Concrete Autoencoders: Differentiable Feature Selection and Reconstruction. - Muhammed Fatih Balin; Abubakar Abid; James Y. Zou (ICML, 2019)

A scalable graph generation algorithm to sample over a given shell distribution. - M. Yusuf Özkaya; Muhammed Fatih Balin; Ali Pinar; Ümit V. Çatalyürek (IPDPS Workshops, 2020)

On Symmetric Rectilinear Matrix Partitioning. - Abdurrahman Yasar; Muhammed Fatih Balin; Xiaojing An; Kaan Sancak; Ümit V. Çatalyürek (CoRR, 2020)

MG-GCN: A Scalable multi-GPU GCN Training Framework. - Muhammed Fatih Balin; Kaan Sancak; Ümit V. Çatalyürek (ICPP, 2022)

(LA)yer-neigh(BOR) Sampling: Defusing Neighborhood Explosion in GNNs. - Muhammed Fatih Balin; Ümit V. Çatalyürek (CoRR, 2022)

On Symmetric Rectilinear Partitioning. - Abdurrahman Yasar; Muhammed Fatih Balin; Xiaojing An; Kaan Sancak; Ümit V. Çatalyürek (ACM J. Exp. Algorithmics, 2022)

Layer-Neighbor Sampling - Defusing Neighborhood Explosion in GNNs. - Muhammed Fatih Balin; Ümit V. Çatalyürek (NeurIPS, 2023)

SGORP: A Subgradient-based Method for d-Dimensional Rectilinear Partitioning. - Muhammed Fatih Balin; Xiaojing An; Abdurrahman Yasar; Ümit V. Çatalyürek (CoRR, 2023)

Do We Really Need Complicated Graph Learning Models? - A Simple but Effective Baseline. - Kaan Sancak; Muhammed Fatih Balin; Ümit V. Çatalyürek (LoG, 2024)

A Scalable and Effective Alternative to Graph Transformers. - Kaan Sancak; Zhigang Hua; Jin Fang; Yan Xie; Andrey Malevich; Bo Long; Muhammed Fatih Balin; Ümit V. Çatalyürek (AAAI, 2025)

Cooperative Minibatching in Graph Neural Networks. - Muhammed Fatih Balin; Dominique LaSalle; Ümit V. Çatalyürek (Trans. Mach. Learn. Res., 2025)