3D Conditional Generative Adversarial Networks to enable large-scale seismic image enhancement

no code implementations • 16 Nov 2019 • Praneet Dutta, Bruce Power, Adam Halpert, Carlos Ezequiel, Aravind Subramanian, Chanchal Chatterjee, Sindhu Hari, Kenton Prindle, Vishal Vaddina, Andrew Leach, Raj Domala, Laura Bandura, Massimo Mascaro

We propose GAN-based image enhancement models for frequency enhancement of 2D and 3D seismic images.

Denoising Image Enhancement +1

AutoML for Contextual Bandits

no code implementations • 7 Sep 2019 • Praneet Dutta, Joe Cheuk, Jonathan S Kim, Massimo Mascaro

We see that our model is able to perform much better than random exploration, being more regret efficient and able to converge with a limited number of samples, while remaining very general and easy to use due to the meta-learning approach.

AutoML Feature Engineering +4

Bayesian Deep Learning for Exoplanet Atmospheric Retrieval

no code implementations • 8 Nov 2018 • Frank Soboczenski, Michael D. Himes, Molly D. O'Beirne, Simone Zorzan, Atilim Gunes Baydin, Adam D. Cobb, Yarin Gal, Daniel Angerhausen, Massimo Mascaro, Giada N. Arney, Shawn D. Domagal-Goldman

Here we present an ML-based retrieval framework called Intelligent exoplaNet Atmospheric RetrievAl (INARA) that consists of a Bayesian deep learning model for retrieval and a data set of 3, 000, 000 synthetic rocky exoplanetary spectra generated using the NASA Planetary Spectrum Generator.

Retrieval