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pro vyhledávání: '"Yezerets, Eva"'
Identifying latent interactions within complex systems is key to unlocking deeper insights into their operational dynamics, including how their elements affect each other and contribute to the overall system behavior. For instance, in neuroscience, d
Externí odkaz:
http://arxiv.org/abs/2404.18267
Learning interpretable representations of neural dynamics at a population level is a crucial first step to understanding how observed neural activity relates to perception and behavior. Models of neural dynamics often focus on either low-dimensional
Externí odkaz:
http://arxiv.org/abs/2206.02972
Autor:
De Silva, Ashwin, Ramesh, Rahul, Ungar, Lyle, Shuler, Marshall Hussain, Cowan, Noah J., Platt, Michael, Li, Chen, Isik, Leyla, Roh, Seung-Eon, Charles, Adam, Venkataraman, Archana, Caffo, Brian, How, Javier J., Kebschull, Justus M, Krakauer, John W., Bichuch, Maxim, Kinfu, Kaleab Alemayehu, Yezerets, Eva, Jayaraman, Dinesh, Shin, Jong M., Villar, Soledad, Phillips, Ian, Priebe, Carey E., Hartung, Thomas, Miller, Michael I., Dey, Jayanta, Ningyuan, Huang, Eaton, Eric, Etienne-Cummings, Ralph, Ogburn, Elizabeth L., Burns, Randal, Osuagwu, Onyema, Mensh, Brett, Muotri, Alysson R., Brown, Julia, White, Chris, Yang, Weiwei, Rusu, Andrei A., Verstynen, Timothy, Kording, Konrad P., Chaudhari, Pratik, Vogelstein, Joshua T.
Learning is a process which can update decision rules, based on past experience, such that future performance improves. Traditionally, machine learning is often evaluated under the assumption that the future will be identical to the past in distribut
Externí odkaz:
http://arxiv.org/abs/2201.07372
Autor:
Perry, Ronan, Mehta, Ronak, Guo, Richard, Yezerets, Eva, Arroyo, Jesús, Powell, Mike, Helm, Hayden, Shen, Cencheng, Vogelstein, Joshua T.
Information-theoretic quantities, such as conditional entropy and mutual information, are critical data summaries for quantifying uncertainty. Current widely used approaches for computing such quantities rely on nearest neighbor methods and exhibit b
Externí odkaz:
http://arxiv.org/abs/1907.00325
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