Nesreen K. Ahmed

Orcid: 0000-0002-7913-4962

According to our database1, Nesreen K. Ahmed authored at least 131 papers between 2010 and 2024.

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Bibliography

2024
Fairness-Aware Graph Neural Networks: A Survey.
ACM Trans. Knowl. Discov. Data, July, 2024

Memory-Augmented Graph Neural Networks: A Brain-Inspired Review.
IEEE Trans. Artif. Intell., May, 2024

GRS-QA - Graph Reasoning-Structured Question Answering Dataset.
CoRR, 2024

Personalization of Large Language Models: A Survey.
CoRR, 2024

CodeRosetta: Pushing the Boundaries of Unsupervised Code Translation for Parallel Programming.
CoRR, 2024

A Survey of Small Language Models.
CoRR, 2024

OMPar: Automatic Parallelization with AI-Driven Source-to-Source Compilation.
CoRR, 2024

ICML Topological Deep Learning Challenge 2024: Beyond the Graph Domain.
CoRR, 2024

Large Generative Graph Models.
CoRR, 2024

A structure-aware framework for learning device placements on computation graphs.
CoRR, 2024

MPIrigen: MPI Code Generation through Domain-Specific Language Models.
CoRR, 2024

The Landscape and Challenges of HPC Research and LLMs.
CoRR, 2024

The 5th International Workshop on Machine Learning on Graphs (MLoG).
Proceedings of the 17th ACM International Conference on Web Search and Data Mining, 2024

GrAPL 2024 Preface and Committees.
Proceedings of the IEEE International Parallel and Distributed Processing Symposium, 2024

Editing Partially Observable Networks via Graph Diffusion Models.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

Forward Learning of Graph Neural Networks.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

OMPGPT: A Generative Pre-trained Transformer Model for OpenMP.
Proceedings of the Euro-Par 2024: Parallel Processing, 2024

Structure Guided Prompt: Instructing Large Language Model in Multi-Step Reasoning by Exploring Graph Structure of the Text.
Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing, 2024

2023
Domain-Specific Code Language Models: Unraveling the Potential for HPC Codes and Tasks.
CoRR, 2023

Leveraging Reinforcement Learning and Large Language Models for Code Optimization.
CoRR, 2023

Leveraging Graph Diffusion Models for Network Refinement Tasks.
CoRR, 2023

CompCodeVet: A Compiler-guided Validation and Enhancement Approach for Code Dataset.
CoRR, 2023

AUTOPARLLM: GNN-Guided Automatic Code Parallelization using Large Language Models.
CoRR, 2023

Bias and Fairness in Large Language Models: A Survey.
CoRR, 2023

Scope is all you need: Transforming LLMs for HPC Code.
CoRR, 2023

On Graph Time-Series Representations for Temporal Networks.
Proceedings of the Companion Proceedings of the ACM Web Conference 2023, 2023

A ML-based Approach for HTML-based Style Recommendation.
Proceedings of the Companion Proceedings of the ACM Web Conference 2023, 2023

PERFOGRAPH: A Numerical Aware Program Graph Representation for Performance Optimization and Program Analysis.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

GLEMOS: Benchmark for Instantaneous Graph Learning Model Selection.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Learning to Parallelize with OpenMP by Augmented Heterogeneous AST Representation.
Proceedings of the Sixth Conference on Machine Learning and Systems, 2023

Augmenting Recurrent Graph Neural Networks with a Cache.
Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2023

MetaGL: Evaluation-Free Selection of Graph Learning Models via Meta-Learning.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

Neural Compositional Rule Learning for Knowledge Graph Reasoning.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

Efficient Estimation of Local Causal Effects in Graphs via Neighborhood Pooling.
Proceedings of the IEEE International Conference on Big Data, 2023

2022
Personalized Visualization Recommendation.
ACM Trans. Web, 2022

Role-Based Graph Embeddings.
IEEE Trans. Knowl. Data Eng., 2022

A Hypergraph Neural Network Framework for Learning Hyperedge-Dependent Node Embeddings.
CoRR, 2022

Graph Learning with Localized Neighborhood Fairness.
CoRR, 2022

Memory-Augmented Graph Neural Networks: A Neuroscience Perspective.
CoRR, 2022

AutoGML: Fast Automatic Model Selection for Graph Machine Learning.
CoRR, 2022

End-to-end Mapping in Heterogeneous Systems Using Graph Representation Learning.
CoRR, 2022

CGC: Contrastive Graph Clustering for Community Detection and Tracking.
CoRR, 2022

CGC: Contrastive Graph Clustering forCommunity Detection and Tracking.
Proceedings of the WWW '22: The ACM Web Conference 2022, Virtual Event, Lyon, France, April 25, 2022

Technology Growth Ranking Using Temporal Graph Representation Learning.
Proceedings of the Companion of The Web Conference 2022, Virtual Event / Lyon, France, April 25, 2022

