b'Roland Kwitt'

research

∙ 06/13/2022

GradICON: Approximate Diffeomorphisms via Gradient Inverse Consistency

Many registration approaches exist with early work focusing on optimizat...

Lin Tian, et al. ∙

research

∙ 02/16/2022

On Measuring Excess Capacity in Neural Networks

We study the excess capacity of deep networks in the context of supervis...

Florian Graf, et al. ∙

research

∙ 07/30/2021

Comparing object recognition in humans and deep convolutional neural networks – An eye tracking study

Deep convolutional neural networks (DCNNs) and the ventral visual pathwa...

Leonard E. van Dyck, et al. ∙

research

∙ 07/19/2021

Topological Attention for Time Series Forecasting

The problem of (point) forecasting univariate time series is considered....

Sebastian Zeng, et al. ∙

research

∙ 05/10/2021

ICON: Learning Regular Maps Through Inverse Consistency

Learning maps between data samples is fundamental. Applications range fr...

Hastings Greer, et al. ∙

research

∙ 05/01/2021

Sparse Pose Trajectory Completion

We propose a method to learn, even using a dataset where objects appear ...

Bo Liu, et al. ∙

research

∙ 02/17/2021

Dissecting Supervised Constrastive Learning

Minimizing cross-entropy over the softmax scores of a linear map compose...

Florian Graf, et al. ∙

research

∙ 06/18/2020

A Shooting Formulation of Deep Learning

Continuous-depth neural networks can be viewed as deep limits of discret...

François-Xavier Vialard, et al. ∙

research

∙ 02/12/2020

Topologically Densified Distributions

We study regularization in the context of small sample-size learning wit...

Christoph D. Hofer, et al. ∙

research

∙ 07/17/2019

Deep Multi-View Learning via Task-Optimal CCA

Canonical Correlation Analysis (CCA) is widely used for multimodal data ...

Heather D. Couture, et al. ∙

research

∙ 06/21/2019

Connectivity-Optimized Representation Learning via Persistent Homology

We study the problem of learning representations with controllable conne...

Christoph Hofer, et al. ∙

research

∙ 05/27/2019

Graph Filtration Learning

We propose an approach to learning with graph-structured data in the pro...

Christoph Hofer, et al. ∙

research

∙ 04/21/2019

Metric Learning for Image Registration

Image registration is a key technique in medical image analysis to estim...

Marc Niethammer, et al. ∙

research

∙ 03/07/2018

Stochastic Block Models with Multiple Continuous Attributes

The stochastic block model (SBM) is a probabilistic model for community ...

Natalie Stanley, et al. ∙

research

∙ 01/13/2018

Feature Space Transfer for Data Augmentation

The problem of data augmentation in feature space is considered. A new a...

Bo Liu, et al. ∙

research

∙ 11/15/2017

Fast Predictive Simple Geodesic Regression

Deformable image registration and regression are important tasks in medi...

Zhipeng Ding, et al. ∙

research

∙ 11/15/2017

Brain Extraction from Normal and Pathological Images: A Joint PCA/Image-Reconstruction Approach

Brain extraction from 3D medical images is a common pre-processing step....

Xu Han, et al. ∙

research

∙ 07/13/2017

Deep Learning with Topological Signatures

Inferring topological and geometrical information from data can offer an...

Christoph Hofer, et al. ∙

research

∙ 03/31/2017

Efficient Registration of Pathological Images: A Joint PCA/Image-Reconstruction Approach

Registration involving one or more images containing pathologies is chal...

Xu Han, et al. ∙

research

∙ 03/31/2017

Quicksilver: Fast Predictive Image Registration - a Deep Learning Approach

This paper introduces Quicksilver, a fast deformable image registration ...

Xiao Yang, et al. ∙

research

∙ 03/31/2017

Fast Predictive Multimodal Image Registration

We introduce a deep encoder-decoder architecture for image deformation p...

Xiao Yang, et al. ∙

research

∙ 12/08/2016

AGA: Attribute Guided Augmentation

We consider the problem of data augmentation, i.e., generating artificia...

Mandar Dixit, et al. ∙

research

∙ 07/08/2016

Fast Predictive Image Registration

We present a method to predict image deformations based on patch-wise im...

Xiao Yang, et al. ∙

research

∙ 04/30/2015

Proceedings of The 39th Annual Workshop of the Austrian Association for Pattern Recognition (OAGM), 2015

The 39th annual workshop of the Austrian Association for Pattern Recogni...

Sebastian Hegenbart, et al. ∙

research

∙ 12/21/2014

A Stable Multi-Scale Kernel for Topological Machine Learning

Topological data analysis offers a rich source of valuable information t...

Jan Reininghaus, et al. ∙

Roland Kwitt

Featured Co-authors

Bo Liu

Xu Han

Gang Hua

Nuno Vasconcelos

Marc Niethammer

Bjoern Menze

Xiao Yang

Ulrich Bauer

J. S. Marron

François-Xavier Vialard

Andreas Uhl

GradICON: Approximate Diffeomorphisms via Gradient Inverse Consistency

On Measuring Excess Capacity in Neural Networks

Comparing object recognition in humans and deep convolutional neural networks – An eye tracking study

Topological Attention for Time Series Forecasting

ICON: Learning Regular Maps Through Inverse Consistency

Sparse Pose Trajectory Completion

Dissecting Supervised Constrastive Learning

A Shooting Formulation of Deep Learning

Topologically Densified Distributions

Deep Multi-View Learning via Task-Optimal CCA

Connectivity-Optimized Representation Learning via Persistent Homology

Graph Filtration Learning

Metric Learning for Image Registration

Stochastic Block Models with Multiple Continuous Attributes

Feature Space Transfer for Data Augmentation

Fast Predictive Simple Geodesic Regression

Brain Extraction from Normal and Pathological Images: A Joint PCA/Image-Reconstruction Approach

Deep Learning with Topological Signatures

Efficient Registration of Pathological Images: A Joint PCA/Image-Reconstruction Approach

Quicksilver: Fast Predictive Image Registration - a Deep Learning Approach

Fast Predictive Multimodal Image Registration

AGA: Attribute Guided Augmentation

Fast Predictive Image Registration

Proceedings of The 39th Annual Workshop of the Austrian Association for Pattern Recognition (OAGM), 2015

A Stable Multi-Scale Kernel for Topological Machine Learning