Joint adaptive modulation-coding and cooperative ARQ for wireless relay networks. - Morteza Mardani; Jalil S. Harsini; Farshad Lahouti; Behrouz Eliasi (ISWCS, 2008)

Cross-Layer Link Adaptation Design for Relay Channels with Cooperative ARQ Protocol - Morteza Mardani; Jalil S. Harsini; Farshad Lahouti (CoRR, 2008)

Joint Adaptive Modulation Coding and Cooperative ARQ over Relay Channels-Applications to Land Mobile Satellite Communications - Morteza Mardani; Jalil S. Harsini; Farshad Lahouti; Behrouz Eliasi (CoRR, 2008)

Unveiling anomalies in large-scale networks via sparsity and low rank. - Morteza Mardani; Gonzalo Mateos; Georgios B. Giannakis (ACSCC, 2011)

Link-Adaptive and QoS-Provisioning Cooperative ARQ - Applications to Relay-Assisted Land Mobile Satellite Communications. - Morteza Mardani; Jalil Seifali Harsini; Farshad Lahouti; Behrouz Eliasi (IEEE Trans. Veh. Technol., 2011)

Distributed nuclear norm minimization for matrix completion. - Morteza Mardani; Gonzalo Mateos; Georgios B. Giannakis (SPAWC, 2012)

Exact recovery of low-rank plus compressed sparse matrices. - Morteza Mardani; Gonzalo Mateos; Georgios B. Giannakis (SSP, 2012)

In-network Sparsity-regularized Rank Minimization: Algorithms and Applications - Morteza Mardani; Gonzalo Mateos; Georgios B. Giannakis (CoRR, 2012)

Cross-Layer Design of Wireless Multihop Random Access Networks. - Morteza Mardani; Seung-Jun Kim 002; Georgios B. Giannakis (IEEE Trans. Signal Process., 2012)

Robust tomography via network traffic maps leveraging sparsity and low rank. - Morteza Mardani; Georgios B. Giannakis (GlobalSIP, 2013)

Robust network traffic estimation via sparsity and low rank. - Morteza Mardani; Georgios B. Giannakis (ICASSP, 2013)

Rank minimization for subspace tracking from incomplete data. - Morteza Mardani; Gonzalo Mateos; Georgios B. Giannakis (ICASSP, 2013)

Dynamic Anomalography: Tracking Network Anomalies Via Sparsity and Low Rank. - Morteza Mardani; Gonzalo Mateos; Georgios B. Giannakis (IEEE J. Sel. Top. Signal Process., 2013)

Recovery of Low-Rank Plus Compressed Sparse Matrices With Application to Unveiling Traffic Anomalies. - Morteza Mardani; Gonzalo Mateos; Georgios B. Giannakis (IEEE Trans. Inf. Theory, 2013)

Decentralized Sparsity-Regularized Rank Minimization: Algorithms and Applications. - Morteza Mardani; Gonzalo Mateos; Georgios B. Giannakis (IEEE Trans. Signal Process., 2013)

Classification of streaming big data with misses. - Fatemeh Sheikholeslami; Morteza Mardani; Georgios B. Giannakis (ACSSC, 2014)

Imputation of streaming low-rank tensor data. - Morteza Mardani; Gonzalo Mateos; Georgios B. Giannakis (SAM, 2014)

Online sketching of big categorical data with absent features. - Yanning Shen; Morteza Mardani; Georgios B. Giannakis (CISS, 2015)

Online sketching for big data subspace learning. - Morteza Mardani; Georgios B. Giannakis (EUSIPCO, 2015)

Subspace Learning and Imputation for Streaming Big Data Matrices and Tensors. - Morteza Mardani; Gonzalo Mateos; Georgios B. Giannakis (IEEE Trans. Signal Process., 2015)

Tracking Tensor Subspaces with Informative Random Sampling for Real-Time MR Imaging. - Morteza Mardani; Georgios B. Giannakis; Kâmil Ugurbil (CoRR, 2016)

Estimating Traffic and Anomaly Maps via Network Tomography. - Morteza Mardani; Georgios B. Giannakis (IEEE/ACM Trans. Netw., 2016)

