research
∙
05/28/2023
StEik: Stabilizing the Optimization of Neural Signed Distance Functions and Finer Shape Representation
We present new insights and a novel paradigm (StEik) for learning implic...
share
research
∙
06/04/2022
Surprising Instabilities in Training Deep Networks and a Theoretical Analysis
We discover restrained numerical instabilities in current training pract...
research
∙
12/12/2021
Image Reconstruction from Events. Why learn it?
Traditional cameras measure image intensity. Event cameras, by contrast,...
research
∙
06/07/2021
Deep Learning 3D Dose Prediction for Conventional Lung IMRT Using Consistent/Unbiased Automated Plans
Deep learning (DL) 3D dose prediction has recently gained a lot of atten...
research
∙
03/27/2021
Intrinsic Integration
If we wish to integrate a function h|Ω⊂^n→ along a single T-level surfac...
research
∙
03/27/2021
An Efficiently Coupled Shape and Appearance Prior for Active Contour Segmentation
This paper proposes a novel training model based on shape and appearance...
research
∙
03/09/2021
Multitask 3D CBCT-to-CT Translation and Organs-at-Risk Segmentation Using Physics-Based Data Augmentation
Purpose: In current clinical practice, noisy and artifact-ridden weekly ...
research
∙
10/19/2020
Verifying the Causes of Adversarial Examples
The robustness of neural networks is challenged by adversarial examples ...
research
∙
11/26/2019
An Adaptive View of Adversarial Robustness from Test-time Smoothing Defense
The safety and robustness of learning-based decision-making systems are ...
research
∙
10/07/2019
An Interactive Control Approach to 3D Shape Reconstruction
The ability to accurately reconstruct the 3D facets of a scene is one of...
research
∙
09/30/2018
Accelerated PDE's for efficient solution of regularized inversion problems
We further develop a new framework, called PDE Acceleration, by applying...
research
∙
04/04/2018
Accelerated Optimization in the PDE Framework: Formulations for the Manifold of Diffeomorphisms
We consider the problem of optimization of cost functionals on the infin...
research
∙
01/27/2018
Towards an Understanding of Neural Networks in Natural-Image Spaces
Two major uncertainties, dataset bias and perturbation, prevail in state...
research
∙
11/27/2017
Accelerated Optimization in the PDE Framework: Formulations for the Active Contour Case
Following the seminal work of Nesterov, accelerated optimization methods...
research
∙
02/06/2014
Tracking via Motion Estimation with Physically Motivated Inter-Region Constraints
In this paper, we propose a method for tracking structures (e.g., ventri...
research
∙
12/03/2013
