Maya Bechler-Speicher

According to our database, Maya Bechler-Speicher authored at least 22 papers between 2019 and 2026.

Collaborative distances:

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

2026

Lost in Tokenization: Fundamental Trade-offs in Graph Tokenization for Transformers.

Maya Bechler-Speicher, Gilad Yehudai, Gil Harari, Clayton Sanford, Amir Globerson, Joan Bruna

CoRR, May, 2026

Ex-GraphRAG: Interpretable Evidence Routing for Graph-Augmented LLMs.

Yoav Kor Sade, Arvindh Arun, Rishi Puri, Steffen Staab, Maya Bechler-Speicher

CoRR, May, 2026

Improving LLM Predictions via Inter-Layer Structural Encoders.

Tom Ulanovski, Eyal Blyachman, Maya Bechler-Speicher

CoRR, March, 2026

A Graph Meta-Network for Learning on Kolmogorov-Arnold Networks.

Guy Bar-Shalom, Ami Tavory, Itay Evron, Maya Bechler-Speicher, Ido Guy, Haggai Maron

CoRR, February, 2026

Billion-Scale Graph Foundation Models.

Maya Bechler-Speicher, Yoel Gottlieb, Andrey Isakov, David Abensur, Ami Tavory, Daniel Haimovich, Ido Guy, Udi Weinsberg

CoRR, February, 2026

2025

GraphBench: Next-generation graph learning benchmarking.

Timo Stoll, Chendi Qian, Ben Finkelshtein, Ali Parviz, Darius Weber, Fabrizio Frasca, Hadar Shavit, Antoine Siraudin, Arman Mielke, Marie Anastacio, Erik Müller, Maya Bechler-Speicher, Michael M. Bronstein, Mikhail Galkin, Holger H. Hoos, Mathias Niepert, Bryan Perozzi, Jan Tönshoff, Christopher Morris

CoRR, December, 2025

Graph Mixing Additive Networks.

Maya Bechler-Speicher, Andrea Zerio, Maor Huri, Marie Vibeke Vestergaard, Ran Gilad-Bachrach, Tine Jess, Samir Bhatt, Aleksejs Sazonovs

CoRR, September, 2025

Interpretable Graph Learning Over Sets of Temporally-Sparse Data.

Andrea Zerio, Maya Bechler-Speicher, Maor Huri, Marie Vibeke Vestergaard, Ran Gilad-Bachrach, Tine Jess, Samir Bhatt, Aleksejs Sazonovs

CoRR, May, 2025

Identifying Critical Phases for Disease Onset with Sparse Haematological Biomarkers.

Andrea Zerio, Maya Bechler-Speicher, Tine Jess, Aleksejs Sazonovs

CoRR, March, 2025

Depth-Width tradeoffs in Algorithmic Reasoning of Graph Tasks with Transformers.

Gilad Yehudai, Clayton Sanford, Maya Bechler-Speicher, Orr Fischer, Ran Gilad-Bachrach, Amir Globerson

CoRR, March, 2025

Towards Invariance to Node Identifiers in Graph Neural Networks.

Maya Bechler-Speicher, Moshe Eliasof, Carola-Bibiane Schönlieb, Ran Gilad-Bachrach, Amir Globerson

CoRR, February, 2025

Spectral Graph Neural Networks are Incomplete on Graphs with a Simple Spectrum.

Snir Hordan, Maya Bechler-Speicher, Gur Lifshitz, Nadav Dym

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2025, 2025

Position: Graph Learning Will Lose Relevance Due To Poor Benchmarks.

Maya Bechler-Speicher, Ben Finkelshtein, Fabrizio Frasca, Luis Müller, Jan Tönshoff, Antoine Siraudin, Viktor Zaverkin, Michael M. Bronstein, Mathias Niepert, Bryan Perozzi, Mikhail Galkin, Christopher Morris

Proceedings of the Forty-second International Conference on Machine Learning, 2025

2024

On the Utilization of Unique Node Identifiers in Graph Neural Networks.

Maya Bechler-Speicher, Moshe Eliasof, Carola-Bibiane Schönlieb, Ran Gilad-Bachrach, Amir Globerson

CoRR, 2024

A General Recipe for Contractive Graph Neural Networks - Technical Report.

Maya Bechler-Speicher, Moshe Eliasof

CoRR, 2024

The Intelligible and Effective Graph Neural Additive Networks.

Maya Bechler-Speicher, Amir Globerson, Ran Gilad-Bachrach

CoRR, 2024

The Intelligible and Effective Graph Neural Additive Network.

Maya Bechler-Speicher, Amir Globerson, Ran Gilad-Bachrach

Proceedings of the Advances in Neural Information Processing Systems 37: Annual Conference on Neural Information Processing Systems 2024, 2024

Cayley Graph Propagation.

JJ Wilson, Maya Bechler-Speicher, Petar Velickovic

Proceedings of the Learning on Graphs Conference, 26-29 November 2024, Virtual., 2024

Graph Neural Networks Use Graphs When They Shouldn't.

Maya Bechler-Speicher, Ido Amos, Ran Gilad-Bachrach, Amir Globerson

Proceedings of the Forty-first International Conference on Machine Learning, 2024

TREE-G: Decision Trees Contesting Graph Neural Networks.

Maya Bechler-Speicher, Amir Globerson, Ran Gilad-Bachrach

Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2022

Graph Trees with Attention.

Maya Bechler-Speicher, Amir Globerson, Ran Gilad-Bachrach

CoRR, 2022

2019

A Crossing Lemma for Families of Jordan Curves with a Bounded Intersection Number.

Maya Bechler-Speicher

CoRR, 2019