Locally Low-Rank tensor regularization for high-resolution quantitative dynamic MRI. - Burhaneddin Yaman; Sebastian Weingärtner; Nikolaos Kargas; Nicholas D. Sidiropoulos; Mehmet Akçakaya (CAMSAP, 2017)

Unified outage performance analysis of two-way/one-way full-duplex/half-duplex fixed-gain AF relay systems. - Asil Koç; Ibrahim Altunbas; Burhaneddin Yaman (ICT, 2017)

Dense Recurrent Neural Networks for Inverse Problems: History-Cognizant Unrolling of Optimization Algorithms. - Seyed Amir Hossein Hosseini; Burhaneddin Yaman; Steen Moeller; Mingyi Hong 001; Mehmet Akçakaya (CoRR, 2019)

Self-Supervised Learning of Physics-Based Reconstruction Neural Networks without Fully-Sampled Reference Data. - Burhaneddin Yaman; Seyed Amir Hossein Hosseini; Steen Moeller; Jutta Ellermann; Kâmil Ugurbil; Mehmet Akçakaya (CoRR, 2019)

High-Fidelity Accelerated MRI Reconstruction by Scan-Specific Fine-Tuning of Physics-Based Neural Networks. - Seyed Amir Hossein Hosseini; Burhaneddin Yaman; Steen Moeller; Mehmet Akçakaya (EMBC, 2020)

Scan-Specific Accelerated Mri Reconstruction Using Recurrent Neural Networks In A Regularized Self-Consistent Framework. - Seyed Amir Hossein Hosseini; Burhaneddin Yaman; Chi Zhang 057; Kâmil Ugurbil; Steen Moeller; Mehmet Akçakaya (ISBI Workshops, 2020)

Self-Supervised Physics-Based Deep Learning MRI Reconstruction Without Fully-Sampled Data. - Burhaneddin Yaman; Seyed Amir Hossein Hosseini; Steen Moeller; Jutta Ellermann; Kâmil Ugurbil; Mehmet Akçakaya (ISBI, 2020)

Noise2Inpaint: Learning Referenceless Denoising by Inpainting Unrolling. - Burhaneddin Yaman; Seyed Amir Hossein Hosseini; Mehmet Akçakaya (CoRR, 2020)

Multi-Mask Self-Supervised Learning for Physics-Guided Neural Networks in Highly Accelerated MRI. - Burhaneddin Yaman; Seyed Amir Hossein Hosseini; Steen Moeller; Jutta Ellermann; Kâmil Ugurbil; Mehmet Akçakaya (CoRR, 2020)

Dense Recurrent Neural Networks for Accelerated MRI: History-Cognizant Unrolling of Optimization Algorithms. - Seyed Amir Hossein Hosseini; Burhaneddin Yaman; Steen Moeller; Mingyi Hong 001; Mehmet Akçakaya (IEEE J. Sel. Top. Signal Process., 2020)

Low-Rank Tensor Models for Improved Multidimensional MRI: Application to Dynamic Cardiac T1 Mapping. - Burhaneddin Yaman; Sebastian Weingärtner; Nikolaos Kargas; Nicholas D. Sidiropoulos; Mehmet Akçakaya (IEEE Trans. Computational Imaging, 2020)

Improved Simultaneous Multi-Slice Functional MRI Using Self-supervised Deep Learning. - Ömer Burak Demirel; Burhaneddin Yaman; Logan Dowdle; Steen Moeller; Luca Vizioli; Essa Yacoub; John P. Strupp; Cheryl A. Olman; Kâmil Ugurbil; Mehmet Akçakaya (ACSCC, 2021)

Efficient Training of 3D Unrolled Neural Networks for MRI Reconstruction Using Small Databases. - Zilin Deng; Burhaneddin Yaman; Chi Zhang 057; Steen Moeller; Mehmet Akçakaya (ACSCC, 2021)

Instabilities in Conventional Multi-Coil MRI Reconstruction with Small Adversarial Perturbations. - Chi Zhang 057; Jinghan Jia; Burhaneddin Yaman; Steen Moeller; Sijia Liu 001; Mingyi Hong 001; Mehmet Akçakaya (ACSCC, 2021)

20-fold Accelerated 7T fMRI Using Referenceless Self-Supervised Deep Learning Reconstruction. - Ömer Burak Demirel; Burhaneddin Yaman; Logan Dowdle; Steen Moeller; Luca Vizioli; Essa Yacoub; John P. Strupp; Cheryl A. Olman; Kâmil Ugurbil; Mehmet Akçakaya (EMBC, 2021)

