Bryan Perozzi

20 papers · 2013–2025 · 6 conferences · across top CS/AI conferences

Achievements

+10 more ↓

🏃 Academic Marathon (12) 🌉 Interdisciplinary Bridge 🧭 Keyword Pioneer 🌍 Conference Polyglot (6) 🐝 Cross-Pollinator (13)

🐣 Hot Topic Early Bird 🌍 Conference Polyglot (6) 🏃 Academic Marathon (12) 🧬 Topic Evolution 🔬 Deep Specialist (11) 🔥 Unstoppable (5) 🚀 Conference Pioneer 💎 Century Club (20) ⚡ Prolific Year (5) 🗃️ Keyword Collector (60)

Conferences

NIPS (8) ICML (4) ICLR (3) JMLR (2) UAI (2) CONLL (1)

Top co-authors

Sami Abu-El-Haija (8) Bahare Fatemi (6) Anton Tsitsulin (5) John Palowitch (4) Jonathan Halcrow (3) Vahab Mirrokni (3) Greg Ver Steeg (2) Amol Kapoor (2) Dustin Zelle (2) Charith Mendis (2)

Research topics

Differential Privacy (1)

Keywords

graph neural network (11) semi-supervised learning (4) representation learning (4) node classification (3) graph embedding (3) graph representation learning (2) node embedding (2) transfer learning (2) random walk (2) link prediction (1) attention mechanism (1) graph learning (1) knowledge transfer (1) zero-shot learning (1) differential privacy (1) graph clustering (1) graph attention (1) domain adaptation (1) neural network theory (1) theoretical analysis (1)

Papers

Test of Time: A Benchmark for Evaluating LLMs on Temporal Reasoning ICLR 2025 Position: Graph Learning Will Lose Relevance Due To Poor Benchmarks ICML 2025 Best of Both Worlds: Advantages of Hybrid Graph Sequence Models ICML 2025 Text-space Graph Foundation Models: Comprehensive Benchmarks and New Insights NIPS 2024 Understanding Transformer Reasoning Capabilities via Graph Algorithms NIPS 2024 Talk like a Graph: Encoding Graphs for Large Language Models ICLR 2024 SubMix: Learning to Mix Graph Sampling Heuristics UAI 2023 Learning Large Graph Property Prediction via Graph Segment Training NIPS 2023 TpuGraphs: A Performance Prediction Dataset on Large Tensor Computational Graphs NIPS 2023 Graph Generative Model for Benchmarking Graph Neural Networks ICML 2023 Graph Clustering with Graph Neural Networks JMLR 2023 Differentially Private Graph Learning via Sensitivity-Bounded Personalized PageRank NIPS 2022 Machine Learning on Graphs: A Model and Comprehensive Taxonomy JMLR 2022 Zero-shot Transfer Learning within a Heterogeneous Graph via Knowledge Transfer Networks NIPS 2022 Shift-Robust GNNs: Overcoming the Limitations of Localized Graph Training data NIPS 2021 Graph Traversal with Tensor Functionals: A Meta-Algorithm for Scalable Learning ICLR 2021 MixHop: Higher-Order Graph Convolutional Architectures via Sparsified Neighborhood Mixing ICML 2019 N-GCN: Multi-scale Graph Convolution for Semi-supervised Node Classification UAI 2019 Watch Your Step: Learning Node Embeddings via Graph Attention NIPS 2018 Polyglot: Distributed Word Representations for Multilingual NLP CONLL 2013