Thomas Vandal
Thomas Vandal
Research Scientist, NASA Ames Research Center
Verified email at baeri.org - Homepage
TitleCited byYear
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
402017
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
222015
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
142018
Mental state event definition generation
E Kodra, R El Kaliouby, TJ Vandal
US Patent App. 14/796,419, 2015
122015
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
102018
Generating High Resolution Climate Change Projections through Single Image Super-Resolution: An Abridged Version.
T Vandal, E Kodra, S Ganguly, AR Michaelis, RR Nemani, AR Ganguly
IJCAI, 5389-5393, 2018
62018
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
32019
Mental state event signature usage
R El Kaliouby, E Kodra, D McDuff, TJ Vandal
US Patent App. 15/262,197, 2016
32016
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, 55-72, 2017
22017
Uncertainty Quantification for Statistical Downscaling using Bayesian Deep Learning
T Vandal, AR Ganguly
7th International Workshop on Climate Informatics, 2017
12017
Surface Reflectance Product from Geostationary Satellite
S Li, W Wang, H Hashimoto, T Vandal, J Yao, RR Nemani
AGU Fall Meeting 2019, 2019
2019
Deep Learning Emulation of Atmospheric Correction for Geostationary Sensors
K Duffy, T Vandal, S Li, RR Nemani, AR Ganguly
AGU Fall Meeting 2019, 2019
2019
Transfer Learning to Generate True Color Images from GOES-16
T Vandal, S Li, W Wang, R Nemani
2019
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
2019
Optical Flow for Intermediate Frame Interpolation of Multispectral Geostationary Satellite Data
T Vandal, R Nemani
arXiv preprint arXiv:1907.12013, 2019
2019
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
2019
DeepEmSat: Deep Emulation for Satellite Data Mining
KM Duffy, T Vandal, S Li, S Ganguly, R Nemani, AR Ganguly
Frontiers in Big Data 2, 42, 2019
2019
Image Super-Resolution and Uncertainty Quantification for Earth Science Data on the NASA Earth Exchange AI Platform
T Vandal, S Ganguly, E Kodra, J Dy, A Michaelis, RR Nemani, ...
AGU Fall Meeting Abstracts, 2018
2018
GEONEX: A Deep Learning Approach to Prediction of Surface Spectral Reflectance
K Duffy, S Ganguly, ED Collier, S Kalia, S Li, GE Madanguit, M Mage, ...
AGU Fall Meeting Abstracts, 2018
2018
NEX-AI: A Cloud and HPC Agnostic Framework for Scaling Deep Learning and Machine Learning Applications for Earth Science
S Ganguly, S Kalia, K Duffy, ED Collier, GE Madanguit, G Shreekant, S Li, ...
AGU Fall Meeting Abstracts, 2018
2018
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