most citedJacobian-Aware Posterior Sampling for Inverse Problems

1 citations · 1 across the 3 of their papers we have counts for

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6 papers

cs.CV20261 cited

Jacobian-Aware Posterior Sampling for Inverse Problems

Liav Hen, Tom Tirer, Raja Giryes +1

Diffusion models provide powerful generative priors for solving inverse problems by sampling from a posterior distribution conditioned on corrupted measurements. Existing methods p…

cs.CV2026

Making Reconstruction FID Predictive of Diffusion Generation FID

Tongda Xu, Mingwei He, Shady Abu-Hussein +6

It is well known that the reconstruction FID (rFID) of a VAE is poorly correlated with the generation FID (gFID) of a latent diffusion model. We propose interpolated FID (iFID), a…

cs.CV2026

Anatomical Token Uncertainty for Transformer-Guided Active MRI Acquisition

Lev Ayzenberg, Shady Abu-Hussein, Raja Giryes +1

Full data acquisition in MRI is inherently slow, which limits clinical throughput and increases patient discomfort. Compressed Sensing MRI (CS-MRI) seeks to accelerate acquisition…

eess.IV2025

Diffusion Models are Robust Pretrainers

Mika Yagoda, Shady Abu-Hussein, Raja Giryes

Diffusion models have gained significant attention for high-fidelity image generation. Our work investigates the potential of exploiting diffusion models for adversarial robustness…

cs.CV2025

ADIR: Adaptive Diffusion for Image Reconstruction

Shady Abu-Hussein, Tom Tirer, Raja Giryes

Denoising diffusion models have recently achieved remarkable success in image generation, capturing rich information about natural image statistics. This makes them highly promisin…

cs.LG2025

DeciMamba: Exploring the Length Extrapolation Potential of Mamba

Assaf Ben-Kish, Itamar Zimerman, Shady Abu-Hussein +4

Long-range sequence processing poses a significant challenge for Transformers due to their quadratic complexity in input length. A promising alternative is Mamba, which demonstrate…