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09/20/2023
Flow Annealed Kalman Inversion for Gradient-Free Inference in Bayesian Inverse Problems
For many scientific inverse problems we are required to evaluate an expe...
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07/18/2023
Field-Level Inference with Microcanonical Langevin Monte Carlo
Field-level inference provides a means to optimally extract information ...
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06/07/2023
Multiscale Flow for Robust and Optimal Cosmological Analysis
We propose Multiscale Flow, a generative Normalizing Flow that creates s...
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03/31/2023
Microcanonical Langevin Monte Carlo
We propose a method for sampling from an arbitrary distribution exp[-S()...
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12/16/2022
Microcanonical Hamiltonian Monte Carlo
We develop Microcanonical Hamiltonian Monte Carlo (MCHMC), a class of mo...
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07/15/2022
A Probabilistic Autoencoder for Type Ia Supernovae Spectral Time Series
We construct a physically-parameterized probabilistic autoencoder (PAE) ...
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05/27/2022
Deterministic Langevin Monte Carlo with Normalizing Flows for Bayesian Inference
We propose a general purpose Bayesian inference algorithm for expensive ...
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02/10/2022
Translation and Rotation Equivariant Normalizing Flow (TRENF) for Optimal Cosmological Analysis
Our universe is homogeneous and isotropic, and its perturbations obey tr...
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12/17/2021
MUSE: Marginal Unbiased Score Expansion and Application to CMB Lensing
We present the marginal unbiased score expansion (MUSE) method, an algor...
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08/13/2021
Self-Calibrating the Look-Elsewhere Effect: Fast Evaluation of the Statistical Significance Using Peak Heights
In experiments where one searches a large parameter space for an anomaly...
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12/21/2020
Unsupervised in-distribution anomaly detection of new physics through conditional density estimation
Anomaly detection is a key application of machine learning, but is gener...
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10/06/2020
Learning effective physical laws for generating cosmological hydrodynamics with Lagrangian Deep Learning
The goal of generative models is to learn the intricate relations betwee...
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07/27/2020
The look-elsewhere effect from a unified Bayesian and frequentist perspective
When searching over a large parameter space for anomalies such as events...
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07/01/2020
Sliced Iterative Generator
We introduce the Sliced Iterative Generator (SIG), an iterative generati...
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06/09/2020
Probabilistic Auto-Encoder
We introduce the Probabilistic Auto-Encoder (PAE), a generative model wi...
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12/12/2019
Normalizing Constant Estimation with Gaussianized Bridge Sampling
Normalizing constant (also called partition function, Bayesian evidence,...
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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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10/16/2019
Generative Learning of Counterfactual for Synthetic Control Applications in Econometrics
A common statistical problem in econometrics is to estimate the impact o...
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01/14/2019