Recurrent generative adversarial neural networks for compressive imaging. - Morteza Mardani; Enhao Gong; Joseph Y. Cheng; John M. Pauly; Lei Xing 001 (CAMSAP, 2017)

Deep Generative Adversarial Networks for Compressed Sensing Automates MRI. - Morteza Mardani; Enhao Gong; Joseph Y. Cheng; Shreyas Vasanawala; Greg Zaharchuk; Marcus T. Alley; Neil Thakur; Song Han 003; William J. Dally; John M. Pauly; Lei Xing 001 (CoRR, 2017)

Recurrent Generative Adversarial Networks for Proximal Learning and Automated Compressive Image Recovery. - Morteza Mardani; Hatef Monajemi; Vardan Papyan; Shreyas Vasanawala; David L. Donoho; John M. Pauly (CoRR, 2017)

Online Categorical Subspace Learning for Sketching Big Data with Misses. - Yanning Shen; Morteza Mardani; Georgios B. Giannakis (IEEE Trans. Signal Process., 2017)

Neural Proximal Gradient Descent for Compressive Imaging. - Morteza Mardani; Qingyun Sun; David L. Donoho; Vardan Papyan; Hatef Monajemi; Shreyas Vasanawala; John M. Pauly (NeurIPS, 2018)

VAE-GANs for Probabilistic Compressive Image Recovery: Uncertainty Analysis. - Vineet Edupuganti; Morteza Mardani; Joseph Y. Cheng; Shreyas Vasanawala; John M. Pauly (CoRR, 2019)

Compressed Sensing: From Research to Clinical Practice with Data-Driven Learning. - Joseph Y. Cheng; Feiyu Chen 004; Christopher M. Sandino; Morteza Mardani; John M. Pauly; Shreyas S. Vasanawala (CoRR, 2019)

Degrees of Freedom Analysis of Unrolled Neural Networks. - Morteza Mardani; Qingyun Sun; Vardan Papyan; Shreyas Vasanawala; John M. Pauly; David L. Donoho (CoRR, 2019)

Deep Generative Adversarial Neural Networks for Compressive Sensing MRI. - Morteza Mardani; Enhao Gong; Joseph Y. Cheng; Shreyas S. Vasanawala; Greg Zaharchuk; Lei Xing 001; John M. Pauly (IEEE Trans. Medical Imaging, 2019)

Multi-scale Unrolled Deep Learning Framework for Accelerated Magnetic Resonance Imaging. - Ukash Nakarmi; Joseph Y. Cheng; Edgar P. Rios; Morteza Mardani; John M. Pauly; Leslie Ying; Shreyas S. Vasanawala (ISBI, 2020)

Neural FFTs for Universal Texture Image Synthesis. - Morteza Mardani; Guilin Liu; Aysegul Dundar; Shiqiu Liu; Andrew Tao; Bryan Catanzaro (NeurIPS, 2020)

Spectral Decomposition in Deep Networks for Segmentation of Dynamic Medical Images. - Edgar A. Rios Piedra; Morteza Mardani; Frank Ong; Ukash Nakarmi; Joseph Y. Cheng; Shreyas Vasanawala (CoRR, 2020)

Compressed Sensing: From Research to Clinical Practice With Deep Neural Networks: Shortening Scan Times for Magnetic Resonance Imaging. - Christopher M. Sandino; Joseph Y. Cheng; Feiyu Chen 004; Morteza Mardani; John M. Pauly; Shreyas S. Vasanawala (IEEE Signal Process. Mag., 2020)

Convex Regularization behind Neural Reconstruction. - Arda Sahiner; Morteza Mardani; Batu Ozturkler; Mert Pilanci; John M. Pauly (ICLR, 2021)

Adaptive Fourier Neural Operators: Efficient Token Mixers for Transformers. - John Guibas; Morteza Mardani; Zongyi Li; Andrew Tao; Anima Anandkumar; Bryan Catanzaro (CoRR, 2021)

