A digraph fourier transform with spread frequency components. - Rasoul Shafipour; Ali Khodabakhsh 002; Gonzalo Mateos; Evdokia Nikolova (GlobalSIP, 2017)

Network topology inference from non-stationary graph signals. - Rasoul Shafipour; Santiago Segarra; Antonio G. Marques; Gonzalo Mateos (ICASSP, 2017)

Closing the Knowledge Gap in an Online Learning Community: Network-Analytic Discoveries, Simulation and Prediction. - Rasoul Shafipour; Raiyan Abdul Baten; Md. Kamrul Hasan 003; Gourab Ghoshal; Gonzalo Mateos; Mohammed E. Hoque 001 (CoRR, 2017)

Spread and Sparse: Learning Interpretable Transforms for Bandlimited Signals on Directed Graphs. - Rasoul Shafipour; Gonzalo Mateos (ACSSC, 2018)

Directed Network Topology Inference via Graph Filter Identification. - Rasoul Shafipour; Santiago Segarra; Antonio G. Marques; Gonzalo Mateos (DSW, 2018)

Blind Identification of Invertible Graph Filters with Multiple Sparse Inputs. - Chang Ye; Rasoul Shafipour; Gonzalo Mateos (EUSIPCO, 2018)

A Novel Scheme for Support Identification and Iterative Sampling of Bandlimited Graph Signals. - Abolfazl Hashemi; Rasoul Shafipour; Haris Vikalo; Gonzalo Mateos (GlobalSIP, 2018)

Sampling and Reconstruction of Graph Signals via Weak Submodularity and Semidefinite Relaxation. - Abolfazl Hashemi; Rasoul Shafipour; Haris Vikalo; Gonzalo Mateos (ICASSP, 2018)

Digraph Fourier Transform via Spectral Dispersion Minimization. - Rasoul Shafipour; Ali Khodabakhsh 002; Gonzalo Mateos; Evdokia Nikolova (ICASSP, 2018)

Identifying Undirected Network Structure via Semidefinite Relaxation. - Rasoul Shafipour; Santiago Segarra; Antonio G. Marques; Gonzalo Mateos (ICASSP, 2018)

Identifying the Topology of Undirected Networks from Diffused Non-stationary Graph Signals. - Rasoul Shafipour; Santiago Segarra; Antonio G. Marques; Gonzalo Mateos (CoRR, 2018)

Online Network Topology Inference with Partial Connectivity Informatio. - Rasoul Shafipour; Gonzalo Mateos (CAMSAP, 2019)

Online Topology Inference from Streaming Stationary Graph Signals. - Rasoul Shafipour; Abolfazl Hashemi; Gonzalo Mateos; Haris Vikalo (DSW, 2019)

Mapping Brain Structural Connectivities to Functional Networks Via Graph Encoder-Decoder With Interpretable Latent Embeddings. - Yang Li 149; Rasoul Shafipour; Gonzalo Mateos; Zhengwu Zhang (GlobalSIP, 2019)

A Windowed Digraph Fourier Transform. - Rasoul Shafipour; Ali Khodabakhsh 002; Gonzalo Mateos (ICASSP, 2019)

A Directed Graph Fourier Transform With Spread Frequency Components. - Rasoul Shafipour; Ali Khodabakhsh 002; Gonzalo Mateos; Evdokia Nikolova (IEEE Trans. Signal Process., 2019)

Online proximal gradient for learning graphs from streaming signals. - Rasoul Shafipour; Gonzalo Mateos (EUSIPCO, 2020)

Supervised Graph Representation Learning for Modeling the Relationship between Structural and Functional Brain Connectivity. - Yang Li 149; Rasoul Shafipour; Gonzalo Mateos; Zhengwu Zhang (ICASSP, 2020)

Online Topology Inference from Streaming Stationary Graph Signals with Partial Connectivity Information. - Rasoul Shafipour; Gonzalo Mateos (Algorithms, 2020)

Non-Local Feature Aggregation on Graphs via Latent Fixed Data Structures. - Mostafa Rahmani; Rasoul Shafipour; Ping Li 001 (ACSCC, 2021)

Towards accelerated greedy sampling and reconstruction of bandlimited graph signals. - Abolfazl Hashemi; Rasoul Shafipour; Haris Vikalo; Gonzalo Mateos (Signal Process., 2022)

With Shared Microexponents, A Little Shifting Goes a Long Way. - Bita Darvish Rouhani; Ritchie Zhao; Venmugil Elango; Rasoul Shafipour; Mathew Hall; Maral Mesmakhosroshahi; Ankit More; Levi Melnick; Maximilian Golub; Girish Varatkar; Lai Shao; Gaurav Kolhe; et al. (ISCA, 2023)

Shared Microexponents: A Little Shifting Goes a Long Way. - Bita Rouhani; Ritchie Zhao; Venmugil Elango; Rasoul Shafipour; Mathew Hall; Maral Mesmakhosroshahi; Ankit More; Levi Melnick; Maximilian Golub; Girish Varatkar; Lei Shao; Gaurav Kolhe; et al. (CoRR, 2023)

Microscaling Data Formats for Deep Learning. - Bita Darvish Rouhani; Ritchie Zhao; Ankit More; Mathew Hall; Alireza Khodamoradi; Summer Deng; Dhruv Choudhary; Marius Cornea; Eric Dellinger; Kristof Denolf; Dusan Stosic; Venmugil Elango; et al. (CoRR, 2023)

SeedLM: Compressing LLM Weights into Seeds of Pseudo-Random Generators. - Rasoul Shafipour; David Harrison; Maxwell Horton; Jeffrey Marker; Houman Bedayat; Sachin Mehta; Mohammad Rastegari; Mahyar Najibi; Saman Naderiparizi (ICLR, 2025)