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pro vyhledávání: '"Bifulco A"'
In the recent literature, various authors have studied spectral comparison results for Schr\"odinger operators with discrete spectrum in different settings including Euclidean domains and quantum graphs. In this note we derive such spectral compariso
Externí odkaz:
http://arxiv.org/abs/2412.15937
Autor:
Witowski, Jan, Zeng, Ken, Cappadona, Joseph, Elayoubi, Jailan, Chiru, Elena Diana, Chan, Nancy, Kang, Young-Joon, Howard, Frederick, Ostrovnaya, Irina, Fernandez-Granda, Carlos, Schnabel, Freya, Ozerdem, Ugur, Liu, Kangning, Steinsnyder, Zoe, Thakore, Nitya, Sadic, Mohammad, Yeung, Frank, Liu, Elisa, Hill, Theodore, Swett, Benjamin, Rigau, Danielle, Clayburn, Andrew, Speirs, Valerie, Vetter, Marcus, Sojak, Lina, Soysal, Simone Muenst, Baumhoer, Daniel, Choucair, Khalil, Zong, Yu, Daoud, Lina, Saad, Anas, Abdulsattar, Waleed, Beydoun, Rafic, Pan, Jia-Wern, Makmur, Haslina, Teo, Soo-Hwang, Pak, Linda Ma, Angel, Victor, Zilenaite-Petrulaitiene, Dovile, Laurinavicius, Arvydas, Klar, Natalie, Piening, Brian D., Bifulco, Carlo, Jun, Sun-Young, Yi, Jae Pak, Lim, Su Hyun, Brufsky, Adam, Esteva, Francisco J., Pusztai, Lajos, LeCun, Yann, Geras, Krzysztof J.
Treatment selection in breast cancer is guided by molecular subtypes and clinical characteristics. Recurrence risk assessment plays a crucial role in personalizing treatment. Current methods, including genomic assays, have limited accuracy and clinic
Externí odkaz:
http://arxiv.org/abs/2410.21256
Autor:
Gioacchini, Luca, Mellia, Marco, Drago, Idilio, Delsanto, Alexander, Siracusano, Giuseppe, Bifulco, Roberto
Generative AI agents, software systems powered by Large Language Models (LLMs), are emerging as a promising approach to automate cybersecurity tasks. Among the others, penetration testing is a challenging field due to the task complexity and the dive
Externí odkaz:
http://arxiv.org/abs/2410.03225
Autor:
Bifulco, Mario, Roversi, Luca
In this study, we initially investigate the application of a hybrid classical-quantum classifier (HCQC) for sentiment analysis, comparing its performance against the classical CPLEX classifier and the Transformer architecture. Our findings indicate t
Externí odkaz:
http://arxiv.org/abs/2409.16928
Autor:
Bifulco, Patrizio, Kerner, Joachim
We study Schr\"odinger operators on compact finite metric graphs subject to $\delta'$-coupling conditions. Based on a novel modified local Weyl law, we derive an explicit expression for the limiting mean eigenvalue distance of two different self-adjo
Externí odkaz:
http://arxiv.org/abs/2407.21719
Large Language Models (LLMs) changed the way we design and interact with software systems. Their ability to process and extract information from text has drastically improved productivity in a number of routine tasks. Developers that want to include
Externí odkaz:
http://arxiv.org/abs/2406.12334
Autor:
Zhao, Theodore, Gu, Yu, Yang, Jianwei, Usuyama, Naoto, Lee, Ho Hin, Naumann, Tristan, Gao, Jianfeng, Crabtree, Angela, Abel, Jacob, Moung-Wen, Christine, Piening, Brian, Bifulco, Carlo, Wei, Mu, Poon, Hoifung, Wang, Sheng
Biomedical image analysis is fundamental for biomedical discovery in cell biology, pathology, radiology, and many other biomedical domains. Holistic image analysis comprises interdependent subtasks such as segmentation, detection, and recognition of
Externí odkaz:
http://arxiv.org/abs/2405.12971
Autor:
Gioacchini, Luca, Siracusano, Giuseppe, Sanvito, Davide, Gashteovski, Kiril, Friede, David, Bifulco, Roberto, Lawrence, Carolin
The advances made by Large Language Models (LLMs) have led to the pursuit of LLM agents that can solve intricate, multi-step reasoning tasks. As with any research pursuit, benchmarking and evaluation are key corner stones to efficient and reliable pr
Externí odkaz:
http://arxiv.org/abs/2404.06411
Autor:
Bifulco, Patrizio, Mugnolo, Delio
We study the $p$-\emph{torsion function} and the corresponding $p$-\emph{torsional rigidity} associated with $p$-Laplacians and, more generally, $p$-Schr\"odinger operators, for $1
Externí odkaz:
http://arxiv.org/abs/2312.14131
Autor:
Naik, Narmada, Khandelwal, Ayush, Joshi, Mohit, Atre, Madhusudan, Wright, Hollis, Kannan, Kavya, Hill, Scott, Mamidipudi, Giridhar, Srinivasa, Ganapati, Bifulco, Carlo, Piening, Brian, Matlock, Kevin
Causal discovery is becoming a key part in medical AI research. These methods can enhance healthcare by identifying causal links between biomarkers, demographics, treatments and outcomes. They can aid medical professionals in choosing more impactful
Externí odkaz:
http://arxiv.org/abs/2311.07191