6 citations · 12 across the 4 of their papers we have counts for
4 papers
Developing a Series of AI Challenges for the United States Department of the Air Force
Vijay Gadepally, Gregory Angelides, Andrei Barbu +39
Through a series of federal initiatives and orders, the U.S. Government has been making a concerted effort to ensure American leadership in AI. These broad strategy documents have…
Meta-Learning and Self-Supervised Pretraining for Real World Image Translation
Ileana Rugina, Rumen Dangovski, Mark Veillette +4
Recent advances in deep learning, in particular enabled by hardware advances and big data, have provided impressive results across a wide range of computational problems such as co…
PCE-PINNs: Physics-Informed Neural Networks for Uncertainty Propagation in Ocean Modeling
Björn Lütjens, Catherine H. Crawford, Mark Veillette +1
Climate models project an uncertainty range of possible warming scenarios from 1.5 to 5 degree Celsius global temperature increase until 2100, according to the CMIP6 model ensemble…
Compute, Time and Energy Characterization of Encoder-Decoder Networks with Automatic Mixed Precision Training
Siddharth Samsi, Michael Jones, Mark M. Veillette
Deep neural networks have shown great success in many diverse fields. The training of these networks can take significant amounts of time, compute and energy. As datasets get large…