20 citations · 66 across the 9 of their papers we have counts for
13 papers
Gradients without Backpropagation
Atılım Güneş Baydin, Barak A. Pearlmutter, Don Syme +2
Using backpropagation to compute gradients of objective functions for optimization has remained a mainstay of machine learning. Backpropagation, or reverse-mode differentiation, is…
Detecting and Quantifying Malicious Activity with Simulation-based Inference
Andrew Gambardella, Bogdan State, Naeemullah Khan +3
We propose the use of probabilistic programming techniques to tackle the malicious user identification problem in a recommendation algorithm. Probabilistic programming provides num…
Multi-Channel Auto-Calibration for the Atmospheric Imaging Assembly using Machine Learning
Luiz F. G. dos Santos, Souvik Bose, Valentina Salvatelli +7
Solar activity plays a quintessential role in influencing the interplanetary medium and space-weather around the Earth. Remote sensing instruments onboard heliophysics space missio…
Towards Automated Satellite Conjunction Management with Bayesian Deep Learning
Francesco Pinto, Giacomo Acciarini, Sascha Metz +7
After decades of space travel, low Earth orbit is a junkyard of discarded rocket bodies, dead satellites, and millions of pieces of debris from collisions and explosions. Objects i…
Spacecraft Collision Risk Assessment with Probabilistic Programming
Giacomo Acciarini, Francesco Pinto, Sascha Metz +7
Over 34,000 objects bigger than 10 cm in length are known to orbit Earth. Among them, only a small percentage are active satellites, while the rest of the population is made of dea…
AutoSimulate: (Quickly) Learning Synthetic Data Generation
Harkirat Singh Behl, Atılım Güneş Baydin, Ran Gal +2
Simulation is increasingly being used for generating large labelled datasets in many machine learning problems. Recent methods have focused on adjusting simulator parameters with t…