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02/17/2022
Gradients without Backpropagation
Using backpropagation to compute gradients of objective functions for op...
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12/16/2021
Simultaneous Multivariate Forecast of Space Weather Indices using Deep Neural Network Ensembles
Solar radio flux along with geomagnetic indices are important indicators...
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12/06/2021
Simulation Intelligence: Towards a New Generation of Scientific Methods
The original "Seven Motifs" set forth a roadmap of essential methods for...
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10/06/2021
Detecting and Quantifying Malicious Activity with Simulation-based Inference
We propose the use of probabilistic programming techniques to tackle the...
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06/14/2021
KL Guided Domain Adaptation
Domain adaptation is an important problem and often needed for real-worl...
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12/23/2020
Towards Automated Satellite Conjunction Management with Bayesian Deep Learning
After decades of space travel, low Earth orbit is a junkyard of discarde...
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12/18/2020
Spacecraft Collision Risk Assessment with Probabilistic Programming
Over 34,000 objects bigger than 10 cm in length are known to orbit Earth...
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08/16/2020
AutoSimulate: (Quickly) Learning Synthetic Data Generation
Simulation is increasingly being used for generating large labelled data...
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05/14/2020
Simulation-Based Inference for Global Health Decisions
The COVID-19 pandemic has highlighted the importance of in-silico epidem...
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02/11/2020
Differentiating the Black-Box: Optimization with Local Generative Surrogates
We propose a novel method for gradient-based optimization of black-box s...
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11/29/2019
Transflow Learning: Repurposing Flow Models Without Retraining
It is well known that deep generative models have a rich latent space, a...
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11/04/2019
Single-Frame Super-Resolution of Solar Magnetograms: Investigating Physics-Based Metrics & Losses
Breakthroughs in our understanding of physical phenomena have traditiona...
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11/04/2019
Probabilistic Super-Resolution of Solar Magnetograms: Generating Many Explanations and Measuring Uncertainties
Machine learning techniques have been successfully applied to super-reso...
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10/25/2019
Attention for Inference Compilation
We present a new approach to automatic amortized inference in universal ...
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10/25/2019
Deep Probabilistic Surrogate Networks for Universal Simulator Approximation
We present a framework for automatically structuring and training fast, ...
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10/20/2019
Amortized Rejection Sampling in Universal Probabilistic Programming
Existing approaches to amortized inference in probabilistic programs wit...
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10/14/2019
Introducing an Explicit Symplectic Integration Scheme for Riemannian Manifold Hamiltonian Monte Carlo
We introduce a recent symplectic integration scheme derived for solving ...
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10/04/2019
Flood Detection On Low Cost Orbital Hardware
Satellite imaging is a critical technology for monitoring and responding...
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10/04/2019
Correlation of Auroral Dynamics and GNSS Scintillation with an Autoencoder
High energy particles originating from solar activity travel along the t...
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10/03/2019
Prediction of GNSS Phase Scintillations: A Machine Learning Approach
A Global Navigation Satellite System (GNSS) uses a constellation of sate...
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07/08/2019
Etalumis: Bringing Probabilistic Programming to Scientific Simulators at Scale
Probabilistic programming languages (PPLs) are receiving widespread atte...
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05/29/2019
Hijacking Malaria Simulators with Probabilistic Programming
Epidemiology simulations have become a fundamental tool in the fight aga...
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05/25/2019
An Ensemble of Bayesian Neural Networks for Exoplanetary Atmospheric Retrieval
Machine learning is now used in many areas of astrophysics, from detecti...
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05/17/2019