Zobrazeno 1 - 10
of 3 713
pro vyhledávání: '"A. Vértes"'
Autor:
Zhang, Jingwei, Swinnen, Lauren, Chatzichristos, Christos, Broux, Victoria, Proost, Renee, Jansen, Katrien, Mahler, Benno, Zabler, Nicolas, Epitashvilli, Nino, Dümpelmann, Matthias, Schulze-Bonhage, Andreas, Schriewer, Elisabeth, Ermis, Ummahan, Wolking, Stefan, Linke, Florian, Weber, Yvonne, Symmonds, Mkael, Sen, Arjune, Biondi, Andrea, Richardson, Mark P., Sulaiman I, Abuhaiba, Silva, Ana Isabel, Sales, Francisco, Vértes, Gergely, Van Paesschen, Wim, De Vos, Maarten
Objective: Most current wearable tonic-clonic seizure (TCS) detection systems are based on extra-cerebral signals, such as electromyography (EMG) or accelerometry (ACC). Although many of these devices show good sensitivity in seizure detection, their
Externí odkaz:
http://arxiv.org/abs/2403.13066
Autor:
Metz, Thomas O., Adkins, Joshua N., Armentrout, Peter B., Chain, Patrick, Chu, Fanny, Corley, Courtney D, Cort, John R., Denis, Elizabeth, Drell, Daniel, Duncan, Katherine R., Ewing, Robert G., Fernandez, Facundo M., Fiehn, Oliver, Garg, Neha, Grimme, Stefan, Henry, Christopher, Hettich, Robert L., Kind, Tobias, Linington, Roger G., Miller, Gary W., Northen, Trent, Overdahl, Kirsten, Patrinos, Ari, Raftery, Daniel, Rigor, Paul, Smith, Richard D., Sobus, Jon, Teeguarden, Justin, Vertes, Akos, Waters, Katrina, Webb-Robertson, Bobbie-Jo, Williams, Antony, Wishart, David
On August 9-10, 2023, a workshop was convened at the Pacific Northwest National Laboratory (PNNL) in Richland, WA that brought together a group of internationally recognized experts in metabolomics, natural products discovery, chemical ecology, chemi
Externí odkaz:
http://arxiv.org/abs/2311.11437
Autor:
Walker, Jacob, Vértes, Eszter, Li, Yazhe, Dulac-Arnold, Gabriel, Anand, Ankesh, Weber, Théophane, Hamrick, Jessica B.
State of the art reinforcement learning has enabled training agents on tasks of ever increasing complexity. However, the current paradigm tends to favor training agents from scratch on every new task or on collections of tasks with a view towards gen
Externí odkaz:
http://arxiv.org/abs/2302.04009
Autor:
Kossen, Jannik, Cangea, Cătălina, Vértes, Eszter, Jaegle, Andrew, Patraucean, Viorica, Ktena, Ira, Tomasev, Nenad, Belgrave, Danielle
We introduce a challenging decision-making task that we call active acquisition for multimodal temporal data (A2MT). In many real-world scenarios, input features are not readily available at test time and must instead be acquired at significant cost.
Externí odkaz:
http://arxiv.org/abs/2211.05039
Autor:
Nyárády, Balázs Bence1 (AUTHOR), Vértes, Miklós2 (AUTHOR), Dósa, Edit1 (AUTHOR) dosa.edit@semmelweis.hu, Yang, Xiao3 (AUTHOR), George, Charles J.4 (AUTHOR), Kiss, Enikő5 (AUTHOR), Baji, Ildikó6 (AUTHOR), Kapornai, Krisztina5 (AUTHOR), Kovacs, Maria7 (AUTHOR) kovacs@pitt.edu
Publikováno v:
Journal of Clinical Medicine. Aug2024, Vol. 13 Issue 16, p4640. 9p.
Autor:
Vértes András
Publikováno v:
Cardiologia Hungarica, Vol 54, Iss 1, Pp 43-46 (2024)
The guidelines of the European Society of Cardiology for the prevention of cardiovascular diseases recommend the use of the SCORE2 risk index instead of the classic SCORE risk index to calculate the cardiovascular risk -specifically, ten-year fatal a
Externí odkaz:
https://doaj.org/article/a4b02f9df7a64922865a0a78bf4b2aad
Autor:
Adamson, Chris, Adler, Sophie, Alexander-Bloch, Aaron F., Anagnostou, Evdokia, Anderson, Kevin M., Areces-Gonzalez, Ariosky, Astle, Duncan E., Auyeung, Bonnie, Ayub, Muhammad, Bae, Jong Bin, Ball, Gareth, Baron-Cohen, Simon, Beare, Richard, Bedford, Saashi A., Benegal, Vivek, Bethlehem, Richard A.I., Beyer, Frauke, Blangero, John, Cábez, Manuel Blesa, Boardman, James P., Borzage, Matthew, Bosch-Bayard, Jorge F., Bourke, Niall, Bullmore, Edward T., Calhoun, Vince D., Chakravarty, Mallar M., Chen, Christina, Chertavian, Casey, Chetelat, Gaël, Chong, Yap S., Corvin, Aiden, Costantino, Manuela, Courchesne, Eric, Crivello, Fabrice, Cropley, Vanessa L., Crosbie, Jennifer, Crossley, Nicolas, Delarue, Marion, Delorme, Richard, Desrivieres, Sylvane, Devenyi, Gabriel, Di Biase, Maria A., Dolan, Ray, Donald, Kirsten A., Donohoe, Gary, Dorfschmidt, Lena, Dunlop, Katharine, Edwards, Anthony D., Elison, Jed T., Ellis, Cameron T., Elman, Jeremy