Cell Broadband Engine processor performance optimization: Tracing tools implementation and use. - Marina Biberstein; Shiri Dori-Hacohen; Yuval Harel; Andre Heilper; Bilha Mendelson; Uzi Shvadron; Eran Treister; Javier Turek; Moon S. Chang (IBM J. Res. Dev., 2009)

Square and stretch multigrid for stochastic matrix eigenproblems. - Eran Treister; Irad Yavneh (Numer. Linear Algebra Appl., 2010)

Fast multilevel methods for Markov chains. - Hans De Sterck; Killian Miller; Eran Treister; Irad Yavneh (Numer. Linear Algebra Appl., 2011)

On-the-Fly Adaptive Smoothed Aggregation Multigrid for Markov Chains. - Eran Treister; Irad Yavneh (SIAM J. Sci. Comput., 2011)

A Multilevel Iterated-Shrinkage Approach to l1 Penalized Least-Squares Minimization. - Eran Treister; Irad Yavneh (IEEE Trans. Signal Process., 2012)

A Block-Coordinate Descent Approach for Large-scale Sparse Inverse Covariance Estimation. - Eran Treister; Javier Turek (NIPS, 2014)

Aggregation-based adaptive algebraic multigrid for sparse linear systems. - Eran Treister (2014)

Non-Galerkin Multigrid Based on Sparsified Smoothed Aggregation. - Eran Treister; Irad Yavneh (SIAM J. Sci. Comput., 2015)

A fast marching algorithm for the factored eikonal equation. - Eran Treister; Eldad Haber (J. Comput. Phys., 2016)

A Multilevel Framework for Sparse Optimization with Application to Inverse Covariance Estimation and Logistic Regression. - Eran Treister; Javier S. Turek; Irad Yavneh (SIAM J. Sci. Comput., 2016)

jInv-a Flexible Julia Package for PDE Parameter Estimation. - Lars Ruthotto; Eran Treister; Eldad Haber (SIAM J. Sci. Comput., 2017)

Full Waveform Inversion Guided by Travel Time Tomography. - Eran Treister; Eldad Haber (SIAM J. Sci. Comput., 2017)

Low-Cost Parameterizations of Deep Convolution Neural Networks. - Eran Treister; Lars Ruthotto; Michal Sharoni; Sapir Zafrani; Eldad Haber (CoRR, 2018)

Shifted Laplacian multigrid for the elastic Helmholtz equation. - Eran Treister (CoRR, 2018)

IMEXnet A Forward Stable Deep Neural Network. - Eldad Haber; Keegan Lensink; Eran Treister; Lars Ruthotto (ICML, 2019)

LeanResNet: A Low-cost yet Effective Convolutional Residual Networks. - Jonathan Ephrath; Lars Ruthotto; Eldad Haber; Eran Treister (CoRR, 2019)

Multi-modal 3D Shape Reconstruction Under Calibration Uncertainty using Parametric Level Set Methods. - Moshe Eliasof; Andrei Sharf; Eran Treister (CoRR, 2019)

A multigrid solver to the Helmholtz equation with a point source based on travel time and amplitude. - Eran Treister; Eldad Haber (Numer. Linear Algebra Appl., 2019)

DiffGCN: Graph Convolutional Networks via Differential Operators and Algebraic Multigrid Pooling. - Moshe Eliasof; Eran Treister (NeurIPS, 2020)

Multigrid-in-Channels Neural Network Architectures. - Moshe Eliasof; Jonathan Ephrath; Lars Ruthotto; Eran Treister (CoRR, 2020)

LeanConvNets: Low-Cost Yet Effective Convolutional Neural Networks. - Jonathan Ephrath; Moshe Eliasof; Lars Ruthotto; Eldad Haber; Eran Treister (IEEE J. Sel. Top. Signal Process., 2020)

Multimodal 3D Shape Reconstruction under Calibration Uncertainty Using Parametric Level Set Methods. - Moshe Eliasof; Andrei Sharf; Eran Treister (SIAM J. Imaging Sci., 2020)

PDE-GCN: Novel Architectures for Graph Neural Networks Motivated by Partial Differential Equations. - Moshe Eliasof; Eldad Haber; Eran Treister (NeurIPS, 2021)

