A multidisciplinary team of researchers from Virginia Polytechnic Institute and State University (Virginia Tech) and Oak Ridge National Laboratory (ORNL) propose a deep learning-based intrusion detection framework, CANShield, to detect advanced
We present a rigorous mathematical analysis of the isolation random forest algorithm for outlier detection.
A multidisciplinary team of researchers from Oak Ridge National Laboratory (ORNL) propose a forensic framework to decide if recorded controller area network (CAN) traffic, a de facto automobile communication standard, contains masquerade attacks.
A web-based GUI for INTERSECT has been created which allows a user to configure an experiment on an electron microscope, setting such parameters as maximum number of steps for the machine learning algorithm to perform.
Researchers at Oak Ridge National Laboratory developed a new parallel performance portable algorithm for solving the Euclidean minimum spanning tree problem (EMST), capable of processing tens of millions of data points a second.
Researchers at the Department of Energy’s Oak Ridge National Laboratory and their technologies have received seven 2022 R&D 100 Awards, plus special recognition for a battery-related green technology product.
After nearly seven years of intense development, the URBAN-NET infrastructure quantification tool is being made available to users.
A graph convolutional neural network (GCNN) was trained with millions of molecules to accurately predict molecular photo-optical properties by scaling data loading and training to over 1,500 GPUs on the Summit and Perlmutter supercomputers at the OLCF a
The Department of Energy’s Office of Science has selected three Oak Ridge National Laboratory scientists for Early Career Research Program awards.
Oak Ridge National Laboratory researchers developed an invertible neural network (INN) to effectively and efficiently solve earth-system model calibration and simulation problems.