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Probabilistic Theories of Deep Learning from first principles; Neurally-inspired learning and computation; Medical Imaging Diagnosis; Reverse-engineering neocortex; Deep Learning for Particle Physics, Data Science, Neuroengineering, Systems
Probabilistic Theories of Deep Learning from first principles; Neurally-inspired learning and computation; Medical Imaging Diagnosis; Reverse-engineering neocortex; Deep Learning for Particle Physics, Data Science, Neuroengineering, Systems
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论文共 81 篇作者统计合作学者相似作者
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Scientific Reportsno. 1 (2024): 1-12
Satpreet Harcharan Singh, Kevin Jiang, Kanchan Bhasin, Ashutosh Sabharwal,Nidal Moukaddam,Ankit B Patel
arxiv(2024)
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Anthony Kaspa R Allam, Vincent R Allam, Sandesh Reddy,Ankit Patel, Emmanouil R Froudarakis,Eric M Rohren,Sameer Sheth, T. Dorina Papageorgiou
biorxiv(2024)
Nicholas E. Charron,Felix Musil,Andrea Guljas,Yaoyi Chen, Klara Bonneau, Aldo S. Pasos-Trejo, Jacopo Venturin, Daria Gusew,Iryna Zaporozhets,Andreas Krämer,Clark Templeton,Atharva Kelkar,
arXiv (Cornell University) (2023)
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arxiv(2023)
McKell Woodland, Mais Al Taie, Jessica Albuquerque Marques Silva, Mohamed Eltaher, Frank Mohn, Alexander Shieh, Austin Castelo,Suprateek Kundu, Joshua P. Yung,Ankit B. Patel,Kristy K. Brock
CoRR (2023)
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McKell Woodland, Nihil Patel,Mais Al Taie, Joshua P. Yung,Tucker J. Netherton,Ankit B. Patel,Kristy K. Brock
UNCERTAINTY FOR SAFE UTILIZATION OF MACHINE LEARNING IN MEDICAL IMAGING, UNSURE 2023 (2023): 147-156
CoRR (2023)
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