Berk Tinaz

Orcid: 0000-0002-5498-5824

According to our database1, Berk Tinaz authored at least 12 papers between 2020 and 2026.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

Legend:

Book  In proceedings  Article  PhD thesis  Dataset  Other 

Links

On csauthors.net:

Bibliography

2026
MosaicMRI: A Diverse Dataset and Benchmark for Raw Musculoskeletal MRI.
CoRR, April, 2026

ATHENA: Adaptive Test-Time Steering for Improving Count Fidelity in Diffusion Models.
CoRR, March, 2026

2025
Hyperphantasia: A Benchmark for Evaluating the Mental Visualization Capabilities of Multimodal LLMs.
CoRR, July, 2025

ConceptMix++: Leveling the Playing Field in Text-to-Image Benchmarking via Iterative Prompt Optimization.
CoRR, July, 2025

Emergence and Evolution of Interpretable Concepts in Diffusion Models.
Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2025, 2025

2024
DiracDiffusion: Denoising and Incremental Reconstruction with Assured Data-Consistency.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

Adapt and Diffuse: Sample-adaptive Reconstruction via Latent Diffusion Models.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

2022
Semi-Supervised Learning of MRI Synthesis Without Fully-Sampled Ground Truths.
IEEE Trans. Medical Imaging, 2022

Progressively volumetrized deep generative models for data-efficient contextual learning of MR image recovery.
Medical Image Anal., 2022

HUMUS-Net: Hybrid Unrolled Multi-scale Network Architecture for Accelerated MRI Reconstruction.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

2020
Prior-Guided Image Reconstruction for Accelerated Multi-Contrast MRI via Generative Adversarial Networks.
IEEE J. Sel. Top. Signal Process., 2020

Semi-Supervised Learning of Mutually Accelerated Multi-Contrast MRI Synthesis without Fully-Sampled Ground-Truths.
CoRR, 2020


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