Uncertainty Quantification in Deep MRI Reconstruction. - Vineet Edupuganti; Morteza Mardani; Shreyas Vasanawala; John M. Pauly (IEEE Trans. Medical Imaging, 2021)

Wasserstein GANs for MR Imaging: From Paired to Unpaired Training. - Ke Lei; Morteza Mardani; John M. Pauly; Shreyas S. Vasanawala (IEEE Trans. Medical Imaging, 2021)

Demystifying Batch Normalization in ReLU Networks: Equivalent Convex Optimization Models and Implicit Regularization. - Tolga Ergen; Arda Sahiner; Batu Ozturkler; John M. Pauly; Morteza Mardani; Mert Pilanci (ICLR, 2022)

Efficient Token Mixing for Transformers via Adaptive Fourier Neural Operators. - John Guibas; Morteza Mardani; Zongyi Li; Andrew Tao; Anima Anandkumar; Bryan Catanzaro (ICLR, 2022)

Hidden Convexity of Wasserstein GANs: Interpretable Generative Models with Closed-Form Solutions. - Arda Sahiner; Tolga Ergen; Batu Ozturkler; Burak Bartan; John M. Pauly; Morteza Mardani; Mert Pilanci (ICLR, 2022)

Unraveling Attention via Convex Duality: Analysis and Interpretations of Vision Transformers. - Arda Sahiner; Tolga Ergen; Batu Ozturkler; John M. Pauly; Morteza Mardani; Mert Pilanci (ICML, 2022)

FourCastNet: A Global Data-driven High-resolution Weather Model using Adaptive Fourier Neural Operators. - Jaideep Pathak; Shashank Subramanian; Peter Harrington; Sanjeev Raja; Ashesh Chattopadhyay; Morteza Mardani; Thorsten Kurth; David Hall; Zongyi Li; Kamyar Azizzadenesheli; Pedram Hassanzadeh; Karthik Kashinath; et al. (CoRR, 2022)

GLEAM: Greedy Learning for Large-Scale Accelerated MRI Reconstruction. - Batu Ozturkler; Arda Sahiner; Tolga Ergen; Arjun D. Desai; Christopher M. Sandino; Shreyas Vasanawala; John M. Pauly; Morteza Mardani; Mert Pilanci (CoRR, 2022)

Pseudoinverse-Guided Diffusion Models for Inverse Problems. - Jiaming Song; Arash Vahdat; Morteza Mardani; Jan Kautz (ICLR, 2023)

Loss-Guided Diffusion Models for Plug-and-Play Controllable Generation. - Jiaming Song; Qinsheng Zhang; Hongxu Yin; Morteza Mardani; Ming-Yu Liu 001; Jan Kautz; Yongxin Chen; Arash Vahdat (ICML, 2023)

SMRD: SURE-Based Robust MRI Reconstruction with Diffusion Models. - Batu Ozturkler; Chao Liu 064; Benjamin Eckart; Morteza Mardani; Jiaming Song; Jan Kautz (MICCAI (3), 2023)

FourCastNet: Accelerating Global High-Resolution Weather Forecasting Using Adaptive Fourier Neural Operators. - Thorsten Kurth; Shashank Subramanian; Peter Harrington; Jaideep Pathak; Morteza Mardani; David Hall; Andrea Miele; Karthik Kashinath; Anima Anandkumar (PASC, 2023)

Multiscale Attention via Wavelet Neural Operators for Vision Transformers. - Anahita Nekoozadeh; Mohammad Reza Ahmadzadeh; Zahra Mardani; Morteza Mardani (CoRR, 2023)

Generative Residual Diffusion Modeling for Km-scale Atmospheric Downscaling. - Morteza Mardani; Noah D. Brenowitz; Yair Cohen; Jaideep Pathak; Chieh-Yu Chen; Cheng-Chin Liu; Arash Vahdat; Karthik Kashinath; Jan Kautz; Mike Pritchard (CoRR, 2023)

Compositional Text-to-Image Generation with Feedforward Layout Generation. - Sifei Liu; Weili Nie; An-Chieh Cheng; Morteza Mardani; Chao Liu 064; Benjamin Eckart; Arash Vahdat (ECCV Workshops (11), 2024)