GradFreeBits: Gradient Free Bit Allocation for Dynamic Low Precision Neural Networks. - Benjamin Bodner; Gil Ben Shalom; Eran Treister (CoRR, 2021)

Quantized convolutional neural networks through the lens of partial differential equations. - Ido Ben-Yair; Gil Ben Shalom; Moshe Eliasof; Eran Treister (CoRR, 2021)

Full Waveform Inversion Using Extended and Simultaneous Sources. - Sagi Buchatsky; Eran Treister (SIAM J. Sci. Comput., 2021)

Searching for N:M Fine-grained Sparsity of Weights and Activations in Neural Networks. - Ruth Akiva-Hochman; Shahaf E. Finder; Javier S. Turek; Eran Treister (ECCV Workshops (7), 2022)

Rethinking Unsupervised Neural Superpixel Segmentation. - Moshe Eliasof; Nir Ben Zikri; Eran Treister (ICIP, 2022)

pathGCN: Learning General Graph Spatial Operators from Paths. - Moshe Eliasof; Eldad Haber; Eran Treister (ICML, 2022)

Wavelet Feature Maps Compression for Image-to-Image CNNs. - Shahaf E. Finder; Yair Zohav; Maor Ashkenazi; Eran Treister (NeurIPS, 2022)

Effective Learning of a GMRF Mixture Model. - Shahaf E. Finder; Eran Treister; Oren Freifeld (IEEE Access, 2022)

Inferring Unfairness and Error from Population Statistics in Binary and Multiclass Classification. - Sivan Sabato; Eran Treister; Elad Yom-Tov (CoRR, 2022)

Unsupervised Image Semantic Segmentation through Superpixels and Graph Neural Networks. - Moshe Eliasof; Nir Ben Zikri; Eran Treister (CoRR, 2022)

ωGNNs: Deep Graph Neural Networks Enhanced by Multiple Propagation Operators. - Moshe Eliasof; Lars Ruthotto; Eran Treister (CoRR, 2022)

Mimetic Neural Networks: A Unified Framework for Protein Design and Folding. - Moshe Eliasof; Tue Boesen; Eldad Haber; Chen Keasar; Eran Treister (Frontiers Bioinform., 2022)

GradFreeBits: Gradient-Free Bit Allocation for Mixed-Precision Neural Networks. - Benjamin Jacob Bodner; Gil Ben Shalom; Eran Treister (Sensors, 2022)

NeRN: Learning Neural Representations for Neural Networks. - Maor Ashkenazi; Zohar Rimon; Ron Vainshtein; Shir Levi; Elad Richardson; Pinchas Mintz; Eran Treister (ICLR, 2023)

Graph Positional Encoding via Random Feature Propagation. - Moshe Eliasof; Fabrizio Frasca; Beatrice Bevilacqua; Eran Treister; Gal Chechik; Haggai Maron (ICML, 2023)

Improving Graph Neural Networks with Learnable Propagation Operators. - Moshe Eliasof; Lars Ruthotto; Eran Treister (ICML, 2023)

Efficient Graph Laplacian Estimation by a Proximal Newton Approach. - Yakov Medvedovsky; Eran Treister; Tirza Routtenberg (CoRR, 2023)

DRIP: Deep Regularizers for Inverse Problems. - Moshe Eliasof; Eldad Haber; Eran Treister (CoRR, 2023)

Multigrid-Augmented Deep Learning for the Helmholtz Equation: Better Scalability with Compact Implicit Layers. - Bar Lerer; Ido Ben-Yair; Eran Treister (CoRR, 2023)

ADR-GNN: Advection-Diffusion-Reaction Graph Neural Networks. - Moshe Eliasof; Eldad Haber; Eran Treister (CoRR, 2023)

Multigrid-Augmented Deep Learning Preconditioners for the Helmholtz Equation. - Yael Azulay; Eran Treister (SIAM J. Sci. Comput., 2023)

MGIC: Multigrid-in-Channels Neural Network Architectures. - Moshe Eliasof; Jonathan Ephrath; Lars Ruthotto; Eran Treister (SIAM J. Sci. Comput., 2023)

