activity
20172020
most citedDeepSD: Generating High Resolution Climate Change Projections through Single Image Super-Resolution

38 citations · 38 across the 2 of their papers we have counts for

collaborators

5 papers

cs.CV2020

Spectral Synthesis for Satellite-to-Satellite Translation

Thomas Vandal, Daniel McDuff, Weile Wang +2

Earth observing satellites carrying multi-spectral sensors are widely used to monitor the physical and biological states of the atmosphere, land, and oceans. These satellites have…

cs.CV2019

Temporal Interpolation of Geostationary Satellite Imagery with Task Specific Optical Flow

Thomas Vandal, Ramakrishna Nemani

Applications of satellite data in areas such as weather tracking and modeling, ecosystem monitoring, wildfire detection, and land-cover change are heavily dependent on the trade-of…

cs.LG2018

Quantifying Uncertainty in Discrete-Continuous and Skewed Data with Bayesian Deep Learning

Thomas Vandal, Evan Kodra, Jennifer Dy +3

Deep Learning (DL) methods have been transforming computer vision with innovative adaptations to other domains including climate change. For DL to pervade Science and Engineering (…

cs.CV201738 cited

DeepSD: Generating High Resolution Climate Change Projections through Single Image Super-Resolution

Thomas Vandal, Evan Kodra, Sangram Ganguly +3

The impacts of climate change are felt by most critical systems, such as infrastructure, ecological systems, and power-plants. However, contemporary Earth System Models (ESM) are r…

stat.ML2017

Intercomparison of Machine Learning Methods for Statistical Downscaling: The Case of Daily and Extreme Precipitation

Thomas Vandal, Evan Kodra, Auroop R Ganguly

Statistical downscaling of global climate models (GCMs) allows researchers to study local climate change effects decades into the future. A wide range of statistical models have be…