| Communication-Avoiding and Memory-Constrained Sparse Matrix-Matrix Multiplication at Extreme Scale | 1 | 0.37 | 2021 |
| FusedMM: A Unified SDDMM-SpMM Kernel for Graph Embedding and Graph Neural Networks | 1 | 0.36 | 2021 |
| Relational Learning Improves Prediction of Mortality in COVID-19 in the Intensive Care Unit | 0 | 0.34 | 2021 |
| Force2Vec: Parallel Force-Directed Graph Embedding | 0 | 0.34 | 2020 |
| Parallel algorithms for finding connected components using linear algebra. | 2 | 0.37 | 2020 |
| A Distributed-Memory Algorithm for Computing a Heavy-Weight Perfect Matching on Bipartite Graphs | 0 | 0.34 | 2020 |
| FastSV: A Distributed-Memory Connected Component Algorithm with Fast Convergence | 4 | 0.40 | 2020 |
| Optimizing High Performance Markov Clustering for Pre-Exascale Architectures | 1 | 0.37 | 2020 |
| BatchLayout: A Batch-Parallel Force-Directed Graph Layout Algorithm in Shared Memory | 0 | 0.34 | 2020 |
| Performance optimization, modeling and analysis of sparse matrix-matrix products on multi-core and many-core processors | 1 | 0.35 | 2019 |
| LACC: A Linear-Algebraic Algorithm for Finding Connected Components in Distributed Memory | 1 | 0.35 | 2019 |
| A distributed-memory approximation algorithm for maximum weight perfect bipartite matching. | 1 | 0.37 | 2018 |
| Phenotyping Immune Cells in Tumor and Healthy Tissue Using Flow Cytometry Data. | 0 | 0.34 | 2018 |
| Integrated Model, Batch, and Domain Parallelism in Training Neural Networks. | 10 | 0.61 | 2018 |
| A Work-Efficient Parallel Sparse Matrix-Sparse Vector Multiplication Algorithm | 9 | 0.54 | 2017 |
| Computing Maximum Cardinality Matchings in Parallel on Bipartite Graphs via Tree-Grafting. | 6 | 0.50 | 2017 |
| Integrated Model and Data Parallelism in Training Neural Networks. | 0 | 0.34 | 2017 |
| The Reverse Cuthill-McKee Algorithm in Distributed-Memory | 1 | 0.35 | 2017 |
| Communication-Avoiding Parallel Sparse-Dense Matrix-Matrix Multiplication | 9 | 0.53 | 2016 |
| Distributed-Memory Algorithms for Maximum Cardinality Matching in Bipartite Graphs | 4 | 0.43 | 2016 |
| flowVS: channel-specific variance stabilization in flow cytometry. | 0 | 0.34 | 2016 |
| A matrix-algebraic formulation of distributed-memory maximal cardinality matching algorithms in bipartite graphs. | 1 | 0.37 | 2016 |
| Distributed-Memory Algorithms for Maximal Cardinality Matching Using Matrix Algebra | 2 | 0.37 | 2015 |
| Parallel Triangle Counting and Enumeration Using Matrix Algebra | 22 | 1.33 | 2015 |
| A Parallel Tree Grafting Algorithm for Maximum Cardinality Matching in Bipartite Graphs | 4 | 0.41 | 2015 |
| EXPLOITING MULTIPLE LEVELS OF PARALLELISM IN SPARSE MATRIX-MATRIX MULTIPLICATION | 20 | 0.76 | 2015 |
| Codesign Lessons Learned from Implementing Graph Matching on Multithreaded Architectures. | 3 | 0.40 | 2015 |
| On parallel push-relabel based algorithms for bipartite maximum matching | 2 | 0.37 | 2014 |
| Immunophenotypes of Acute Myeloid Leukemia From Flow Cytometry Data Using Templates. | 1 | 0.36 | 2014 |
| Classifying Immunophenotypes With Templates From Flow Cytometry | 1 | 0.37 | 2013 |
| Multithreaded Algorithms for Matching in Graphs with Application to Data Analysis in Flow Cytometry | 5 | 0.46 | 2012 |
| Matching phosphorylation response patterns of antigen-receptor-stimulated T cells via flow cytometry. | 11 | 0.56 | 2012 |
| Multithreaded Algorithms for Maximum Matching in Bipartite Graphs | 5 | 0.43 | 2012 |
| Computing maximum matching in parallel on bipartite graphs: worth the effort? | 2 | 0.41 | 2011 |
| Identifying rare cell populations in comparative flow cytometry | 8 | 0.85 | 2010 |
