Zobrazeno 1 - 10
of 456
pro vyhledávání: '"Ghosh Satrajit"'
Pre-trained deep learning embeddings have consistently shown superior performance over handcrafted acoustic features in speech emotion recognition (SER). However, unlike acoustic features with clear physical meaning, these embeddings lack clear inter
Externí odkaz:
http://arxiv.org/abs/2409.09511
Autor:
Gillon, Colleen J., Baker, Cody, Ly, Ryan, Balzani, Edoardo, Brunton, Bingni W., Schottdorf, Manuel, Ghosh, Satrajit, Dehghani, Nima
Across the life sciences, an ongoing effort over the last 50 years has made data and methods more reproducible and transparent. This openness has led to transformative insights and vastly accelerated scientific progress. For example, structural biolo
Externí odkaz:
http://arxiv.org/abs/2407.00976
Autor:
Johnson, Erik C., Nguyen, Thinh T., Dichter, Benjamin K., Zappulla, Frank, Kosma, Montgomery, Gunalan, Kabilar, Halchenko, Yaroslav O., Neufeld, Shay Q., Ratan, Kristen, Edwards, Nicholas J., Ressl, Susanne, Heilbronner, Sarah R., Schirner, Michael, Ritter, Petra, Wester, Brock, Ghosh, Satrajit, Martone, Maryann E., Pestilli, Franco, Yatsenko, Dimitri
Scientists are increasingly leveraging advances in instruments, automation, and collaborative tools to scale up their experiments and research goals, leading to new bursts of discovery. Various scientific disciplines, including neuroscience, have ado
Externí odkaz:
http://arxiv.org/abs/2401.00077
Autor:
Poldrack, Russell A., Markiewicz, Christopher J., Appelhoff, Stefan, Ashar, Yoni K., Auer, Tibor, Baillet, Sylvain, Bansal, Shashank, Beltrachini, Leandro, Benar, Christian G., Bertazzoli, Giacomo, Bhogawar, Suyash, Blair, Ross W., Bortoletto, Marta, Boudreau, Mathieu, Brooks, Teon L., Calhoun, Vince D., Castelli, Filippo Maria, Clement, Patricia, Cohen, Alexander L, Cohen-Adad, Julien, D'Ambrosio, Sasha, de Hollander, Gilles, de la iglesia-Vayá, María, de la Vega, Alejandro, Delorme, Arnaud, Devinsky, Orrin, Draschkow, Dejan, Duff, Eugene Paul, DuPre, Elizabeth, Earl, Eric, Esteban, Oscar, Feingold, Franklin W., Flandin, Guillaume, galassi, anthony, Gallitto, Giuseppe, Ganz, Melanie, Gau, Rémi, Gholam, James, Ghosh, Satrajit S., Giacomel, Alessio, Gillman, Ashley G, Gleeson, Padraig, Gramfort, Alexandre, Guay, Samuel, Guidali, Giacomo, Halchenko, Yaroslav O., Handwerker, Daniel A., Hardcastle, Nell, Herholz, Peer, Hermes, Dora, Honey, Christopher J., Innis, Robert B., Ioanas, Horea-Ioan, Jahn, Andrew, Karakuzu, Agah, Keator, David B., Kiar, Gregory, Kincses, Balint, Laird, Angela R., Lau, Jonathan C., Lazari, Alberto, Legarreta, Jon Haitz, Li, Adam, Li, Xiangrui, Love, Bradley C., Lu, Hanzhang, Maumet, Camille, Mazzamuto, Giacomo, Meisler, Steven L., Mikkelsen, Mark, Mutsaerts, Henk, Nichols, Thomas E., Nikolaidis, Aki, Nilsonne, Gustav, Niso, Guiomar, Norgaard, Martin, Okell, Thomas W, Oostenveld, Robert, Ort, Eduard, Park, Patrick J., Pawlik, Mateusz, Pernet, Cyril R., Pestilli, Franco, Petr, Jan, Phillips, Christophe, Poline, Jean-Baptiste, Pollonini, Luca, Raamana, Pradeep Reddy, Ritter, Petra, Rizzo, Gaia, Robbins, Kay A., Rockhill, Alexander P., Rogers, Christine, Rokem, Ariel, Rorden, Chris, Routier, Alexandre, Saborit-Torres, Jose Manuel, Salo, Taylor, Schirner, Michael, Smith, Robert E., Spisak, Tamas, Sprenger, Julia, Swann, Nicole C., Szinte, Martin, Takerkart, Sylvain, Thirion, Bertrand, Thomas, Adam G., Torabian, Sajjad, Varoquaux, Gael, Voytek, Bradley, Welzel, Julius, Wilson, Martin, Yarkoni, Tal, Gorgolewski, Krzysztof J.
The Brain Imaging Data Structure (BIDS) is a community-driven standard for the organization of data and metadata from a growing range of neuroscience modalities. This paper is meant as a history of how the standard has developed and grown over time.
Externí odkaz:
http://arxiv.org/abs/2309.05768
Autor:
Subash, Priyanka, Gray, Alex, Boswell, Misque, Cohen, Samantha L., Garner, Rachael, Salehi, Sana, Fisher, Calvary, Hobel, Samuel, Ghosh, Satrajit, Halchenko, Yaroslav, Dichter, Benjamin, Poldrack, Russell A., Markiewicz, Chris, Hermes, Dora, Delorme, Arnaud, Makeig, Scott, Behan, Brendan, Sparks, Alana, Arnott, Stephen R, Wang, Zhengjia, Magnotti, John, Beauchamp, Michael S., Pouratian, Nader, Toga, Arthur W., Duncan, Dominique
As data sharing has become more prevalent, three pillars - archives, standards, and analysis tools - have emerged as critical components in facilitating effective data sharing and collaboration. This paper compares four freely available intracranial
Externí odkaz:
http://arxiv.org/abs/2306.15041
Reliability of machine learning (ML) systems is crucial in safety-critical applications such as healthcare, and uncertainty estimation is a widely researched method to highlight the confidence of ML systems in deployment. Sequential and parallel ense
Externí odkaz:
http://arxiv.org/abs/2104.10715
Publikováno v:
BMC Medical Imaging, Vol 5, Iss 1, p 7 (2005)
Abstract Background To make inferences about brain structures or activity across multiple individuals, one first needs to determine the structural correspondences across their image data. We have recently developed Mindboggle as a fully automated, fe
Externí odkaz:
https://doaj.org/article/795c03d30ac441369f5a11bac90d426c
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Akademický článek
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Autor:
McClure, Patrick, Rho, Nao, Lee, John A., Kaczmarzyk, Jakub R., Zheng, Charles, Ghosh, Satrajit S., Nielson, Dylan, Thomas, Adam G., Bandettini, Peter, Pereira, Francisco
In this paper, we describe a Bayesian deep neural network (DNN) for predicting FreeSurfer segmentations of structural MRI volumes, in minutes rather than hours. The network was trained and evaluated on a large dataset (n = 11,480), obtained by combin
Externí odkaz:
http://arxiv.org/abs/1812.01719