Compressed Sensing MRI with ℓ1-Wavelet Reconstruction Revisited Using Modern Data Science Tools. - Hongyi Gu; Burhaneddin Yaman; Kâmil Ugurbil; Steen Moeller; Mehmet Akçakaya (EMBC, 2021)

Improved Supervised Training of Physics-Guided Deep Learning Image Reconstruction with Multi-Masking. - Burhaneddin Yaman; Seyed Amir Hossein Hosseini; Steen Moeller; Mehmet Akçakaya (ICASSP, 2021)

Ground-Truth Free Multi-Mask Self-Supervised Physics-Guided Deep Learning in Highly Accelerated MRI. - Burhaneddin Yaman; Seyed Amir Hossein Hosseini; Steen Moeller; Jutta Ellermann; Kâmil Ugurbil; Mehmet Akçakaya (ISBI, 2021)

Self-Supervised Physics-Guided Deep Learning Reconstruction for High-Resolution 3D LGE CMR. - Burhaneddin Yaman; Chetan Shenoy; Zilin Deng; Steen Moeller; Hossam El-Rewaidy; Reza Nezafat; Mehmet Akçakaya (ISBI, 2021)

Scan-Specific MRI Reconstruction using Zero-Shot Physics-Guided Deep Learning. - Burhaneddin Yaman; Seyed Amir Hossein Hosseini; Mehmet Akçakaya (CoRR, 2021)

On Instabilities of Conventional Multi-Coil MRI Reconstruction to Small Adverserial Perturbations. - Chi Zhang 057; Jinghan Jia; Burhaneddin Yaman; Steen Moeller; Sijia Liu 001; Mingyi Hong 001; Mehmet Akçakaya (CoRR, 2021)

Unsupervised Deep Learning Methods for Biological Image Reconstruction. - Mehmet Akçakaya; Burhaneddin Yaman; Hyungjin Chung; Jong Chul Ye (CoRR, 2021)

fastMRI+: Clinical Pathology Annotations for Knee and Brain Fully Sampled Multi-Coil MRI Data. - Ruiyang Zhao; Burhaneddin Yaman; Yuxin Zhang; Russell Stewart; Austin Dixon; Florian Knoll; Zhengnan Huang; Yvonne W. Lui; Michael S. Hansen; Matthew P. Lungren (CoRR, 2021)

End-to-End AI-based MRI Reconstruction and Lesion Detection Pipeline for Evaluation of Deep Learning Image Reconstruction. - Ruiyang Zhao; Yuxin Zhang; Burhaneddin Yaman; Matthew P. Lungren; Michael S. Hansen (CoRR, 2021)

Signal-Intensity Informed Multi-Coil MRI Encoding Operator for Improved Physics-Guided Deep Learning Reconstruction of Dynamic Contrast-Enhanced MRI. - Ömer Burak Demirel; Burhaneddin Yaman; Steen Moeller; Sebastian Weingärtner; Mehmet Akçakaya (EMBC, 2022)

Zero-Shot Self-Supervised Learning for MRI Reconstruction. - Burhaneddin Yaman; Seyed Amir Hossein Hosseini; Mehmet Akçakaya (ICLR, 2022)

Distributed Memory-Efficient Physics-Guided Deep Learning Reconstruction for Large-Scale 3d Non-Cartesian MRI. - Chi Zhang 057; Davide Piccini; Ömer Burak Demirel; Gabriele Bonanno; Burhaneddin Yaman; Matthias Stuber; Steen Moeller; Mehmet Akçakaya (ISBI, 2022)

Physics-Driven Deep Learning for Computational Magnetic Resonance Imaging. - Kerstin Hammernik; Thomas Küstner; Burhaneddin Yaman; Zhengnan Huang; Daniel Rueckert; Florian Knoll; Mehmet Akçakaya (CoRR, 2022)

Accelerated MRI With Deep Linear Convolutional Transform Learning. - Hongyi Gu; Burhaneddin Yaman; Steen Moeller; Il Yong Chun; Mehmet Akçakaya (CoRR, 2022)

Object Detection for Autonomous Dozers. - Chun-Hao Liu; Burhaneddin Yaman (CoRR, 2022)

Unsupervised Deep Learning Methods for Biological Image Reconstruction and Enhancement: An overview from a signal processing perspective. - Mehmet Akçakaya; Burhaneddin Yaman; Hyungjin Chung; Jong Chul Ye (IEEE Signal Process. Mag., 2022)

Ultra-Sonic Sensor based Object Detection for Autonomous Vehicles. - Tommaso Nesti; Santhosh Boddana; Burhaneddin Yaman (CVPR Workshops, 2023)

