Search Results - "Barberan, C J"

Current progress and open challenges for applying deep learning across the biosciences by Sapoval, Nicolae, Aghazadeh, Amirali, Nute, Michael G., Antunes, Dinler A., Balaji, Advait, Baraniuk, Richard, Barberan, C. J., Dannenfelser, Ruth, Dun, Chen, Edrisi, Mohammadamin, Elworth, R. A. Leo, Kille, Bryce, Kyrillidis, Anastasios, Nakhleh, Luay, Wolfe, Cameron R., Yan, Zhi, Yao, Vicky, Treangen, Todd J.

“…Deep Learning (DL) has recently enabled unprecedented advances in one of the grand challenges in computational biology: the half-century-old problem of protein…”
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Multi-task network for automated analysis of high-resolution endomicroscopy images to detect cervical precancer and cancer by Brenes, David, Barberan, CJ, Hunt, Brady, Parra, Sonia G., Salcedo, Mila P., Possati-Resende, Júlio C., Cremer, Miriam L., Castle, Philip E., Fregnani, José H.T.G., Maza, Mauricio, Schmeler, Kathleen M., Baraniuk, Richard, Richards-Kortum, Rebecca

“…Cervical cancer is a public health emergency in low- and middle-income countries where resource limitations hamper standard-of-care prevention strategies. The…”
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To Petabytes and beyond: recent advances in probabilistic and signal processing algorithms and their application to metagenomics by Elworth, R A Leo, Wang, Qi, Kota, Pavan K, Barberan, C J, Coleman, Benjamin, Balaji, Advait, Gupta, Gaurav, Baraniuk, Richard G, Shrivastava, Anshumali, Treangen, Todd J

“…As computational biologists continue to be inundated by ever increasing amounts of metagenomic data, the need for data analysis approaches that keep up with…”
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Decoding the AI Pen: Techniques and Challenges in Detecting AI-Generated Text by Abdali, Sara, Anarfi, Richard, Barberan, CJ, He, Jia

“…Large Language Models (LLMs) have revolutionized the field of Natural Language Generation (NLG) by demonstrating an impressive ability to generate human-like…”
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NeuroView: Explainable Deep Network Decision Making by Barberan, C. J

“…Deep neural networks (DNs) provide superhuman performance in numerous computer vision tasks, yet it remains unclear exactly which of a DN's units contribute to…”
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NFT-K: Non-Fungible Tangent Kernels by Alemohammad, Sina, Babaei, Hossein, Barberan, Cj, Liu, Naiming, Luzi, Lorenzo, Mason, Blake, Baraniuk, Richard G.

“…Deep neural networks have become essential for numerous applications due to their strong empirical performance such as vision, RL, and classification…”
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GEM: Incorporating Context into Genomic Distance Estimation by Barberan, C. J

“…A pivotal question in computational biology is how similar two organisms are based on their genomic sequences. Unfortunately, classical sequence…”
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Can LLMs be Fooled? Investigating Vulnerabilities in LLMs by Abdali, Sara, He, Jia, Barberan, CJ, Anarfi, Richard

“…The advent of Large Language Models (LLMs) has garnered significant popularity and wielded immense power across various domains within Natural Language…”
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Securing Large Language Models: Threats, Vulnerabilities and Responsible Practices by Abdali, Sara, Anarfi, Richard, Barberan, CJ, He, Jia

“…Large language models (LLMs) have significantly transformed the landscape of Natural Language Processing (NLP). Their impact extends across a diverse spectrum…”
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NeuroView: Explainable Deep Network Decision Making by Barberan, CJ, Balestriero, Randall, Baraniuk, Richard G

“…Deep neural networks (DNs) provide superhuman performance in numerous computer vision tasks, yet it remains unclear exactly which of a DN's units contribute to…”
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NeuroView-RNN: It's About Time by Barberan, CJ, Alemohammad, Sina, Liu, Naiming, Balestriero, Randall, Baraniuk, Richard G

“…Recurrent Neural Networks (RNNs) are important tools for processing sequential data such as time-series or video. Interpretability is defined as the ability to…”
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NFT-K: Non-Fungible Tangent Kernels by Alemohammad, Sina, Babaei, Hossein, Barberan, CJ, Liu, Naiming, Luzi, Lorenzo, Mason, Blake, Baraniuk, Richard G

“…Deep neural networks have become essential for numerous applications due to their strong empirical performance such as vision, RL, and classification…”
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