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05/04/2023
BitGNN: Unleashing the Performance Potential of Binary Graph Neural Networks on GPUs
Recent studies have shown that Binary Graph Neural Networks (GNNs) are p...
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03/15/2023
Cloud Services Enable Efficient AI-Guided Simulation Workflows across Heterogeneous Resources
Applications that fuse machine learning and simulation can benefit from ...
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11/25/2022
Extreme Acceleration of Graph Neural Network-based Prediction Models for Quantum Chemistry
Molecular property calculations are the bedrock of chemical physics. Hig...
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11/08/2022
Reducing Down(stream)time: Pretraining Molecular GNNs using Heterogeneous AI Accelerators
The demonstrated success of transfer learning has popularized approaches...
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06/09/2022
Pseudo-Poincaré: A Unification Framework for Euclidean and Hyperbolic Graph Neural Networks
Hyperbolic neural networks have recently gained significant attention du...
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02/09/2021
Benchmarking Deep Graph Generative Models for Optimizing New Drug Molecules for COVID-19
Design of new drug compounds with target properties is a key area of res...
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11/30/2020
HydroNet: Benchmark Tasks for Preserving Intermolecular Interactions and Structural Motifs in Predictive and Generative Models for Molecular Data
Intermolecular and long-range interactions are central to phenomena as d...
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07/22/2020
Self-Supervised Learning of Contextual Embeddings for Link Prediction in Heterogeneous Networks
Representation learning methods for heterogeneous networks produce a low...
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07/19/2019
Snomed2Vec: Random Walk and Poincaré Embeddings of a Clinical Knowledge Base for Healthcare Analytics
Representation learning methods that transform encoded data (e.g., diagn...
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05/03/2019
Enterprise Cyber Resiliency Against Lateral Movement: A Graph Theoretic Approach
Lateral movement attacks are a serious threat to enterprise security. In...
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01/24/2018
A Chronological Edge-Driven Approach to Temporal Subgraph Isomorphism
Many real world networks are considered temporal networks, in which the ...
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01/14/2016
Trust from the past: Bayesian Personalized Ranking based Link Prediction in Knowledge Graphs
Link prediction, or predicting the likelihood of a link in a knowledge g...
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12/23/2015
Multi-centrality Graph Spectral Decompositions and their Application to Cyber Intrusion Detection
Many modern datasets can be represented as graphs and hence spectral dec...
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04/24/2013