A., Eyler, Lisa, Fair, Damien A., Fletcher, Paul C., Fonagy, Peter, Franz, Carol E., Galan-Garcia, Lidice, Gholipour, Ali, Giedd, Jay, Gilmore, John H., Glahn, David C., Goodyer, Ian M., Grant, P.E., Groenewold, Nynke A., Gudapati, Shreya, Gunning, Faith M., Gur, Raquel E., Gur, Ruben C., Hammill, Christopher F., Hansson, Oskar, Hedden, Trey, Heinz, Andreas, Henson, Richard N., Heuer, Katja, Hoare, Jacqueline, Holla, Bharath, Holmes, Avram J., Huang, Hao, Ipser, Jonathan, Jack, Clifford R., Jr., Jackowski, Andrea P., Jia, Tianye, Jones, David T., Jones, Peter B., Kahn, Rene S., Karlsson, Hasse, Karlsson, Linnea, Kawashima, Ryuta, Kelley, Elizabeth A., Kern, Silke, Kim, Ki-Woong, Kitzbichler, Manfred G., Kremen, William S., Lalonde, François, Landeau, Brigitte, Lerch, Jason, Lewis, John D., Li, Jiao, Liao, Wei, Liston, Conor, Lombardo, Michael V., Lv, Jinglei, Mallard, Travis T., Marcelis, Machteld, Mathias, Samuel R., Mazoyer, Bernard, McGuire, Philip, Meaney, Michael J., Mechelli, Andrea, Misic, Bratislav, Morgan, Sarah E., Mothersill, David, Ortinau, Cynthia, Ossenkoppele, Rik, Ouyang, Minhui, Palaniyappan, Lena, Paly, Leo, Pan, Pedro M., Pantelis, Christos, Park, Min Tae M., Paus, Tomas, Pausova, Zdenka, Paz-Linares, Deirel, Binette, Alexa Pichet, Pierce, Karen, Qian, Xing, Qiu, Anqi, Raznahan, Armin, Rittman, Timothy, Rodrigue, Amanda, Rollins, Caitlin K., Romero-Garcia, Rafael, Ronan, Lisa, Rosenberg, Monica D., Rowitch, David H., Salum, Giovanni A., Satterthwaite, Theodore D., Schaare, H. Lina, Schabdach, Jenna, Schachar, Russell J., Schöll, Michael, Schultz, Aaron P., Seidlitz, Jakob, Sharp, David, Shinohara, Russell T., Skoog, Ingmar, Smyser, Christopher D., Sperling, Reisa A., Stein, Dan J., Stolicyn, Aleks, Suckling, John, Sullivan, Gemma, Thyreau, Benjamin, Toro, Roberto, Traut, Nicolas, Tsvetanov, Kamen A., Turk-Browne, Nicholas B., Tuulari, Jetro J., Tzourio, Christophe, Vachon-Presseau, Étienne, Valdes-Sosa, Mitchell J., Valdes-Sosa, Pedro A., Valk, Sofie L., van Amelsvoort, Therese, Vandekar, Simon N., Vasung, Lana, Vértes, Petra E., Victoria, Lindsay W., Villeneuve, Sylvia, Villringer, Arno, Vogel, Jacob W., Wagstyl, Konrad, Wang, Yin-Shan S., Warfield, Simon K., Warrier, Varun, Westman, Eric, Westwater, Margaret L., Whalley, Heather C., White, Simon R., Witte, A. Veronica, Yang, Ning, Yeo, B.T. Thomas, Yun, Hyuk Jin, Zalesky, Andrew, Zar, Heather J., Zettergren, Anna, Zhou, Juan H., Ziauddeen, Hisham, Zimmerman, Dabriel, Zugman, Andre, Zuo, Xi-Nian N., Ho, Natalie C.W., Nogovitsyn, Nikita, Metzak, Paul, Ballester, Pedro L., Hassel, Stefanie, Rotzinger, Susan, Poppenk, Jordan, Lam, Raymond W., Taylor, Valerie H., Milev, Roumen, Frey, Benicio N., Harkness, Kate L., Addington, Jean, Kennedy, Sidney H.
Publikováno v:
In Biological Psychiatry: Cognitive Neuroscience and Neuroimaging August 2024 9(8):786-799
Autor:
Laura E. Suárez, Agoston Mihalik, Filip Milisav, Kenji Marshall, Mingze Li, Petra E. Vértes, Guillaume Lajoie, Bratislav Misic
Publikováno v:
Nature Communications, Vol 15, Iss 1, Pp 1-14 (2024)
Abstract The connection patterns of neural circuits form a complex network. How signaling in these circuits manifests as complex cognition and adaptive behaviour remains the central question in neuroscience. Concomitant advances in connectomics and a
Externí odkaz:
https://doaj.org/article/018d25c031c64f659820273b26a0b3cf
Autor:
Filos, Angelos, Vértes, Eszter, Marinho, Zita, Farquhar, Gregory, Borsa, Diana, Friesen, Abram, Behbahani, Feryal, Schaul, Tom, Barreto, André, Osindero, Simon
Using a model of the environment and a value function, an agent can construct many estimates of a state's value, by unrolling the model for different lengths and bootstrapping with its value function. Our key insight is that one can treat this set of
Externí odkaz:
http://arxiv.org/abs/2112.04153
Autor:
Anand, Ankesh, Walker, Jacob, Li, Yazhe, Vértes, Eszter, Schrittwieser, Julian, Ozair, Sherjil, Weber, Théophane, Hamrick, Jessica B.
One of the key promises of model-based reinforcement learning is the ability to generalize using an internal model of the world to make predictions in novel environments and tasks. However, the generalization ability of model-based agents is not well
Externí odkaz:
http://arxiv.org/abs/2111.01587