Search Results for author:
Found 22 papers, 10 papers with code
Gravitationally Lensed Black Hole Emission Tomography
In this work, we propose BH-NeRF, a novel tomography approach that leverages gravitational lensing to recover the continuous 3D emission field near a black hole.
alpha-Deep Probabilistic Inference (alpha-DPI): efficient uncertainty quantification from exoplanet astrometry to black hole feature extraction
Inferring the posterior of hidden features, conditioned on the observed measurements, is essential for understanding the uncertainty of results and downstream scientific interpretations.
Unsupervised learning of MRI tissue properties using MRI physics models
In this work we propose an unsupervised deep-learning strategy that employs MRI physics to estimate all three tissue properties from a single multiecho MRI scan session, and generalizes across varying acquisition parameters.
End-to-End Sequential Sampling and Reconstruction for MR Imaging
In this paper, we leverage the sequential nature of MRI measurements, and propose a fully differentiable framework that jointly learns a sequential sampling policy simultaneously with a reconstruction strategy.
Measurement-Robust Control Barrier Functions: Certainty in Safety with Uncertainty in State
The increasing complexity of modern robotic systems and the environments they operate in necessitates the formal consideration of safety in the presence of imperfect measurements.
Visual Vibration Tomography: Estimating Interior Material Properties from Monocular Video
We propose an approach that estimates heterogeneous material properties of an object from a monocular video of its surface vibrations.
Inference of Black Hole Fluid-Dynamics From Sparse Interferometric Measurements
We are motivated by the task of imaging the stochastically evolving environment surrounding black holes, and demonstrate how flow parameters can be estimated from sparse interferometric measurements used in radio astronomical imaging.
Deep Probabilistic Imaging: Uncertainty Quantification and Multi-modal Solution Characterization for Computational Imaging
In this paper, we propose a variational deep probabilistic imaging approach to quantify reconstruction uncertainty.
Learning a Probabilistic Strategy for Computational Imaging Sensor Selection
In this paper, we demonstrate the approach in the context of a very-long-baseline-interferometry (VLBI) array design task, where sensor correlations and atmospheric noise present unique challenges.
Medical Image Imputation from Image Collections
We present an algorithm for creating high resolution anatomically plausible images consistent with acquired clinical brain MRI scans with large inter-slice spacing.
Visual Dynamics: Stochastic Future Generation via Layered Cross Convolutional Networks
We study the problem of synthesizing a number of likely future frames from a single input image.
Interferometric Imaging Directly with Closure Phases and Closure Amplitudes
Closure-only imaging provides results that are as non-committal as possible and allows for reconstructing an image independently from separate amplitude and phase self-calibration.
Instrumentation and Methods for Astrophysics High Energy Astrophysical Phenomena
Reconstructing Video from Interferometric Measurements of Time-Varying Sources
Most recently, the Event Horizon Telescope (EHT) has extended VLBI to short millimeter wavelengths with a goal of achieving angular resolution sufficient for imaging the event horizons of nearby supermassive black holes.
Dynamical Imaging with Interferometry
By linking widely separated radio dishes, the technique of very long baseline interferometry (VLBI) can greatly enhance angular resolution in radio astronomy.
Instrumentation and Methods for Astrophysics
Turning Corners Into Cameras: Principles and Methods
We show that walls and other obstructions with edges can be exploited as naturally-occurring "cameras" that reveal the hidden scenes beyond them.
Visual Vibrometry: Estimating MaterialProperties from Small Motions in Video
The estimation of material properties is important for scene understanding, with many applications in vision, robotics, andstructural engineering.
Visual Vibrometry: Estimating Material Properties from Small Motions in Video
The estimation of material properties is important for scene understanding, with many applications in vision, robotics, and structural engineering.
Multi-resolution Data Fusion for Super-Resolution Electron Microscopy
Consequently, there is an enormous demand in the materials and biological sciences to image at greater speed and lower dosage, while maintaining resolution.
Visual Dynamics: Probabilistic Future Frame Synthesis via Cross Convolutional Networks
We study the problem of synthesizing a number of likely future frames from a single input image.
High Resolution Linear Polarimetric Imaging for the Event Horizon Telescope
Polarimetric MEM is thus an attractive choice for image reconstruction with the
Instrumentation and Methods for Astrophysics Astrophysics of Galaxies
Computational Imaging for VLBI Image Reconstruction
Very long baseline interferometry (VLBI) is a technique for imaging celestial radio emissions by simultaneously observing a source from telescopes distributed across Earth.
Visual Vibrometry: Estimating Material Properties From Small Motion in Video
The estimation of material properties is important for scene understanding, with many applications in vision, robotics, and structural engineering.
