Zobrazeno 1 - 10
of 114 910
pro vyhledávání: '"ALEXANDRU, A."'
Autor:
Presacan, Oriana, Dorobantiu, Alexandru, Thambawita, Vajira, Riegler, Michael A., Stensen, Mette H., Iliceto, Mario, Aldea, Alexandru C., Sharma, Akriti
Accurate embryo morphology assessment is essential in assisted reproductive technology for selecting the most viable embryo. Artificial intelligence has the potential to enhance this process. However, the limited availability of embryo data presents
Externí odkaz:
http://arxiv.org/abs/2412.01255
Autor:
Manea, Alexandru, Pruneau, Claude, Brandibur, Diana Catalina, Danu, Andrea, Dobrin, Alexandru F., Gonzalez, Victor, Basu, Sumit
Balance functions have been regarded in the past as a method of investigating the late-stage hadronization found in the presence of a strongly-coupled medium. They are also used to constrain mechanisms of particle production in large and small collis
Externí odkaz:
http://arxiv.org/abs/2411.11207
Autor:
Isdrailǎ, Tudor-Alexandru, Wu, Jun-Yi
We propose a method for partial state reconstruction of multiphoton states in multimode ($N$-photon $M$-mode) linear optical networks (LONs) employing only two bucket photon-number-resolving (PNR) detectors. The reconstructed Heisenberg-Weyl-reduced
Externí odkaz:
http://arxiv.org/abs/2412.04271
Autor:
Crăciun, Cristian-George, Smădu, Răzvan-Alexandru, Cercel, Dumitru-Clementin, Cercel, Mihaela-Claudia
Pre-trained Language Models (PLMs) have shown remarkable performances in recent years, setting a new paradigm for NLP research and industry. The legal domain has received some attention from the NLP community partly due to its textual nature. Some ta
Externí odkaz:
http://arxiv.org/abs/2412.04119
Autor:
Andrei, Vlad C., Drăguţoiu, Alexandru P., Béna, Gabriel, Akl, Mahmoud, Li, Yin, Lohrmann, Matthias, Mönich, Ullrich J., Boche, Holger
This paper explores the potential of conversion-based neuromorphic algorithms for highly accurate and energy-efficient single-snapshot multidimensional harmonic retrieval (MHR). By casting the MHR problem as a sparse recovery problem, we devise the c
Externí odkaz:
http://arxiv.org/abs/2412.04008
Autor:
Rivera, Gabriela Calistro, Heirich, Oliver, Shrestha, Amita, Ferenczi, Agnes, Duliu, Alexandru, Eppinger, Jakob, Castella, Bruno Femenia, Fuchs, Christian, Garbagnati, Elisa, Laidlaw, Douglas, Lützen, Pia, De Marco, Innocenzo, Moll, Florian, Prell, Johannes, Reeves, Andrew, Nonay, Jorge Rosano, Roubal, Christian, Torres, Joana S., Wagner, Matthias
The EAGLE-1 mission aims to develop Europe's first sovereign, end-to-end space-based quantum key distribution (QKD) system. The mission is led by the European Space Agency (ESA) and SES in collaboration with several European National Space Agencies a
Externí odkaz:
http://arxiv.org/abs/2412.03222
Good datasets are essential for developing and benchmarking any machine learning system. Their importance is even more extreme for safety critical applications such as deepfake detection - the focus of this paper. Here we reveal that two of the most
Externí odkaz:
http://arxiv.org/abs/2412.00175
Autor:
Boncalo, Oana, Amaricai, Alexandru
This paper proposes a new iterative gradient descent decoding method for real number parity codes. The proposed decoder, named Gradient Descent Symbol Update (GDSU), is used for a class of low-density parity-check (LDPC) real-number codes that can be
Externí odkaz:
http://arxiv.org/abs/2411.16203
Fractional gradient descent has been studied extensively, with a focus on its ability to extend traditional gradient descent methods by incorporating fractional-order derivatives. This approach allows for more flexibility in navigating complex optimi
Externí odkaz:
http://arxiv.org/abs/2411.14855
Debugging is an essential skill when learning to program, yet its instruction and emphasis often vary widely across introductory courses. In the era of code-generating large language models (LLMs), the ability for students to reason about code and id
Externí odkaz:
http://arxiv.org/abs/2411.14303