Daniel Moyer | DeepAI

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∙ 06/09/2023

NeuroGraph: Benchmarks for Graph Machine Learning in Brain Connectomics

Machine learning provides a valuable tool for analyzing high-dimensional...

0 Anwar Said, et al. ∙

∙ 06/22/2022

SVoRT: Iterative Transformer for Slice-to-Volume Registration in Fetal Brain MRI

Volumetric reconstruction of fetal brains from multiple stacks of MR sli...

0 Junshen Xu, et al. ∙

∙ 11/13/2021

Image Classification with Consistent Supporting Evidence

Adoption of machine learning models in healthcare requires end users' tr...

0 Peiqi Wang, et al. ∙

∙ 03/18/2021

Equivariant Filters for Efficient Tracking in 3D Imaging

We demonstrate an object tracking method for 3D images with fixed comput...

0 Daniel Moyer, et al. ∙

∙ 03/08/2021

Multimodal Representation Learning via Maximization of Local Mutual Information

We propose and demonstrate a representation learning approach by maximiz...

0 Ruizhi Liao, et al. ∙

∙ 01/15/2021

Harmonization and the Worst Scanner Syndrome

We show that for a wide class of harmonization/domain-invariance schemes...

0 Daniel Moyer, et al. ∙

∙ 12/08/2020

Bayesian Image Reconstruction using Deep Generative Models

Machine learning models are commonly trained end-to-end and in a supervi...

19 Razvan V. Marinescu, et al. ∙

∙ 10/05/2020

DEMI: Discriminative Estimator of Mutual Information

Estimating mutual information between continuous random variables is oft...

0 Ruizhi Liao, et al. ∙

∙ 05/29/2020

Overview of Scanner Invariant Representations

Pooled imaging data from multiple sources is subject to bias from each s...

8 Daniel Moyer, et al. ∙

∙ 12/02/2019

Discovery and Separation of Features for Invariant Representation Learning

Supervised machine learning models often associate irrelevant nuisance f...

47 Ayush Jaiswal, et al. ∙

∙ 11/11/2019

Invariant Representations through Adversarial Forgetting

We propose a novel approach to achieving invariance for deep neural netw...

29 Ayush Jaiswal, et al. ∙

∙ 05/30/2019

Efficient Covariance Estimation from Temporal Data

Estimating the covariance structure of multivariate time series is a fun...

3 Hrayr Harutyunyan, et al. ∙

∙ 04/15/2019

Exact Rate-Distortion in Autoencoders via Echo Noise

Compression is at the heart of effective representation learning. Howeve...

36 Rob Brekelmans, et al. ∙

∙ 04/10/2019

Scanner Invariant Representations for Diffusion MRI Harmonization

Pooled imaging data from multiple sources is subject to variation betwee...

26 Daniel Moyer, et al. ∙

∙ 08/10/2018

Connectivity-Driven Brain Parcellation via Consensus Clustering

We present two related methods for deriving connectivity-based brain atl...

0 Anvar Kurmukov, et al. ∙

∙ 06/12/2018

Measures of Tractography Convergence

In the present work, we use information theory to understand the empiric...

0 Daniel Moyer, et al. ∙

∙ 05/24/2018

Evading the Adversary in Invariant Representation

Representations of data that are invariant to changes in specified nuisa...

0 Daniel Moyer, et al. ∙

∙ 06/19/2017

Evaluating 35 Methods to Generate Structural Connectomes Using Pairwise Classification

There is no consensus on how to construct structural brain networks from...

0 Dmitry Petrov, et al. ∙

∙ 03/02/2017

A Restaurant Process Mixture Model for Connectivity Based Parcellation of the Cortex

One of the primary objectives of human brain mapping is the division of ...

0 Daniel Moyer, et al. ∙

∙ 11/18/2016

An Empirical Study of Continuous Connectivity Degree Sequence Equivalents

In the present work we demonstrate the use of a parcellation free connec...

0 Daniel Moyer, et al. ∙

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