Zobrazeno 1 - 10
of 33
pro vyhledávání: '"Hurwitz, Cole"'
Autor:
Zhang, Yizi, Wang, Yanchen, Jimenez-Beneto, Donato, Wang, Zixuan, Azabou, Mehdi, Richards, Blake, Winter, Olivier, Laboratory, International Brain, Dyer, Eva, Paninski, Liam, Hurwitz, Cole
Neuroscience research has made immense progress over the last decade, but our understanding of the brain remains fragmented and piecemeal: the dream of probing an arbitrary brain region and automatically reading out the information encoded in its neu
Externí odkaz:
http://arxiv.org/abs/2407.14668
Autor:
Hurwitz, Cole, Srivastava, Akash, Xu, Kai, Jude, Justin, Perich, Matthew G., Miller, Lee E., Hennig, Matthias H.
Latent dynamics models have emerged as powerful tools for modeling and interpreting neural population activity. Recently, there has been a focus on incorporating simultaneously measured behaviour into these models to further disentangle sources of ne
Externí odkaz:
http://arxiv.org/abs/2110.14853
Modern recording technologies now enable simultaneous recording from large numbers of neurons. This has driven the development of new statistical models for analyzing and interpreting neural population activity. Here we provide a broad overview of re
Externí odkaz:
http://arxiv.org/abs/2102.01807
Autor:
Srivastava, Akash, Bansal, Yamini, Ding, Yukun, Hurwitz, Cole Lincoln, Xu, Kai, Egger, Bernhard, Sattigeri, Prasanna, Tenenbaum, Joshua B., Le, Phuong, R, Arun Prakash, Zhou, Nengfeng, Vaughan, Joel, Wang, Yaquan, Bhattacharyya, Anwesha, Greenewald, Kristjan, Cox, David D., Gutfreund, Dan
Current autoencoder-based disentangled representation learning methods achieve disentanglement by penalizing the (aggregate) posterior to encourage statistical independence of the latent factors. This approach introduces a trade-off between disentang
Externí odkaz:
http://arxiv.org/abs/2010.13187
State-of-the-art models for high-resolution image generation, such as BigGAN and VQVAE-2, require an incredible amount of compute resources and/or time (512 TPU-v3 cores) to train, putting them out of reach for the larger research community. On the o
Externí odkaz:
http://arxiv.org/abs/2009.04433
Scalable Spike Source Localization in Extracellular Recordings using Amortized Variational Inference
Determining the positions of neurons in an extracellular recording is useful for investigating functional properties of the underlying neural circuitry. In this work, we present a Bayesian modelling approach for localizing the source of individual sp
Externí odkaz:
http://arxiv.org/abs/1905.12375
Akademický článek
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Reliable spike detection and sorting, the process of assigning each detected spike to its originating neuron, is an essential step in the analysis of extracellular electrical recordings from neurons. The volume and complexity of the data from recentl
Externí odkaz:
http://arxiv.org/abs/1809.01051
Autor:
Biderman, Dan, Whiteway, Matthew R, Hurwitz, Cole, Greenspan, Nicholas, Lee, Robert S, Vishnubhotla, Ankit, Warren, Richard, Pedraja, Federico, Noone, Dillon, Schartner, Michael, Huntenburg, Julia M, Khanal, Anup, Meijer, Guido T, Noel, Jean-Paul, Pan-Vazquez, Alejandro, Socha, Karolina Z, Urai, Anne E, Cunningham, John P, Sawtell, Nathaniel, Paninski, Liam
Publikováno v:
bioRxiv
Pose estimation algorithms are shedding new light on animal behavior and intelligence. Most existing models are only trained with labeled frames (supervised learning). Although effective in many cases, the fully supervised approach requires extensive
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=pmid________::35b9c308d6cbd2be678ceff9bed1627e
https://europepmc.org/articles/PMC10168383/
https://europepmc.org/articles/PMC10168383/
Autor:
Hurwitz, Cole Lincoln
The brain represents information about the world through the electrical activity of populations of neurons. By placing an electrode near a neuron that is firing (spiking), it is possible to detect the resulting extracellular action potential (EAP) th
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=od_______463::68e044fcf5128afd988d04af0572c5c5
https://hdl.handle.net/1842/38697
https://hdl.handle.net/1842/38697