Analog compressed sensing for RF propagation channel sounding. - Jonathan I. Tamir; Theodore S. Rappaport; Yonina C. Eldar; Ahsan Aziz (ICASSP, 2012)

Object Signature Acquisition through Compressive Scanning. - Jonathan I. Tamir; Dan E. Tamir; Shlomi Dolev (OSC, 2012)

Cellular broadband millimeter wave propagation and angle of arrival for adaptive beam steering systems (invited paper). - Theodore S. Rappaport; Yijun Qiao; Jonathan I. Tamir; James Murdock; Eshar Ben-Dor (RWS, 2012)

A 38 GHz cellular outage study for an urban outdoor campus environment. - James Murdock; Eshar Ben-Dor; Yijun Qiao; Jonathan I. Tamir; Theodore S. Rappaport (WCNC, 2012)

Wireless index coding through rank minimization. - Jonathan I. Tamir; Ethan R. Elenberg; Anurag Banerjee; Sriram Vishwanath (ICC, 2014)

Compressive scanning of an object signature. - Jonathan I. Tamir; Dan E. Tamir; Wilhelmus J. Geerts; Shlomi Dolev (Nat. Comput., 2015)

Indigo: A Domain-Specific Language for Fast, Portable Image Reconstruction. - Michael B. Driscoll; Benjamin Brock; Frank Ong; Jonathan I. Tamir; Hsiou-Yuan Liu; Michael Lustig; Armando Fox; Katherine A. Yelick (IPDPS, 2018)

Clinically Deployed Distributed Magnetic Resonance Imaging Reconstruction: Application to Pediatric Knee Imaging. - Michael J. Anderson; Jonathan I. Tamir; Javier S. Turek; Marcus T. Alley; Theodore L. Willke; Shreyas S. Vasanawala; Michael Lustig (CoRR, 2018)

MR Shuffling: Accelerated Single-Scan Multi-Contrast Magnetic Resonance Imaging - Jonathan I. Tamir (2018)

Compressed Sensing MRI Reconstruction on Intel HARPv2. - Yushan Su; Michael Anderson; Jonathan I. Tamir; Michael Lustig; Kai Li 001 (FCCM, 2019)

Memory-efficient Learning for Large-scale Computational Imaging. - Michael R. Kellman; Jonathan I. Tamir; Emrah Bostan; Michael Lustig; Laura Waller (CoRR, 2019)

Memory-efficient Learning for Large-scale Computational Imaging. - Michael R. Kellman; Kevin Zhang 003; Jonathan I. Tamir; Emrah Bostan; Michael Lustig; Laura Waller (CoRR, 2020)

Computational MRI With Physics-Based Constraints: Application to Multicontrast and Quantitative Imaging. - Jonathan I. Tamir; Frank Ong; Suma Anand; Ekin Karasan; Ke Wang; Michael Lustig (IEEE Signal Process. Mag., 2020)

Memory-Efficient Learning for Large-Scale Computational Imaging. - Michael R. Kellman; Kevin Zhang 003; Eric Markley; Jonathan I. Tamir; Emrah Bostan; Michael Lustig; Laura Waller (IEEE Trans. Computational Imaging, 2020)

Hyperbolic graph embedding with enhanced semi-implicit variational inference. - Ali Lotfi-Rezaabad; Rahi Kalantari; Sriram Vishwanath; Mingyuan Zhou; Jonathan I. Tamir (AISTATS, 2021)

Deep J-Sense: Accelerated MRI Reconstruction via Unrolled Alternating Optimization. - Marius Arvinte; Sriram Vishwanath; Ahmed H. Tewfik; Jonathan I. Tamir (MICCAI (6), 2021)

Memory-Efficient Learning for High-Dimensional MRI Reconstruction. - Ke Wang; Michael R. Kellman; Christopher M. Sandino; Kevin Zhang 003; Shreyas S. Vasanawala; Jonathan I. Tamir; Stella X. Yu; Michael Lustig (MICCAI (6), 2021)

Robust Compressed Sensing MRI with Deep Generative Priors. - Ajil Jalal; Marius Arvinte; Giannis Daras; Eric Price 001; Alexandros G. Dimakis; Jonathan I. Tamir (NeurIPS, 2021)

Scan Specific Artifact Reduction in K-space (SPARK) Neural Networks Synergize with Physics-based Reconstruction to Accelerate MRI. - Jonathan I. Tamir; Onur Beker; Heng Yu; Elfar Adalsteinsson; Berkin Bilgic (CoRR, 2021)

eRAKI: Fast Robust Artificial neural networks for K-space Interpolation (RAKI) with Coil Combination and Joint Reconstruction. - Heng Yu; Zijing Dong; Jonathan I. Tamir; Congyu Liao; Kawin Setsompop; Berkin Bilgic (CoRR, 2021)

High Fidelity Deep Learning-based MRI Reconstruction with Instance-wise Discriminative Feature Matching Loss. - Ke Wang; Jonathan I. Tamir; Alfredo De Goyeneche; Uri Wollner; Rafi Brada; Stella X. Yu; Michael Lustig (CoRR, 2021)

Subtle Inverse Crimes: Naïvely training machine learning algorithms could lead to overly-optimistic results. - Efrat Shimron; Jonathan I. Tamir; Ke Wang; Michael Lustig (CoRR, 2021)

