Zobrazeno 1 - 10
of 18 444
pro vyhledávání: '"RAMASAMY, P"'
Autor:
Sfeir, Anthony, Petkova, Asya, Chaaya, Sabine, Chichova, Karina, Rossi, Marta, Vock, Anna, Mosut, Alessandro, Saravanaraj, Akshayanivasini Ramasamy, Sumini, Valentina, Nilsson, Tommy
As humans venture deeper into space, the need for a lunar settlement, housing the first group of settlers, grows steadily. By means of new technologies such as in situ resource utilisation (ISRU) as well as computational design, this goal can be impl
Externí odkaz:
http://arxiv.org/abs/2410.17114
Autor:
Ramasamy, Akilan, Hou, Lin, Bazantes, Jorge Vega, Irons, Tom J. P., Wibowo-Teale, Andrew M., Sun, Jianwei
Self-interaction error (SIE), arising from the imperfect cancellation of the spurious classical Coulomb interaction between an electron and itself, is a persistent challenge in modern density functional approximations. This issue is illustrated using
Externí odkaz:
http://arxiv.org/abs/2410.08887
Autor:
Ma'sum, Muhammad Anwar, Pratama, Mahardhika, Ramasamy, Savitha, Liu, Lin, Habibullah, Habibullah, Kowalczyk, Ryszard
Federated Class Incremental Learning (FCIL) is a new direction in continual learning (CL) for addressing catastrophic forgetting and non-IID data distribution simultaneously. Existing FCIL methods call for high communication costs and exemplars from
Externí odkaz:
http://arxiv.org/abs/2407.20705
Autor:
Thandapani, Rama Krishnan Gopal Ramasamy, Capel, Benjamin, Lasnier, Antoine, Chatzigiannakis, Ioannis
A widespread adoption of Virtual, Augmented, and Mixed Reality (VR/AR/MR), collectively referred to as Extended Reality (XR), has become a tangible possibility to revolutionize educational and training scenarios by offering immersive, interactive exp
Externí odkaz:
http://arxiv.org/abs/2407.06967
Autor:
Ma'sum, Muhammad Anwar, Pratama, Mahardhika, Savitha, Ramasamy, Liu, Lin, Habibullah, Kowalczyk, Ryszard
A continual learning (CL) model is desired for remote sensing image analysis because of varying camera parameters, spectral ranges, resolutions, etc. There exist some recent initiatives to develop CL techniques in this domain but they still depend on
Externí odkaz:
http://arxiv.org/abs/2406.18574
Autor:
Hu, Junfeng, Liu, Xu, Fan, Zhencheng, Yin, Yifang, Xiang, Shili, Ramasamy, Savitha, Zimmermann, Roger
Spatio-temporal graph neural networks have proven efficacy in capturing complex dependencies for urban computing tasks such as forecasting and kriging. Yet, their performance is constrained by the reliance on extensive data for training on a specific
Externí odkaz:
http://arxiv.org/abs/2405.12452
Autor:
Weng, Weiwei, Pratama, Mahardhika, Zhang, Jie, Chen, Chen, Yee, Edward Yapp Kien, Savitha, Ramasamy
Artificial neural networks, celebrated for their human-like cognitive learning abilities, often encounter the well-known catastrophic forgetting (CF) problem, where the neural networks lose the proficiency in previously acquired knowledge. Despite nu
Externí odkaz:
http://arxiv.org/abs/2405.07142
Autor:
Qiao, Zhongzheng, Pham, Xuan Huy, Ramasamy, Savitha, Jiang, Xudong, Kayacan, Erdal, Sarabakha, Andriy
In autonomous and mobile robotics, a principal challenge is resilient real-time environmental perception, particularly in situations characterized by unknown and dynamic elements, as exemplified in the context of autonomous drone racing. This study i
Externí odkaz:
http://arxiv.org/abs/2405.01054
Autor:
Qiao, Zhongzheng, Pham, Quang, Cao, Zhen, Le, Hoang H, Suganthan, P. N., Jiang, Xudong, Savitha, Ramasamy
Real-world environments are inherently non-stationary, frequently introducing new classes over time. This is especially common in time series classification, such as the emergence of new disease classification in healthcare or the addition of new act
Externí odkaz:
http://arxiv.org/abs/2402.12035
Autor:
Ramasamy, Rohan, Aleynikova, Ksenia, Nikulsin, Nikita, Hindenlang, Florian, Holod, Ihor, Strumberger, Erika, Hoelzl, Matthias, team, the JOREK
An important question for the outlook of stellarator reactors is their robustness against pressure driven modes, and the underlying mechanism behind experimentally observed soft $\beta$ limits. Towards building a robust answer to these questions, sim
Externí odkaz:
http://arxiv.org/abs/2402.02881