Zobrazeno 1 - 10
of 7 628
pro vyhledávání: '"A. Feigenbaum"'
Autor:
Feigenbaum, Itai, Arpit, Devansh, Wang, Huan, Heinecke, Shelby, Niebles, Juan Carlos, Yao, Weiran, Xiong, Caiming, Savarese, Silvio
Causal discovery aims to recover information about an unobserved causal graph from the observable data it generates. Layerings are orderings of the variables which place causes before effects. In this paper, we provide ways to recover layerings of a
Externí odkaz:
http://arxiv.org/abs/2401.10495
Autor:
Feigenbaum, Itai, Wang, Huan, Heinecke, Shelby, Niebles, Juan Carlos, Yao, Weiran, Xiong, Caiming, Arpit, Devansh
Causal discovery aims to recover a causal graph from data generated by it; constraint based methods do so by searching for a d-separating conditioning set of nodes in the graph via an oracle. In this paper, we provide analytic evidence that on large
Externí odkaz:
http://arxiv.org/abs/2303.05628
Autor:
Arpit, Devansh, Fernandez, Matthew, Feigenbaum, Itai, Yao, Weiran, Liu, Chenghao, Yang, Wenzhuo, Josel, Paul, Heinecke, Shelby, Hu, Eric, Wang, Huan, Hoi, Stephen, Xiong, Caiming, Zhang, Kun, Niebles, Juan Carlos
We introduce the Salesforce CausalAI Library, an open-source library for causal analysis using observational data. It supports causal discovery and causal inference for tabular and time series data, of discrete, continuous and heterogeneous types. Th
Externí odkaz:
http://arxiv.org/abs/2301.10859
Autor:
Lahnakoski, Juha M., Nolte, Tobias, Solway, Alec, Vilares, Iris, Hula, Andreas, Feigenbaum, Janet, Lohrenz, Terry, King-Casas, Brooks, Fonagy, Peter, Montague, P. Read, Schilbach, Leonhard
Publikováno v:
In Journal of Affective Disorders 1 September 2024 360:345-353
Autor:
Malchik, Caleb, Feigenbaum, Joan
Internet companies derive value from users by recording and influencing their behavior. Users can pressure companies to refrain from certain invasive and manipulative practices by selectively withdrawing their attention, an exercise of data leverage
Externí odkaz:
http://arxiv.org/abs/2201.10677
Autor:
Judson, Samuel, Feigenbaum, Joan
Insightful interdisciplinary collaboration is essential to the principled governance of complex technologies, like those produced by modern computing research and development. Technical research on the interaction between computation and society ofte
Externí odkaz:
http://arxiv.org/abs/2201.07413
Autor:
Schwarzer, Nicola-Hans, Nolte, Tobias, Fonagy, Peter, Feigenbaum, Janet, King-Casas, Brooks, Rüfenacht, Eva, Gingelmaier, Stephan, Leibowitz, Judy, Pilling, Steve, Read Montague, P.
Publikováno v:
In Children and Youth Services Review August 2024 163
Autor:
Mancinelli, Federico, Nolte, Tobias, Griem, Julia, Lohrenz, Terry, Feigenbaum, Janet, King-Casas, Brooks, Montague, P. Read, Fonagy, Peter, Mathys, Christoph
Publikováno v:
In Journal of Psychiatric Research July 2024 175:470-478
Autor:
Feigenbaum, Frank, Parks, Susan E., Martin, Madelene P., Ross, Tanishu D., Kupanoff, Kristina M.
Publikováno v:
In World Neurosurgery July 2024 187:e189-e198
Autor:
Ghanem, Ghadi, Tsai, Hsin Hsiang Clarence, Durant, Catherine, Feigenbaum, Gary S., Glaeser, Alexandra Milin
Publikováno v:
In Transfusion and Apheresis Science June 2024 63(3)