Marius: Learning Massive Graph Embeddings on a Single Machine. - Jason Mohoney; Roger Waleffe; Henry Xu; Theodoros Rekatsinas; Shivaram Venkataraman (OSDI, 2021)

Learning Massive Graph Embeddings on a Single Machine. - Jason Mohoney; Roger Waleffe; Yiheng Xu; Theodoros Rekatsinas; Shivaram Venkataraman (CoRR, 2021)

Demonstration of Marius: Graph Embeddings with a Single Machine. - Anders Carlsson; Anze Xie; Jason Mohoney; Roger Waleffe; Shanan Peters; Theodoros Rekatsinas; Shivaram Venkataraman (Proc. VLDB Endow., 2021)

Marius++: Large-Scale Training of Graph Neural Networks on a Single Machine. - Roger Waleffe; Jason Mohoney; Theodoros Rekatsinas; Shivaram Venkataraman (CoRR, 2022)

MariusGNN: Resource-Efficient Out-of-Core Training of Graph Neural Networks. - Roger Waleffe; Jason Mohoney; Theodoros Rekatsinas; Shivaram Venkataraman (EuroSys, 2023)

Fact Ranking over Large-Scale Knowledge Graphs with Reasoning Embedding Models. - Hongyu Ren; Ali Mousavi 003; Anil Pacaci; Shihabur Rahman Chowdhury; Jason Mohoney; Ihab F. Ilyas; Yunyao Li 001; Theodoros Rekatsinas (IEEE Data Eng. Bull., 2023)

High-Throughput Vector Similarity Search in Knowledge Graphs. - Jason Mohoney; Anil Pacaci; Shihabur Rahman Chowdhury; Ali Mousavi 003; Ihab F. Ilyas; Umar Farooq Minhas; Jeffrey Pound; Theodoros Rekatsinas (Proc. ACM Manag. Data, 2023)

Incremental IVF Index Maintenance for Streaming Vector Search. - Jason Mohoney; Anil Pacaci; Shihabur Rahman Chowdhury; Umar Farooq Minhas; Jeffrey Pound; Cédric Renggli; Nima Reyhani; Ihab F. Ilyas; Theodoros Rekatsinas; Shivaram Venkataraman (CoRR, 2024)

Quake: Adaptive Indexing for Vector Search. - Jason Mohoney; Devesh Sarda; Mengze Tang; Shihabur Rahman Chowdhury; Anil Pacaci; Ihab F. Ilyas; Theodoros Rekatsinas; Shivaram Venkataraman (OSDI, 2025)

Armada: Memory-Efficient Distributed Training of Large-Scale Graph Neural Networks. - Roger Waleffe; Devesh Sarda; Jason Mohoney; Emmanouil-Vasileios Vlatakis-Gkaragkounis; Theodoros Rekatsinas; Shivaram Venkataraman (CoRR, 2025)