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Graph-Based Deep Learning for Medical Diagnosis and Analysis: Past, Present and Future

With the advances of data-driven machine learning research, a wide varie...
05/27/2021 ∙ by David Ahmedt-Aristizabal, et al. ∙ 631 ∙ share

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Heterogeneous Graph Representation Learning with Relation Awareness

Representation learning on heterogeneous graphs aims to obtain meaningfu...
05/24/2021 ∙ by Le Yu, et al. ∙ 241 ∙ share

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PYROBOCOP : Python-based Robotic Control Optimization Package for Manipulation and Collision Avoidance

PYROBOCOP is a lightweight Python-based package for control and optimiza...
06/06/2021 ∙ by Arvind U. Raghunathan, et al. ∙ 212 ∙ share

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Graph Neural Networks for Natural Language Processing: A Survey

Deep learning has become the dominant approach in coping with various ta...
06/10/2021 ∙ by Lingfei Wu, et al. ∙ 173 ∙ share

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Uncertainty Quantification 360: A Holistic Toolkit for Quantifying and Communicating the Uncertainty of AI

In this paper, we describe an open source Python toolkit named Uncertain...
06/02/2021 ∙ by Soumya Ghosh, et al. ∙ 107 ∙ share

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GraphMI: Extracting Private Graph Data from Graph Neural Networks

As machine learning becomes more widely used for critical applications, ...
06/05/2021 ∙ by Zaixi Zhang, et al. ∙ 102 ∙ share

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NeuraCrypt: Hiding Private Health Data via Random Neural Networks for Public Training

Balancing the needs of data privacy and predictive utility is a central ...
06/04/2021 ∙ by Adam Yala, et al. ∙ 101 ∙ share

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Efficient Deep Learning: A Survey on Making Deep Learning Models Smaller, Faster, and Better

Deep Learning has revolutionized the fields of computer vision, natural ...
06/16/2021 ∙ by Gaurav Menghani, et al. ∙ 100 ∙ share

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AndroidEnv: A Reinforcement Learning Platform for Android

We introduce AndroidEnv, an open-source platform for Reinforcement Learn...
05/27/2021 ∙ by Daniel Toyama, et al. ∙ 92 ∙ share

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Statistical embedding: Beyond principal components

There has been an intense recent activity in embedding of very high dime...
06/03/2021 ∙ by Dag Tjøstheim, et al. ∙ 90 ∙ share

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Neural Bellman-Ford Networks: A General Graph Neural Network Framework for Link Prediction

Link prediction is a very fundamental task on graphs. Inspired by tradit...
06/13/2021 ∙ by Zhaocheng Zhu, et al. ∙ 82 ∙ share

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