Zobrazeno 1 - 10
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pro vyhledávání: '"A A Elyas"'
Traditional natural disaster response involves significant coordinated teamwork where speed and efficiency are key. Nonetheless, human limitations can delay critical actions and inadvertently increase human and economic losses. Agentic Large Vision L
Externí odkaz:
http://arxiv.org/abs/2411.01511
Autor:
Obbad, Elyas, Mlauzi, Iddah, Miranda, Brando, Schaeffer, Rylan, Obbad, Kamal, Bedi, Suhana, Koyejo, Sanmi
Data selection is crucial for optimizing language model (LM) performance on specific tasks, yet most existing methods fail to effectively consider the target task distribution. Current approaches either ignore task-specific requirements entirely or r
Externí odkaz:
http://arxiv.org/abs/2410.18194
Existing unsupervised keypoint detection methods apply artificial deformations to images such as masking a significant portion of images and using reconstruction of original image as a learning objective to detect keypoints. However, this approach la
Externí odkaz:
http://arxiv.org/abs/2410.14700
Transformers have made significant strides across various artificial intelligence domains, including natural language processing, computer vision, and audio processing. This success has naturally garnered considerable interest from both academic and
Externí odkaz:
http://arxiv.org/abs/2408.04723
Convolutional neural networks (CNNs) and Transformers have shown advanced accuracy in crack detection under certain conditions. Yet, the fixed local attention can compromise the generalisation of CNNs, and the quadratic complexity of the global self-
Externí odkaz:
http://arxiv.org/abs/2406.16518
Artificial intelligence has dramatically reshaped our interaction with digital technologies, ushering in an era where advancements in AI algorithms and Large Language Models (LLMs) have natural language processing (NLP) systems like ChatGPT. This stu
Externí odkaz:
http://arxiv.org/abs/2406.06616
Autor:
Furey, Brandon J., Wu, Zhenlin, Isaza-Monsalve, Mariano, Walser, Stefan, Mattivi, Elyas, Nardi, René, Schindler, Philipp
The rotation of trapped molecules offers a promising platform for quantum technologies and quantum information processing. In parallel, quantum error correction codes that can protect quantum information encoded in rotational states of a single molec
Externí odkaz:
http://arxiv.org/abs/2405.02236
Vision-based crack detection faces deployment challenges due to the size of robust models and edge device limitations. These can be addressed with lightweight models trained with knowledge distillation (KD). However, state-of-the-art (SOTA) KD method
Externí odkaz:
http://arxiv.org/abs/2404.06258
Autor:
Boruah, Supranta S., Eifler, Tim, Miranda, Vivian, Farah, Elyas, Motka, Jay, Krause, Elisabeth, Fang, Xiao, Rogozenski, Paul, Collaboration, The LSST Dark Energy Science
Validating modeling choices through simulated analyses and quantifying the impact of different systematic effects will form a major computational bottleneck in the preparation for 3$\times$2 analysis with Stage-IV surveys such as Vera Rubin Observato
Externí odkaz:
http://arxiv.org/abs/2403.11797
Autor:
Wu, Zhenlin, Walser, Stefan, Podlesnic, Verena, Isaza-Monsalve, Mariano, Mattivi, Elyas, Mu, Guanqun, Nardi, René, Gniewek, Piotr, Tomza, Michał, Furey, Brandon J., Schindler, Philipp
Publikováno v:
J. Chem. Phys. 161, 044304 (2024)
Molecular ions that are generated by chemical reactions with trapped atomic ions can serve as an accessible testbed for developing molecular quantum technologies. On the other hand, they are also a hindrance to scaling up quantum computers based on a
Externí odkaz:
http://arxiv.org/abs/2401.10854