Thomas Vandal
Thomas Vandal
Research Scientist, NASA Ames Research Center
Verified email at nasa.gov - Homepage
Title
Cited by
Cited by
Year
DeepSD: Generating High Resolution Climate Change Projections through Single Image Super-Resolution
T Vandal, E Kodra, S Ganguly, A Michaelis, R Nemani, AR Ganguly
23rd ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2017
782017
Intercomparison of Machine Learning Methods for Statistical Downscaling: The Case of Daily and Extreme Precipitation
T Vandal, E Kodra, AR Ganguly
Theoretical and Applied Climatology, 1-14, 2018
382018
Event detection: Ultra large-scale clustering of facial expressions
T Vandal, D McDuff, R El Kaliouby
2015 11th IEEE International Conference and Workshops on Automatic Face and …, 2015
242015
Quantifying Uncertainty in Discrete-Continuous and Skewed Data with Bayesian Deep Learning
T Vandal, E Kodra, J Dy, S Ganguly, R Nemani, AR Ganguly
24rd ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2018
232018
Generating high resolution climate change projections through single image super-resolution: An abridged version
T Vandal, E Kodra, S Ganguly, A Michaelis, R Nemani, AR Ganguly
International Joint Conferences on Artificial Intelligence Organization, 2018
172018
Mental state event definition generation
E Kodra, R El Kaliouby, TJ Vandal
US Patent App. 14/796,419, 2015
102015
First provisional land surface reflectance product from geostationary satellite Himawari-8 AHI
S Li, W Wang, H Hashimoto, J Xiong, T Vandal, J Yao, L Qian, K Ichii, ...
Remote Sensing 11 (24), 2990, 2019
72019
Quantum-assisted associative adversarial network: Applying quantum annealing in deep learning
M Wilson, T Vandal, T Hogg, E Rieffel
arXiv preprint arXiv:1904.10573, 2019
62019
Mental state event signature usage
R El Kaliouby, E Kodra, D Mcduff, TJ Vandal
US Patent App. 15/262,197, 2016
62016
Statistical Downscaling of Global Climate Models with Image Super-resolution and Uncertainty Quantification
TJ Vandal
Northeastern University, 2018
32018
Statistical Downscaling in Climate with State-of-the-Art Scalable Machine Learning
T Vandal, U Bhatia, AR Ganguly
Large-Scale Machine Learning in the Earth Sciences, Chapman and Hall/CRC, 55-72, 2017
32017
Prediction and uncertainty quantification of daily airport flight delays
T Vandal, M Livingston, C Piho, S Zimmerman
International Conference on Predictive Applications and APIs, 45-51, 2018
22018
Uncertainty Quantification for Statistical Downscaling using Bayesian Deep Learning
T Vandal, AR Ganguly
7th International Workshop on Climate Informatics, 2017
22017
High-Dimensional Similarity Search with Quantum-Assisted Variational Autoencoder
N Gao, M Wilson, T Vandal, W Vinci, R Nemani, E Rieffel
Proceedings of the 26th ACM SIGKDD International Conference on Knowledge …, 2020
12020
Deep Learning Emulation of Multi-Angle Implementation of Atmospheric Correction (MAIAC)
K Duffy, T Vandal, W Wang, R Nemani, AR Ganguly
arXiv preprint arXiv:1910.13408, 2019
12019
Temporal Interpolation of Geostationary Satellite Imagery with Task Specific Optical Flow
T Vandal, R Nemani
arXiv preprint arXiv:1907.12013, 2019
12019
Optical Flow for Intermediate Frame Interpolation of Multispectral Geostationary Satellite Data
T Vandal, RR Nemani
Arxiv.(In review), 2019
12019
Super-resolution and deep learning for climate downscaling
T Vandal, AR Ganguly
98th American Meteorological Society Annual Meeting, 2018
12018
Spectral Synthesis for Satellite-to-Satellite Translation
T Vandal, D McDuff, W Wang, A Michaelis, R Nemani
arXiv preprint arXiv:2010.06045, 2020
2020
Data Science for Weather Impacts on Crop Yield
VS Konduri, TJ Vandal, S Ganguly, AR Ganguly
Frontiers in Sustainable Food Systems 4, 52, 2020
2020
The system can't perform the operation now. Try again later.
Articles 1–20