Zobrazeno 1 - 10
of 53
pro vyhledávání: '"Theodore L Willke"'
Autor:
Manoj Kumar, Cameron T Ellis, Qihong Lu, Hejia Zhang, Mihai Capotă, Theodore L Willke, Peter J Ramadge, Nicholas B Turk-Browne, Kenneth A Norman
Publikováno v:
PLoS Computational Biology, Vol 16, Iss 1, p e1007549 (2020)
Advanced brain imaging analysis methods, including multivariate pattern analysis (MVPA), functional connectivity, and functional alignment, have become powerful tools in cognitive neuroscience over the past decade. These tools are implemented in cust
Externí odkaz:
https://doaj.org/article/580abb344f644e9d8b68cf318019b4a4
Autor:
Yao Xiao, Guixiang Ma, Nesreen K. Ahmed, Mihai Capotă, Theodore L. Willke, Shahin Nazarian, Paul Bogdan
Publikováno v:
Communications Engineering, Vol 2, Iss 1, Pp 1-15 (2023)
Abstract Recent technological advances have contributed to the rapid increase in algorithmic complexity of applications, ranging from signal processing to autonomous systems. To control this complexity and endow heterogeneous computing systems with a
Externí odkaz:
https://doaj.org/article/dce5624382d842e2b61228caa8395f1b
Autor:
Hoda Eldardiry, Xiangnan Kong, Ryan A. Rossi, Rong Zhou, Theodore L. Willke, Nesreen K. Ahmed, John Boaz Lee
Publikováno v:
IEEE Transactions on Knowledge and Data Engineering. 34:2401-2415
Random walks are at the heart of many existing node embedding and network representation learning methods. However, such methods have many limitations that arise from the use of traditional random walks, e.g., the embeddings resulting from these meth
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::2cea6374e97b91542f242ef4ed5910b0
https://doi.org/10.1109/tkde.2020.3006475
https://doi.org/10.1109/tkde.2020.3006475
Autor:
Manoj Kumar, null Michael Anderson, James Antony, Christopher Baldassano, Paula Pacheco Brooks, Ming Bo Cai, Po-Hsuan Cameron Chen, Cameron Thomas Ellis, Gregory Henselman-Petrusek, David Huberdeau, J. Benjamin Hutchinson, Y. Peeta Li, Qihong Lu, Jeremy R. Manning, Anne C. Mennen, Samuel A. Nastase, Hugo Richard, Anna C. Schapiro, Nicolas W Schuck, Michael Shvartsman, Narayanan Sundaram, Daniel Suo, Javier S. Turek, David Turner, Vy Vo, Grant Wallace, Yida Wang, Jamal A. Williams, Hejia Zhang, Xia Zhu, Mihai Capota, Jonathan D. Cohen, Uri Hasson, Kai Li, Peter J. Ramadge, Nicholas Turk-Browne, Theodore L. Willke, Kenneth A. Norman
Publikováno v:
Aperture Neuro
Functional magnetic resonance imaging (fMRI) offers a rich source of data for studying the neural basis of cognition. Here, we describe the Brain Imaging Analysis Kit (BrainIAK), an open-source, free Python package that provides computationally optim
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::924227a8444ec4fa72f357e0287906b4
https://pubmed.ncbi.nlm.nih.gov/35939268
https://pubmed.ncbi.nlm.nih.gov/35939268
Autor:
Guixiang Ma, Yao Xiao, Mihai Capota, Theodore L. Willke, Shahin Nazarian, Paul Bogdan, Nesreen K. Ahmed
Publikováno v:
2021 IEEE International Conference on Big Data (Big Data).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::7d8be70eba7c863ceed834b768fbd55d
https://doi.org/10.1109/bigdata52589.2021.9671685
https://doi.org/10.1109/bigdata52589.2021.9671685
Autor:
Nicholas B. Turk-Browne, Kenneth A. Norman, Cameron T. Ellis, Mihai Capota, Qihong Lu, Peter J. Ramadge, Manoj Kumar, Theodore L. Willke, Hejia Zhang
Publikováno v:
PLoS Computational Biology
PLoS Computational Biology, Vol 16, Iss 1, p e1007549 (2020)
PLoS Computational Biology, Vol 16, Iss 1, p e1007549 (2020)
Advanced brain imaging analysis methods, including multivariate pattern analysis (MVPA), functional connectivity, and functional alignment, have become powerful tools in cognitive neuroscience over the past decade. These tools are implemented in cust
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::1657860a5554211ad586f4f7580e0632
http://europepmc.org/articles/PMC6961866
http://europepmc.org/articles/PMC6961866
Publikováno v:
Proceedings of the VLDB Endowment. 10:1430-1441
We propose Graph Priority Sampling ( gps ), a new paradigm for order-based reservoir sampling from massive graph streams. gps provides a general way to weight edge sampling according to auxiliary and/or size variables so as to accomplish various esti
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::6bd080d6db0e1236ded624a1f694d343
https://doi.org/10.14778/3137628.3137651
https://doi.org/10.14778/3137628.3137651
Autor:
Shaden Smith, Theodore L. Willke, Zheguang Zhao, Subramanya R. Dulloor, Narayanan Sundaram, Mihai Capota, Michael R. Anderson, Nadathur Satish
Publikováno v:
Proceedings of the VLDB Endowment. 10:901-912
Apache Spark is a popular framework for data analytics with attractive features such as fault tolerance and interoperability with the Hadoop ecosystem. Unfortunately, many analytics operations in Spark are an order of magnitude or more slower compare
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::3109cf0a1de3d577a25509af94b04510
https://doi.org/10.14778/3090163.3090168
https://doi.org/10.14778/3090163.3090168
In many domains where data are represented as graphs, learning a similarity metric among graphs is considered a key problem, which can further facilitate various learning tasks, such as classification, clustering, and similarity search. Recently, the
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::fde75e5c84e7b53813fcb941a100e7eb
http://arxiv.org/abs/1912.11615
http://arxiv.org/abs/1912.11615
Autor:
Dipanjan Sengupta, Michael W. Cole, Nesreen K. Ahmed, Theodore L. Willke, Guixiang Ma, Nicholas B. Turk-Browne, Philip S. Yu
Publikováno v:
CIKM
We propose an end-to-end graph similarity learning framework called Higher-order Siamese GCN for multi-subject fMRI data analysis. The proposed framework learns the brain network representations via a supervised metric-based approach with siamese neu
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::206b177df85d0aedf5e8017723c362be
https://doi.org/10.1145/3357384.3357815
https://doi.org/10.1145/3357384.3357815