Joint Learning of Hierarchical Community Structure and Node Representations: An Unsupervised Approach.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2022

One-Pass Algorithms for MAP Inference of Nonsymmetric Determinantal Point Processes.
Proceedings of the International Conference on Machine Learning, 2022

Network Report: A Structured Description for Network Datasets.
Proceedings of the 31st ACM International Conference on Information & Knowledge Management, 2022

2021
Heterogeneous Graphlets.
ACM Trans. Knowl. Discov. Data, 2021

Online Sampling of Temporal Networks.
ACM Trans. Knowl. Discov. Data, 2021

Dynamic Node Embeddings From Edge Streams.
IEEE Trans. Emerg. Top. Comput. Intell., 2021

Deep graph similarity learning: a survey.
Data Min. Knowl. Discov., 2021

Online MAP Inference and Learning for Nonsymmetric Determinantal Point Processes.
CoRR, 2021

DistGNN: scalable distributed training for large-scale graph neural networks.
Proceedings of the International Conference for High Performance Computing, 2021

A Distributed Graph-Theoretic Framework for Automatic Parallelization in Multi-core Systems.
Proceedings of the Fourth Conference on Machine Learning and Systems, 2021

From Closing Triangles to Higher-Order Motif Closures for Better Unsupervised Online Link Prediction.
Proceedings of the CIKM '21: The 30th ACM International Conference on Information and Knowledge Management, Virtual Event, Queensland, Australia, November 1, 2021

Learning Code Representations Using Multifractal-based Graph Networks.
Proceedings of the 2021 IEEE International Conference on Big Data (Big Data), 2021

Graph Neural Networks with Heterophily.
Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020
Deep Inductive Graph Representation Learning.
IEEE Trans. Knowl. Data Eng., 2020

On Proximity and Structural Role-based Embeddings in Networks: Misconceptions, Techniques, and Applications.
ACM Trans. Knowl. Discov. Data, 2020

Correction to: Complex networks are structurally distinguishable by domain.
Soc. Netw. Anal. Min., 2020

PIUMA: Programmable Integrated Unified Memory Architecture.
CoRR, 2020

A Vertex Cut based Framework for Load Balancing and Parallelism Optimization in Multi-core Systems.
CoRR, 2020

Inferring Individual Level Causal Models from Graph-based Relational Time Series.
CoRR, 2020

Fast and Accurate Estimation of Typed Graphlets.
Proceedings of the Companion of The 2020 Web Conference 2020, 2020

From Closing Triangles to Closing Higher-Order Motifs.
Proceedings of the Companion of The 2020 Web Conference 2020, 2020

Fast Hierarchical Graph Clustering in Linear-Time.
Proceedings of the Companion of The 2020 Web Conference 2020, 2020

A Structural Graph Representation Learning Framework.
Proceedings of the WSDM '20: The Thirteenth ACM International Conference on Web Search and Data Mining, 2020

Deep Parametric Model for Discovering Group-cohesive Functional Brain Regions.
Proceedings of the 2020 SIAM International Conference on Data Mining, 2020

Adaptive Shrinkage Estimation for Streaming Graphs.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

NeuroVectorizer: end-to-end vectorization with deep reinforcement learning.
Proceedings of the CGO '20: 18th ACM/IEEE International Symposium on Code Generation and Optimization, 2020

2019
Estimation of Graphlet Counts in Massive Networks.
IEEE Trans. Neural Networks Learn. Syst., 2019

Attention Models in Graphs: A Survey.
ACM Trans. Knowl. Discov. Data, 2019

Complex networks are structurally distinguishable by domain.
Soc. Netw. Anal. Min., 2019

Temporal Network Sampling.
CoRR, 2019

From Community to Role-based Graph Embeddings.
CoRR, 2019

Deep Reinforcement Learning in System Optimization.
CoRR, 2019

Network Shrinkage Estimation.
CoRR, 2019

Linear-time Hierarchical Community Detection.
CoRR, 2019

Higher-Order Ranking and Link Prediction: From Closing Triangles to Closing Higher-Order Motifs.
CoRR, 2019

Temporal Network Representation Learning.
CoRR, 2019

Heterogeneous Network Motifs.
CoRR, 2019

Deep Graph Similarity Learning for Brain Data Analysis.
Proceedings of the 28th ACM International Conference on Information and Knowledge Management, 2019

2018
Interactive Visual Graph Mining and Learning.
ACM Trans. Intell. Syst. Technol., 2018

Similarity Learning with Higher-Order Proximity for Brain Network Analysis.
CoRR, 2018

Learning Role-based Graph Embeddings.
CoRR, 2018

HONE: Higher-Order Network Embeddings.
CoRR, 2018

Deep Inductive Network Representation Learning.
Proceedings of the Companion of the The Web Conference 2018 on The Web Conference 2018, 2018