Deep Diffusion Models for Robust Channel Estimation. - Marius Arvinte; Jonathan I. Tamir (CoRR, 2021)

FSE Compensated Motion Correction for MRI Using Data Driven Methods. - Brett Levac; Sidharth Kumar; Sofia Kardonik; Jonathan I. Tamir (MICCAI (6), 2022)

Score-Based Generative Models for Robust Channel Estimation. - Marius Arvinte; Jonathan I. Tamir (WCNC, 2022)

Wideband and Entropy-Aware Deep Soft Bit Quantization. - Marius Arvinte; Jonathan I. Tamir (WCNC, 2022)

Few-Max: Few-Shot Domain Adaptation for Unsupervised Contrastive Representation Learning. - Ali Lotfi-Rezaabad; Sidharth Kumar; Sriram Vishwanath; Jonathan I. Tamir (CoRR, 2022)

High-fidelity Direct Contrast Synthesis from Magnetic Resonance Fingerprinting. - Ke Wang; Mariya Doneva; Jakob Meineke; Thomas Amthor; Ekin Karasan; Fei Tan 003; Jonathan I. Tamir; Stella X. Yu; Michael Lustig (CoRR, 2022)

Joint high-dimensional soft bit estimation and quantization using deep learning. - Marius Arvinte; Sriram Vishwanath; Ahmed H. Tewfik; Jonathan I. Tamir (EURASIP J. Wirel. Commun. Netw., 2022)

Solving Inverse Problems with Score-Based Generative Priors learned from Noisy Data. - Asad Aali; Marius Arvinte; Sidharth Kumar; Jonathan I. Tamir (ACSSC, 2023)

MRI Reconstruction with Side Information using Diffusion Models. - Brett Levac; Ajil Jalal; Kannan Ramchandran; Jonathan I. Tamir (ACSSC, 2023)

Accelerated Motion Correction for MRI Using Score-Based Generative Models. - Brett Levac; Ajil Jalal; Jonathan I. Tamir (ISBI, 2023)

Zero-Shot Self-Supervised Joint Temporal Image and Sensitivity Map Reconstruction via Linear Latent Space. - Molin Zhang; Junshen Xu; Jonathan I. Tamir; Elfar Adalsteinsson (MIDL, 2023)

Optimizing Sampling Patterns for Compressed Sensing MRI with Diffusion Generative Models. - Sriram Ravula; Brett Levac; Ajil Jalal; Jonathan I. Tamir; Alexandros G. Dimakis (CoRR, 2023)

SubZero: Subspace Zero-Shot MRI Reconstruction. - Heng Yu; Jonathan I. Tamir; Berkin Bilgic (CoRR, 2023)

MIMO Channel Estimation Using Score-Based Generative Models. - Marius Arvinte; Jonathan I. Tamir (IEEE Trans. Wirel. Commun., 2023)

INFusion: Diffusion Regularized Implicit Neural Representations for 2D and 3D Accelerated MRI Reconstruction. - Yamin Ishraq Arefeen; Brett Levac; Zach Stoebner; Jonathan I. Tamir (IEEECONF, 2024)

Institute for Foundations of Machine Learning (IFML): Advancing AI systems that will transform our world. - Adam R. Klivans; Alexandros G. Dimakis; Kristen Grauman; Jonathan I. Tamir; Daniel Jesus Diaz; Karen Davidson (AI Mag., 2024)

Evaluating Neural Networks for Early Maritime Threat Detection. - Dhanush Tella; Chandra Teja Tiriveedhi; Naphtali Rishe; Dan E. Tamir; Jonathan I. Tamir (CoRR, 2024)

Accelerated, Robust Lower-Field Neonatal MRI with Generative Models. - Yamin Ishraq Arefeen; Brett Levac; Jonathan I. Tamir (CoRR, 2024)

Enhancing Deep Learning-Driven Multi-Coil MRI Reconstruction via Self-Supervised Denoising. - Asad Aali; Marius Arvinte; Sidharth Kumar; Yamin Ishraq Arefeen; Jonathan I. Tamir (CoRR, 2024)

Differentiable Rendering for Synthetic Aperture Radar Imagery. - Michael Wilmanski; Jonathan I. Tamir (IEEE Trans. Aerosp. Electron. Syst., 2024)

Polynomial Preconditioners for Regularized Linear Inverse Problems. - Siddharth Srinivasan Iyer; Frank Ong; Xiaozhi Cao; Congyu Liao; Luca Daniel; Jonathan I. Tamir; Kawin Setsompop (SIAM J. Imaging Sci., 2024)

Ambient Diffusion Posterior Sampling: Solving Inverse Problems with Diffusion Models Trained on Corrupted Data. - Asad Aali; Giannis Daras; Brett Levac; Sidharth Kumar; Alex Dimakis; Jonathan I. Tamir (ICLR, 2025)

Double Blind Imaging with Generative Modeling. - Brett Levac; Ajil Jalal; Kannan Ramchandran; Jonathan I. Tamir (CoRR, 2025)

Non-rigid Motion Correction for MRI Reconstruction via Coarse-To-Fine Diffusion Models. - Frederic Wang; Jonathan I. Tamir (CoRR, 2025)

Diffusion Probabilistic Generative Models for Accelerated, in-NICU Permanent Magnet Neonatal MRI. - Yamin Ishraq Arefeen; Brett Levac; Bhairav Patel; Chang Ho; Jonathan I. Tamir (CoRR, 2025)