various domains of data mining and big data analysis. The efficacy of ML models depends heavily on high-quality datasets, which are often complicated by the presence of missing values. Consequ

Externí odkaz: http://arxiv.org/abs/2410.08295