Bahare Fatemi

According to our database, Bahare Fatemi authored at least 19 papers between 2016 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

Let Your Graph Do the Talking: Encoding Structured Data for LLMs.

Bryan Perozzi, Bahare Fatemi, Dustin Zelle, Anton Tsitsulin, Seyed Mehran Kazemi, Rami Al-Rfou, Jonathan Halcrow

CoRR, 2024

2023

Geometric deep learning of particle motion by MAGIK.

Bahare Fatemi, Jonathan Halcrow, Khuloud Jaqaman

Nat. Mac. Intell., May, 2023

Knowledge Hypergraph Embedding Meets Relational Algebra.

Bahare Fatemi, Perouz Taslakian, David Vázquez, David Poole

J. Mach. Learn. Res., 2023

Talk like a Graph: Encoding Graphs for Large Language Models.

Bahare Fatemi, Jonathan Halcrow, Bryan Perozzi

CoRR, 2023

TpuGraphs: A Performance Prediction Dataset on Large Tensor Computational Graphs.

Phitchaya Mangpo Phothilimthana, Sami Abu-El-Haija, Kaidi Cao, Bahare Fatemi, Charith Mendis, Bryan Perozzi

CoRR, 2023

UGSL: A Unified Framework for Benchmarking Graph Structure Learning.

Bahare Fatemi, Sami Abu-El-Haija, Anton Tsitsulin, Seyed Mehran Kazemi, Dustin Zelle, Neslihan Bulut, Jonathan Halcrow, Bryan Perozzi

CoRR, 2023

Learning to Substitute Ingredients in Recipes.

Bahare Fatemi, Quentin Duval, Rohit Girdhar, Michal Drozdzal, Adriana Romero-Soriano

CoRR, 2023

SubMix: Learning to Mix Graph Sampling Heuristics.

Sami Abu-El-Haija, Joshua V. Dillon, Bahare Fatemi, Kyriakos Axiotis, Neslihan Bulut, Johannes Gasteiger, Bryan Perozzi, MohammadHossein Bateni

Proceedings of the Uncertainty in Artificial Intelligence, 2023

TpuGraphs: A Performance Prediction Dataset on Large Tensor Computational Graphs.

Mangpo Mangpo Phothilimthana, Sami Abu-El-Haija, Kaidi Cao, Bahare Fatemi, Michael Burrows, Charith Mendis, Bryan Perozzi

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

19th International Workshop on Mining and Learning with Graphs (MLG).

Neil Shah, Shobeir Fakhraei, Da Zheng, Bahare Fatemi, Leman Akoglu

Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2023

2022

Using Graph Algorithms to Pretrain Graph Completion Transformers.

Jonathan Pilault, Michael Galkin, Bahare Fatemi, Perouz Taslakian, David Vázquez, Christopher Pal

CoRR, 2022

2021

Structure learning for relational logistic regression: an ensemble approach.

Nandini Ramanan, Gautam Kunapuli, Tushar Khot, Bahare Fatemi, Seyed Mehran Kazemi, David Poole, Kristian Kersting, Sriraam Natarajan

Data Min. Knowl. Discov., 2021

SLAPS: Self-Supervision Improves Structure Learning for Graph Neural Networks.

Bahare Fatemi, Layla El Asri, Seyed Mehran Kazemi

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

2020

Knowledge Hypergraphs: Prediction Beyond Binary Relations.

Bahare Fatemi, Perouz Taslakian, David Vázquez, David Poole

Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence, 2020

2019

Knowledge Hypergraphs: Extending Knowledge Graphs Beyond Binary Relations.

Bahare Fatemi, Perouz Taslakian, David Vázquez, David Poole

CoRR, 2019

Improved Knowledge Graph Embedding Using Background Taxonomic Information.

Bahare Fatemi, Siamak Ravanbakhsh, David Poole

Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019

2018

Record Linkage to Match Customer Names: A Probabilistic Approach.

Bahare Fatemi, Seyed Mehran Kazemi, David Poole

CoRR, 2018

2017

Comparing Aggregators for Relational Probabilistic Models.

Seyed Mehran Kazemi, Bahare Fatemi, Alexandra Kim, Zilun Peng, Moumita Roy Tora, Xing Zeng, Matthew C. Dirks, David Poole

CoRR, 2017

2016

A Learning Algorithm for Relational Logistic Regression: Preliminary Results.

Bahare Fatemi, Seyed Mehran Kazemi, David Poole

CoRR, 2016