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10/28/2022
Towards solving model bias in cosmic shear forward modeling
As the volume and quality of modern galaxy surveys increase, so does the...
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07/12/2022
Neural Posterior Estimation with Differentiable Simulators
Simulation-Based Inference (SBI) is a promising Bayesian inference frame...
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07/12/2022
Hybrid Physical-Neural ODEs for Fast N-body Simulations
We present a new scheme to compensate for the small-scales approximation...
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01/14/2022
Probabilistic Mass Mapping with Neural Score Estimation
Weak lensing mass-mapping is a useful tool to access the full distributi...
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02/10/2021
Real-Time Likelihood-free Inference of Roman Binary Microlensing Events with Amortized Neural Posterior Estimation
Fast and automated inference of binary-lens, single-source (2L1S) microl...
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11/16/2020
Denoising Score-Matching for Uncertainty Quantification in Inverse Problems
Deep neural networks have proven extremely efficient at solving a wide r...
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10/08/2020
Automating Inference of Binary Microlensing Events with Neural Density Estimation
Automated inference of binary microlensing events with traditional sampl...
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03/04/2020
Transformation Importance with Applications to Cosmology
Machine learning lies at the heart of new possibilities for scientific d...
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12/09/2019
Hybrid Physical-Deep Learning Model for Astronomical Inverse Problems
We present a Bayesian machine learning architecture that combines a phys...
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10/22/2019
Uncertainty Quantification with Generative Models
We develop a generative model-based approach to Bayesian inverse problem...
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09/19/2016