A Variational Perspective on Solving Inverse Problems with Diffusion Models. - Morteza Mardani; Jiaming Song; Jan Kautz; Arash Vahdat (ICLR, 2024)

Scaling Convex Neural Networks with Burer-Monteiro Factorization. - Arda Sahiner; Tolga Ergen; Batu Ozturkler; John M. Pauly; Morteza Mardani; Mert Pilanci (ICLR, 2024)

Compositional Text-to-Image Generation with Dense Blob Representations. - Weili Nie; Sifei Liu; Morteza Mardani; Chao Liu 064; Benjamin Eckart; Arash Vahdat (ICML, 2024)

Warped Diffusion: Solving Video Inverse Problems with Image Diffusion Models. - Giannis Daras; Weili Nie; Karsten Kreis; Alex Dimakis; Morteza Mardani; Nikola B. Kovachki; Arash Vahdat (NeurIPS, 2024)

BlobGEN-3D: Compositional 3D-Consistent Freeview Image Generation with 3D Blobs. - Chao Liu 064; Weili Nie; Sifei Liu; Abhishek Badki; Hang Su 005; Morteza Mardani; Benjamin Eckart; Arash Vahdat (SIGGRAPH Asia, 2024)

DiffObs: Generative Diffusion for Global Forecasting of Satellite Observations. - Jason Stock; Jaideep Pathak; Yair Cohen; Mike Pritchard; Piyush Garg; Dale R. Durran; Morteza Mardani; Noah D. Brenowitz (CoRR, 2024)

Repulsive Score Distillation for Diverse Sampling of Diffusion Models. - Nicolas Zilberstein; Morteza Mardani; Santiago Segarra (CoRR, 2024)

Generative Data Assimilation of Sparse Weather Station Observations at Kilometer Scales. - Peter Manshausen; Yair Cohen; Jaideep Pathak; Mike Pritchard; Piyush Garg; Morteza Mardani; Karthik Kashinath; Simon Byrne; Noah D. Brenowitz (CoRR, 2024)

Kilometer-Scale Convection Allowing Model Emulation using Generative Diffusion Modeling. - Jaideep Pathak; Yair Cohen; Piyush Garg; Peter Harrington; Noah D. Brenowitz; Dale R. Durran; Morteza Mardani; Arash Vahdat; Shaoming Xu; Karthik Kashinath; Michael S. Pritchard (CoRR, 2024)

Stochastic Flow Matching for Resolving Small-Scale Physics. - Stathi Fotiadis; Noah D. Brenowitz; Tomas Geffner; Yair Cohen; Michael S. Pritchard; Arash Vahdat; Morteza Mardani (CoRR, 2024)

AGG: Amortized Generative 3D Gaussians for Single Image to 3D. - Dejia Xu; Ye Yuan 012; Morteza Mardani; Sifei Liu; Jiaming Song; Zhangyang Wang; Arash Vahdat (Trans. Mach. Learn. Res., 2024)

Heavy-Tailed Diffusion Models. - Kushagra Pandey; Jaideep Pathak; Yilun Xu; Stephan Mandt; Michael S. Pritchard; Arash Vahdat; Morteza Mardani (ICLR, 2025)

Repulsive Latent Score Distillation for Solving Inverse Problems. - Nicolas Zilberstein; Morteza Mardani; Santiago Segarra (ICLR, 2025)

AutoSamp: Autoencoding k-Space Sampling via Variational Information Maximization for 3D MRI. - Cagan Alkan; Morteza Mardani; Congyu Liao; Zhitao Li 004; Shreyas S. Vasanawala; John M. Pauly (IEEE Trans. Medical Imaging, 2025)

Test-Time Scaling of Diffusion Models via Noise Trajectory Search. - Vignav Ramesh; Morteza Mardani (CoRR, 2025)

Elucidated Rolling Diffusion Models for Probabilistic Weather Forecasting. - Salva Rühling Cachay; Miika Aittala; Karsten Kreis; Noah D. Brenowitz; Arash Vahdat; Morteza Mardani; Rose Yu (CoRR, 2025)