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07/05/2023
Privacy Amplification via Importance Sampling
We examine the privacy-enhancing properties of subsampling a data set vi...
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06/30/2023
Risk-sensitive Actor-free Policy via Convex Optimization
Traditional reinforcement learning methods optimize agents without consi...
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05/25/2023
Neural incomplete factorization: learning preconditioners for the conjugate gradient method
In this paper, we develop a novel data-driven approach to accelerate sol...
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04/17/2023
Refusion: Enabling Large-Size Realistic Image Restoration with Latent-Space Diffusion Models
This work aims to improve the applicability of diffusion models in reali...
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01/31/2023
Archetypal Analysis++: Rethinking the Initialization Strategy
Archetypal analysis is a matrix factorization method with convexity cons...
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01/27/2023
Image Restoration with Mean-Reverting Stochastic Differential Equations
This paper presents a stochastic differential equation (SDE) approach fo...
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01/03/2023
A Tutorial on Parametric Variational Inference
Variational inference uses optimization, rather than integration, to app...
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05/12/2022
Probabilistic Estimation of Chirp Instantaneous Frequency Using Gaussian Processes
We present a probabilistic approach for estimating chirp signal and its ...
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03/03/2022
NUQ: A Noise Metric for Diffusion MRI via Uncertainty Discrepancy Quantification
Diffusion MRI (dMRI) is the only non-invasive technique sensitive to tis...
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02/01/2022
Graph-based Neural Acceleration for Nonnegative Matrix Factorization
We describe a graph-based neural acceleration technique for nonnegative ...
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03/01/2021
Latent linear dynamics in spatiotemporal medical data
Spatiotemporal imaging is common in medical imaging, with applications i...
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04/10/2020
Decentralized Differentially Private Segmentation with PATE
When it comes to preserving privacy in medical machine learning, two imp...
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03/24/2020
Registration by tracking for sequential 2D MRI
Our anatomy is in constant motion. With modern MR imaging it is possible...
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03/13/2020
The Elliptical Processes: a New Family of Flexible Stochastic Processes
We present the elliptical processes-a new family of stochastic processes...
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08/19/2019
A unified representation network for segmentation with missing modalities
Over the last few years machine learning has demonstrated groundbreaking...
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11/16/2017
Bayesian uncertainty quantification in linear models for diffusion MRI
Diffusion MRI (dMRI) is a valuable tool in the assessment of tissue micr...
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11/09/2016