Zobrazeno 1 - 7
of 7
pro vyhledávání: '"Samsi, Sid"'
Autor:
Samuel, Kaira, Kepner, Jeremy, Jones, Michael, Milechin, Lauren, Gadepally, Vijay, Arcand, William, Bestor, David, Bergeron, William, Byun, Chansup, Hubbell, Matthew, Houle, Michael, Klein, Anna, Lopez, Victor, Mullen, Julie, Prout, Andrew, Reuther, Albert, Rosa, Antonio, Samsi, Sid, Yee, Charles, Michaleas, Peter
First responders and other forward deployed essential workers can benefit from advanced analytics. Limited network access and software security requirements prevent the usage of standard cloud based microservice analytic platforms that are typically
Externí odkaz:
http://arxiv.org/abs/2108.11525
Autor:
Samuel, Kaira, Gadepally, Vijay, Jacobs, David, Jones, Michael, McAlpin, Kyle, Palko, Kyle, Paulk, Ben, Samsi, Sid, Siu, Ho Chit, Yee, Charles, Kepner, Jeremy
AI algorithms that identify maneuvers from trajectory data could play an important role in improving flight safety and pilot training. AI challenges allow diverse teams to work together to solve hard problems and are an effective tool for developing
Externí odkaz:
http://arxiv.org/abs/2108.11503
Autor:
Kepner, Jeremy, Kipf, Andreas, Engwirda, Darren, Vembar, Navin, Jones, Michael, Milechin, Lauren, Gadepally, Vijay, Hill, Chris, Kraska, Tim, Arcand, William, Bestor, David, Bergeron, William, Byun, Chansup, Hubbell, Matthew, Houle, Michael, Kirby, Andrew, Klein, Anna, Mullen, Julie, Prout, Andrew, Reuther, Albert, Rosa, Antonio, Samsi, Sid, Yee, Charles, Michaleas, Peter
Pandemic measures such as social distancing and contact tracing can be enhanced by rapidly integrating dynamic location data and demographic data. Projecting billions of longitude and latitude locations onto hundreds of thousands of highly irregular
Externí odkaz:
http://arxiv.org/abs/2005.03156
Autor:
Kepner, Jeremy, Alford, Simon, Gadepally, Vijay, Jones, Michael, Milechin, Lauren, Reuther, Albert, Robinett, Ryan, Samsi, Sid
The MIT/IEEE/Amazon GraphChallenge.org encourages community approaches to developing new solutions for analyzing graphs and sparse data. Sparse AI analytics present unique scalability difficulties. The Sparse Deep Neural Network (DNN) Challenge draws
Externí odkaz:
http://arxiv.org/abs/2004.01181
Autor:
Kepner, Jeremy, Alford, Simon, Gadepally, Vijay, Jones, Michael, Milechin, Lauren, Robinett, Ryan, Samsi, Sid
The MIT/IEEE/Amazon GraphChallenge.org encourages community approaches to developing new solutions for analyzing graphs and sparse data. Sparse AI analytics present unique scalability difficulties. The proposed Sparse Deep Neural Network (DNN) Challe
Externí odkaz:
http://arxiv.org/abs/1909.05631
Deep neural networks (DNNs) have emerged as key enablers of machine learning. Applying larger DNNs to more diverse applications is an important challenge. The computations performed during DNN training and inference are dominated by operations on the
Externí odkaz:
http://arxiv.org/abs/1807.03165
Autor:
Samsi, Siddharth Sadanand
The use of computers in medical image analysis has seen tremendous growth following the development of imaging technologies that can capture image data in-vivo as well as ex-vivo. While the field of radiology has adopted computer aided image analysis
Externí odkaz:
http://rave.ohiolink.edu/etdc/view?acc_num=osu1333560691