| 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 | 78 | 2017 |
| 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 | 38 | 2018 |
| 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 | 24 | 2015 |
| 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 | 23 | 2018 |
| 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 | 17 | 2018 |
| Mental state event definition generation E Kodra, R El Kaliouby, TJ Vandal US Patent App. 14/796,419, 2015 | 10 | 2015 |
| 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 | 7 | 2019 |
| 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 | 6 | 2019 |
| Mental state event signature usage R El Kaliouby, E Kodra, D Mcduff, TJ Vandal US Patent App. 15/262,197, 2016 | 6 | 2016 |
| Statistical Downscaling of Global Climate Models with Image Super-resolution and Uncertainty Quantification TJ Vandal Northeastern University, 2018 | 3 | 2018 |
| 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 | 3 | 2017 |
| 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 | 2 | 2018 |
| Uncertainty Quantification for Statistical Downscaling using Bayesian Deep Learning T Vandal, AR Ganguly 7th International Workshop on Climate Informatics, 2017 | 2 | 2017 |
| 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 | 1 | 2020 |
| 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 | 1 | 2019 |
| Temporal Interpolation of Geostationary Satellite Imagery with Task Specific Optical Flow T Vandal, R Nemani arXiv preprint arXiv:1907.12013, 2019 | 1 | 2019 |
| Optical Flow for Intermediate Frame Interpolation of Multispectral Geostationary Satellite Data T Vandal, RR Nemani Arxiv.(In review), 2019 | 1 | 2019 |
| Super-resolution and deep learning for climate downscaling T Vandal, AR Ganguly 98th American Meteorological Society Annual Meeting, 2018 | 1 | 2018 |
| 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 |
Ramakrishna NemaniNASA Ames Research CenterVerified email at nasa.gov