Higher-order Network Representation Learning.
Proceedings of the Companion of the The Web Conference 2018 on The Web Conference 2018, 2018

Continuous-Time Dynamic Network Embeddings.
Proceedings of the Companion of the The Web Conference 2018 on The Web Conference 2018, 2018

GraML 2018 Keynote.
Proceedings of the 2018 IEEE International Parallel and Distributed Processing Symposium Workshops, 2018

Similarity-based Multi-label Learning.
Proceedings of the 2018 International Joint Conference on Neural Networks, 2018

Sampling for Approximate Bipartite Network Projection.
Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence, 2018

Interactive Higher-Order Network Analysis.
Proceedings of the 2018 IEEE International Conference on Data Mining Workshops, 2018

Relational Similarity Machines (RSM): A Similarity-based Learning Framework for Graphs.
Proceedings of the IEEE International Conference on Big Data (IEEE BigData 2018), 2018

Dynamic Network Embeddings: From Random Walks to Temporal Random Walks.
Proceedings of the IEEE International Conference on Big Data (IEEE BigData 2018), 2018

2017
On Sampling from Massive Graph Streams.
Proc. VLDB Endow., 2017

Graphlet decomposition: framework, algorithms, and applications.
Knowl. Inf. Syst., 2017

Estimating Node Similarity by Sampling Streaming Bipartite Graphs.
CoRR, 2017

Representation Learning in Large Attributed Graphs.
CoRR, 2017

A Framework for Generalizing Graph-based Representation Learning Methods.
CoRR, 2017

Network Classification and Categorization.
CoRR, 2017

Deep Feature Learning for Graphs.
CoRR, 2017

Estimation of Graphlet Statistics.
CoRR, 2017

Edge Role Discovery via Higher-Order Structures.
Proceedings of the Advances in Knowledge Discovery and Data Mining, 2017

Exploring optimizations on shared-memory platforms for parallel triangle counting algorithms.
Proceedings of the 2017 IEEE High Performance Extreme Computing Conference, 2017

Truss decomposition on shared-memory parallel systems.
Proceedings of the 2017 IEEE High Performance Extreme Computing Conference, 2017

A Formal Approach to Modeling the Cost of Cognitive Control.
Proceedings of the 39th Annual Meeting of the Cognitive Science Society, 2017

Stream Aggregation Through Order Sampling.
Proceedings of the 2017 ACM on Conference on Information and Knowledge Management, 2017

E-CLoG: Counting edge-centric local graphlets.
Proceedings of the 2017 IEEE International Conference on Big Data (IEEE BigData 2017), 2017

A Higher-Order Latent Space Network Model.
Proceedings of the Workshops of the The Thirty-First AAAI Conference on Artificial Intelligence, 2017

2016
Relational Similarity Machines.
CoRR, 2016

Revisiting Role Discovery in Networks: From Node to Edge Roles.
CoRR, 2016

Exact and Estimation of Local Edge-centric Graphlet Counts.
Proceedings of the 5th International Workshop on Big Data, 2016

Estimation of local subgraph counts.
Proceedings of the 2016 IEEE International Conference on Big Data (IEEE BigData 2016), 2016

2015
Scaling Up Network Analysis and Mining: Statistical Sampling, Estimation, and Pattern Discovery
PhD thesis, 2015

Role Discovery in Networks.
IEEE Trans. Knowl. Data Eng., 2015

An Interactive Data Repository with Visual Analytics.
SIGKDD Explor., 2015

A Web-based Interactive Visual Graph Analytics Platform.
CoRR, 2015

Fast Parallel Graphlet Counting for Large Networks.
CoRR, 2015

Interactive Visual Graph Analytics on the Web.
Proceedings of the Ninth International Conference on Web and Social Media, 2015

Efficient Graphlet Counting for Large Networks.
Proceedings of the 2015 IEEE International Conference on Data Mining, 2015

The Network Data Repository with Interactive Graph Analytics and Visualization.
Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence, 2015

2014
Coloring large complex networks.
Soc. Netw. Anal. Min., 2014

NetworkRepository: A Graph Data Repository with Visual Interactive Analytics.
CoRR, 2014

Learning the Latent State Space of Time-Varying Graphs.
CoRR, 2014

Graph sample and hold: a framework for big-graph analytics.
Proceedings of the 20th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2014

2013
Network Sampling: From Static to Streaming Graphs.
ACM Trans. Knowl. Discov. Data, 2013

2012
Does a Daily Deal Promotion Signal a Distressed Business? An Empirical Investigation of Small Business Survival
CoRR, 2012

Space-efficient sampling from social activity streams.
Proceedings of the 1st International Workshop on Big Data, 2012

Network Sampling Designs for Relational Classification.
Proceedings of the Sixth International Conference on Weblogs and Social Media, 2012

2010
Time-based sampling of social network activity graphs.
Proceedings of the Eighth Workshop on Mining and Learning with Graphs, 2010


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