High-fidelity Database-free Deep Learning Reconstruction for Real-time Cine Cardiac MRI. - Ömer Burak Demirel; Chi Zhang 057; Burhaneddin Yaman; Merve Gülle; Chetan Shenoy; Tim Leiner; Peter Kellman; Mehmet Akçakaya (EMBC, 2023)

High-Quality 0.5mm Isotropic fMRI: Random Matrix Theory Meets Physics-Driven Deep Learning. - Ömer Burak Demirel; Steen Moeller; Luca Vizioli; Burhaneddin Yaman; Logan Dowdle; Essa Yacoub; Kâmil Ugurbil; Mehmet Akçakaya (NER, 2023)

Instance-Aware Repeat Factor Sampling for Long-Tailed Object Detection. - Burhaneddin Yaman; Tanvir Mahmud; Chun-Hao Liu (CoRR, 2023)

Deep Double Descent for Time Series Forecasting: Avoiding Undertrained Models. - Valentino Assandri; Sam Heshmati; Burhaneddin Yaman; Anton Iakovlev; Ariel Emiliano Repetur (CoRR, 2023)

Physics-Driven Deep Learning for Computational Magnetic Resonance Imaging: Combining physics and machine learning for improved medical imaging. - Kerstin Hammernik; Thomas Küstner; Burhaneddin Yaman; Zhengnan Huang; Daniel Rueckert; Florian Knoll; Mehmet Akçakaya (IEEE Signal Process. Mag., 2023)

VLP: Vision Language Planning for Autonomous Driving. - Chenbin Pan; Burhaneddin Yaman; Tommaso Nesti; Abhirup Mallik; Alessandro Gabriele Allievi; Senem Velipasalar; Liu Ren (CVPR, 2024)

CLIP-BEVFormer: Enhancing Multi-View Image-Based BEV Detector with Ground Truth Flow. - Chenbin Pan; Burhaneddin Yaman; Senem Velipasalar; Liu Ren (CVPR, 2024)

PaPr: Training-Free One-Step Patch Pruning with Lightweight ConvNets for Faster Inference. - Tanvir Mahmud; Burhaneddin Yaman; Chun-Hao Liu; Diana Marculescu (ECCV (23), 2024)

SSVOD: Semi-Supervised Video Object Detection with Sparse Annotations. - Tanvir Mahmud; Chun-Hao Liu; Burhaneddin Yaman; Diana Marculescu (WACV, 2024)

MTA: Multimodal Task Alignment for BEV Perception and Captioning. - Yunsheng Ma; Burhaneddin Yaman; Xin Ye; Feng Tao; Abhirup Mallik; Ziran Wang; Liu Ren (CoRR, 2024)

BEVDiffuser: Plug-and-Play Diffusion Model for BEV Denoising with Ground-Truth Guidance. - Xin Ye; Burhaneddin Yaman; Sheng Cheng; Feng Tao; Abhirup Mallik; Liu Ren (CVPR, 2025)

AdaWM: Adaptive World Model based Planning for Autonomous Driving. - Hang Wang; Xin Ye; Feng Tao; Chenbin Pan; Abhirup Mallik; Burhaneddin Yaman; Liu Ren; Junshan Zhang (ICLR, 2025)

Position: Prospective of Autonomous Driving - Multimodal LLMs, World Models, Embodied Intelligence, AI Alignment, and Mamba. - Yunsheng Ma; Wenqian Ye; Can Cui; Haiming Zhang 001; Shuo Xing; Fucai Ke; Jinhong Wang; Chenglin Miao; Jintai Chen; Hamid Rezatofighi; Zhen Li 026; Guangtao Zheng; et al. (WACV (Workshops), 2025)

LORD: Large Models Based Opposite Reward Design for Autonomous Driving. - Xin Ye; Feng Tao; Abhirup Mallik; Burhaneddin Yaman; Liu Ren (WACV, 2025)

ALN-P3: Unified Language Alignment for Perception, Prediction, and Planning in Autonomous Driving. - Yunsheng Ma; Burhaneddin Yaman; Xin Ye; Mahmut Yurt; Jingru Luo; Abhirup Mallik; Ziran Wang; Liu Ren (CoRR, 2025)

LTDA-Drive: LLMs-guided Generative Models based Long-tail Data Augmentation for Autonomous Driving. - Mahmut Yurt; Xin Ye; Yunsheng Ma; Jingru Luo; Abhirup Mallik; John Pauly; Burhaneddin Yaman; Liu Ren (CoRR, 2025)