Theodore L. Willke | DeepAI

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Featured Co-authors

Philip S. Yu
283 publications
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∙ 10/09/2020

A Vertex Cut based Framework for Load Balancing and Parallelism Optimization in Multi-core Systems

High-level applications, such as machine learning, are evolving from sim...

0 Guixiang Ma, et al. ∙

∙ 07/20/2020

Navigating the Trade-Off between Multi-Task Learning and Learning to Multitask in Deep Neural Networks

The terms multi-task learning and multitasking are easily confused. Mult...

0 Sachin Ravi, et al. ∙

∙ 12/25/2019

Deep Graph Similarity Learning: A Survey

In many domains where data are represented as graphs, learning a similar...

25 Guixiang Ma, et al. ∙

∙ 08/30/2019

A single-layer RNN can approximate stacked and bidirectional RNNs, and topologies in between

To enhance the expressiveness and representational capacity of recurrent...

1 Javier S. Turek, et al. ∙

∙ 09/11/2018

Clinically Deployed Distributed Magnetic Resonance Imaging Reconstruction: Application to Pediatric Knee Imaging

Magnetic resonance imaging is capable of producing volumetric images wit...

4 Michael J. Anderson, et al. ∙

∙ 09/04/2018

Out-of-Distribution Detection Using an Ensemble of Self Supervised Leave-out Classifiers

As deep learning methods form a critical part in commercially important ...

0 Apoorv Vyas, et al. ∙

∙ 07/16/2018

Scheduling Computation Graphs of Deep Learning Models on Manycore CPUs

For a deep learning model, efficient execution of its computation graph ...

0 Linpeng Tang, et al. ∙

∙ 02/07/2018

Learning Role-based Graph Embeddings

Random walks are at the heart of many existing network embedding methods...

0 Nesreen K. Ahmed, et al. ∙

∙ 11/17/2017

Segmenting Brain Tumors with Symmetry

We explore encoding brain symmetry into a neural network for a brain tum...

0 Hejia Zhang, et al. ∙

∙ 10/25/2017

Inductive Representation Learning in Large Attributed Graphs

Graphs (networks) are ubiquitous and allow us to model entities (nodes) ...

0 Nesreen K. Ahmed, et al. ∙

∙ 09/14/2017

A Framework for Generalizing Graph-based Representation Learning Methods

Random walks are at the heart of many existing deep learning algorithms ...

0 Nesreen K. Ahmed, et al. ∙

∙ 10/04/2016

Revisiting Role Discovery in Networks: From Node to Edge Roles

Previous work in network analysis has focused on modeling the mixed-memb...

0 Nesreen K. Ahmed, et al. ∙

∙ 09/29/2016

A Searchlight Factor Model Approach for Locating Shared Information in Multi-Subject fMRI Analysis

There is a growing interest in joint multi-subject fMRI analysis. The ch...

0 Hejia Zhang, et al. ∙

∙ 08/17/2016

A Convolutional Autoencoder for Multi-Subject fMRI Data Aggregation

Finding the most effective way to aggregate multi-subject fMRI data is a...

0 Po-Hsuan Chen, et al. ∙

∙ 08/16/2016

Enabling Factor Analysis on Thousand-Subject Neuroimaging Datasets

The scale of functional magnetic resonance image data is rapidly increas...

0 Michael J. Anderson, et al. ∙

∙ 06/13/2015

Graphlet Decomposition: Framework, Algorithms, and Applications

From social science to biology, numerous applications often rely on grap...

0 Nesreen K. Ahmed, et al. ∙