Feature Transportation Improves Graph Neural Networks. - Moshe Eliasof; Eldad Haber; Eran Treister (AAAI, 2024)

On The Temporal Domain of Differential Equation Inspired Graph Neural Networks. - Moshe Eliasof; Eldad Haber; Eran Treister; Carola-Bibiane Schönlieb (AISTATS, 2024)

Efficient Graph Laplacian Estimation by Proximal Newton. - Yakov Medvedovsky; Eran Treister; Tirza S. Routtenberg (AISTATS, 2024)

Every Node Counts: Improving the Training of Graph Neural Networks on Node Classification. - Moshe Eliasof; Eldad Haber; Eran Treister (ECAI, 2024)

Wavelet Convolutions for Large Receptive Fields. - Shahaf E. Finder; Roy Amoyal; Eran Treister; Oren Freifeld (ECCV (54), 2024)

Towards Croppable Implicit Neural Representations. - Maor Ashkenazi; Eran Treister (NeurIPS, 2024)

An Over Complete Deep Learning Method for Inverse Problems. - Moshe Eliasof; Eldad Haber; Eran Treister (CoRR, 2024)

Physics-guided Full Waveform Inversion using Encoder-Solver Convolutional Neural Networks. - Matan Goren; Eran Treister (CoRR, 2024)

A block-acoustic preconditioner for the elastic Helmholtz equation. - Rachel Yovel; Eran Treister (CoRR, 2024)

The determinant of the Laplacian matrix of a quaternion unit gain graph. - Ivan I. Kyrchei; Eran Treister; Volodymyr O. Pelykh (Discret. Math., 2024)

Global-local graph neural networks for node-classification. - Moshe Eliasof; Eran Treister (Pattern Recognit. Lett., 2024)

Graph Neural Reaction Diffusion Models. - Moshe Eliasof; Eldad Haber; Eran Treister (SIAM J. Sci. Comput., 2024)

Multigrid-Augmented Deep Learning Preconditioners for the Helmholtz Equation Using Compact Implicit Layers. - Bar Lerer; Ido Ben-Yair; Eran Treister (SIAM J. Sci. Comput., 2024)

pISTA: Preconditioned Iterative Soft Thresholding Algorithm for Graphical Lasso. - Gal Shalom; Eran Treister; Irad Yavneh (SIAM J. Sci. Comput., 2024)

LFA-Tuned Matrix-Free Multigrid Method for the Elastic Helmholtz Equation. - Rachel Yovel; Eran Treister (SIAM J. Sci. Comput., 2024)

A hybrid shifted Laplacian multigrid and domain decomposition preconditioner for the elastic Helmholtz equations. - Eran Treister; Rachel Yovel (J. Comput. Phys., 2024)

Haar Wavelet Feature Compression for Quantized Graph Convolutional Networks. - Moshe Eliasof; Benjamin Jacob Bodner; Eran Treister (IEEE Trans. Neural Networks Learn. Syst., 2024)

The immersed boundary method: an accelerated SIMPLE approach for moving bodies. - Rachel Yovel; Eran Treister; Yuri Feldman (CoRR, 2025)

Towards Efficient Training of Graph Neural Networks: A Multiscale Approach. - Eshed Gal; Moshe Eliasof; Carola-Bibiane Schönlieb; Eldad Haber; Eran Treister (CoRR, 2025)

Improving the Effective Receptive Field of Message-Passing Neural Networks. - Shahaf E. Finder; Ron Shapira Weber; Moshe Eliasof; Oren Freifeld; Eran Treister (CoRR, 2025)

Understanding and Improving Laplacian Positional Encodings For Temporal GNNs. - Yaniv Galron; Fabrizio Frasca; Haggai Maron; Eran Treister; Moshe Eliasof (CoRR, 2025)

Zero-Shot Detection of LLM-Generated Code via Approximated Task Conditioning. - Maor Ashkenazi; Ofir Brenner; Tal Furman Shohet; Eran Treister (CoRR, 2025)

The determinant of the adjacency matrix of a quaternion unit gain graph. - Ivan I. Kyrchei; Eran Treister; Volodymyr O. Pelykh (Discret. Math., 2026)