Search Results for author: Mohamed R. Amer

Found 9 papers, 3 papers with code

Image Classification with Hierarchical Multigraph Networks

1 code implementation21 Jul 2019 Boris Knyazev, Xiao Lin, Mohamed R. Amer, Graham W. Taylor

Graph Convolutional Networks (GCNs) are a class of general models that can learn from graph structured data.

Classification General Classification +1

Data-Efficient Mutual Information Neural Estimator

no code implementations8 May 2019 Xiao Lin, Indranil Sur, Samuel A. Nastase, Ajay Divakaran, Uri Hasson, Mohamed R. Amer

We demonstrate the effectiveness of our estimators on synthetic benchmarks and a real world fMRI data, with application of inter-subject correlation analysis.


Understanding Attention and Generalization in Graph Neural Networks

2 code implementations NeurIPS 2019 Boris Knyazev, Graham W. Taylor, Mohamed R. Amer

We aim to better understand attention over nodes in graph neural networks (GNNs) and identify factors influencing its effectiveness.

Graph Classification

Spectral Multigraph Networks for Discovering and Fusing Relationships in Molecules

1 code implementation23 Nov 2018 Boris Knyazev, Xiao Lin, Mohamed R. Amer, Graham W. Taylor

Spectral Graph Convolutional Networks (GCNs) are a generalization of convolutional networks to learning on graph-structured data.

Classification General Classification +2

Human Motion Modeling using DVGANs

no code implementations27 Apr 2018 Xiao Lin, Mohamed R. Amer

We present a novel generative model for human motion modeling using Generative Adversarial Networks (GANs).

Motion Capture

Structure Optimization for Deep Multimodal Fusion Networks using Graph-Induced Kernels

no code implementations3 Jul 2017 Dhanesh Ramachandram, Michal Lisicki, Timothy J. Shields, Mohamed R. Amer, Graham W. Taylor

A popular testbed for deep learning has been multimodal recognition of human activity or gesture involving diverse inputs such as video, audio, skeletal pose and depth images.

Activity Recognition

Action-Affect Classification and Morphing using Multi-Task Representation Learning

no code implementations21 Mar 2016 Timothy J. Shields, Mohamed R. Amer, Max Ehrlich, Amir Tamrakar

We propose a new model that enhances the CRBM model with a factored multi-task component to become Multi-Task Conditional Restricted Boltzmann Machines (MTCRBMs).

Classification General Classification +3

Human Social Interaction Modeling Using Temporal Deep Networks

no code implementations6 May 2015 Mohamed R. Amer, Behjat Siddiquie, Amir Tamrakar, David A. Salter, Brian Lande, Darius Mehri, Ajay Divakaran

We present a novel approach to computational modeling of social interactions based on modeling of essential social interaction predicates (ESIPs) such as joint attention and entrainment.

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