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08/24/2023
Beyond Document Page Classification: Design, Datasets, and Challenges
This paper highlights the need to bring document classification benchmar...
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07/24/2023
Dense Transformer based Enhanced Coding Network for Unsupervised Metal Artifact Reduction
CT images corrupted by metal artifacts have serious negative effects on ...
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05/31/2023
Surrogate Model Extension (SME): A Fast and Accurate Weight Update Attack on Federated Learning
In Federated Learning (FL) and many other distributed training framework...
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05/21/2023
Confidence-aware Personalized Federated Learning via Variational Expectation Maximization
Federated Learning (FL) is a distributed learning scheme to train a shar...
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03/28/2023
Dice Semimetric Losses: Optimizing the Dice Score with Soft Labels
The soft Dice loss (SDL) has taken a pivotal role in many automated segm...
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02/11/2023
Jaccard Metric Losses: Optimizing the Jaccard Index with Soft Labels
IoU losses are surrogates that directly optimize the Jaccard index. In s...
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10/25/2022
Clinically-Inspired Multi-Agent Transformers for Disease Trajectory Forecasting from Multimodal Data
Deep neural networks are often applied to medical images to automate the...
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10/13/2022
A Consistent and Differentiable Lp Canonical Calibration Error Estimator
Calibrated probabilistic classifiers are models whose predicted probabil...
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08/25/2022
On confidence intervals for precision matrices and the eigendecomposition of covariance matrices
The eigendecomposition of a matrix is the central procedure in probabili...
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07/13/2022
MRF-UNets: Searching UNet with Markov Random Fields
UNet [27] is widely used in semantic segmentation due to its simplicity ...
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06/17/2022
Designing MacPherson Suspension Architectures using Bayesian Optimization
Engineering design is traditionally performed by hand: an expert makes d...
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06/04/2022
Combinatorial optimization for low bit-width neural networks
Low-bit width neural networks have been extensively explored for deploym...
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12/23/2021
On the relationship between calibrated predictors and unbiased volume estimation
Machine learning driven medical image segmentation has become standard i...
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06/07/2021
Pointwise visual field estimation from optical coherence tomography in glaucoma: a structure-function analysis using deep learning
Background/Aims: Standard Automated Perimetry (SAP) is the gold standard...
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05/29/2021
Greedy Bayesian Posterior Approximation with Deep Ensembles
Ensembles of independently trained neural networks are a state-of-the-ar...
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05/10/2021
Meta-Cal: Well-controlled Post-hoc Calibration by Ranking
In many applications, it is desirable that a classifier not only makes a...
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04/08/2021
DeepProg: A Transformer-based Framework for Predicting Disease Prognosis
A vast majority of deep learning methods are built to automate diagnosti...
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03/22/2021
Glaucoma detection beyond the optic disc: The importance of the peripapillary region using explainable deep learning
Today, a large number of glaucoma cases remain undetected, resulting in ...
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10/26/2020
Optimization for Medical Image Segmentation: Theory and Practice when evaluating with Dice Score or Jaccard Index
In many medical imaging and classical computer vision tasks, the Dice sc...
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10/06/2020
Additive Tree-Structured Conditional Parameter Spaces in Bayesian Optimization: A Novel Covariance Function and a Fast Implementation
Bayesian optimization (BO) is a sample-efficient global optimization alg...
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06/21/2020
Additive Tree-Structured Covariance Function for Conditional Parameter Spaces in Bayesian Optimization
Bayesian optimization (BO) is a sample-efficient global optimization alg...
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06/04/2020
Pathological myopia classification with simultaneous lesion segmentation using deep learning
This investigation reports on the results of convolutional neural networ...
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05/21/2020
AOWS: Adaptive and optimal network width search with latency constraints
Neural architecture search (NAS) approaches aim at automatically finding...
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11/25/2019
Discriminative training of conditional random fields with probably submodular constraints
Problems of segmentation, denoising, registration and 3D reconstruction ...
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07/23/2019
Adaptive Compression-based Lifelong Learning
The problem of a deep learning model losing performance on a previously ...
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09/06/2018
Yes, IoU loss is submodular - as a function of the mispredictions
This note is a response to [7] in which it is claimed that [13, Proposit...
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07/17/2018
Supermodular Locality Sensitive Hashes
In this work, we show deep connections between Locality Sensitive Hashab...
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06/07/2018
Efficient semantic image segmentation with superpixel pooling
In this work, we evaluate the use of superpixel pooling layers in deep n...
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05/25/2018
Towards a glaucoma risk index based on simulated hemodynamics from fundus images
Glaucoma is the leading cause of irreversible but preventable blindness ...
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10/18/2017
Stochastic Weighted Function Norm Regularization
Deep neural networks (DNNs) have become increasingly important due to th...
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06/09/2017
An Ensemble Deep Learning Based Approach for Red Lesion Detection in Fundus Images
Diabetic retinopathy is one of the leading causes of preventable blindne...
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05/24/2017
Optimization of the Jaccard index for image segmentation with the Lovász hinge
The Jaccard loss, commonly referred to as the intersection-over-union lo...
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03/31/2017
Intraoperative margin assessment of human breast tissue in optical coherence tomography images using deep neural networks
Objective: In this work, we perform margin assessment of human breast ti...
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05/30/2016
Stochastic Function Norm Regularization of Deep Networks
Deep neural networks have had an enormous impact on image analysis. Stat...
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12/29/2015
Testing for Differences in Gaussian Graphical Models: Applications to Brain Connectivity
Functional brain networks are well described and estimated from data wit...
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11/14/2015