#super-resolution try — diffusion models for protein design efficient attention beyond transformers papers like retrieval-augmented generation
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5 papers match
astro-ph.IM 2026 ☆
PhySR: Physics-Informed Neural Network for Super-Resolution Reconstruction in Radio Synthesis Imaging Hongkun Yang, Li Zhang, Ming Zhang +1
PhySR is a physics‑informed neural network that directly reconstructs high‑resolution radio images from low‑resolution dirty images by embedding the telescope’s primary beam, PSF c…
#radio interferometry #super-resolution #physics-informed neural networks #image reconstruction
astro-ph.CO 2026 ☆
Cosmo-SPINN: Fuzzy Dark Matter Simulations with Physics-Informed Generative Networks Ashutosh Kumar Mishra, Emma Tolley, Nicolas Cerardi
The paper introduces a physics‑informed generative U‑Net that can evolve fuzzy dark matter fields and perform super‑resolution of simulations while enforcing the Schrödinger‑Poisso…
#fuzzy dark matter #physics-informed neural networks #generative modeling #cosmological simulation
cs.LG 2026 ☆
ZUNA1.1: A more flexible EEG foundation model for Denoising and Super-resolution Christopher Warner, Jonas Mago, JR Huml +1
The paper presents ZUNA1.1, a 380‑million‑parameter diffusion autoencoder that can denoise and super‑resolve EEG recordings of variable length and channel configurations, outperfor…
#eeg processing #diffusion models #signal reconstruction #denoising
eess.SP 2026 ☆
Spatial Angular Pseudo-Derivative Search Algorithm: A Real-Time Single-Snapshot Super-Resolution Sparse DOA Scheme for Automotive Radar Longxin Bai, Jingchao Zhang, Liyan Qiao
The paper introduces a fast, single‑snapshot algorithm that uses a spatial angular pseudo‑derivative constraint to achieve super‑resolution direction‑of‑arrival estimation for auto…
#direction-of-arrival estimation #automotive radar #sparse recovery #real-time processing
cs.CV 2026 ☆
RoughNet: Mapping Arctic Sea Ice Roughness Using Diffusion-Based Super-Resolution of Satellite Imagery Tessa Cannon, Michel Tsamados, Petru Manescu +5
The paper introduces RoughNet, a conditional diffusion model that converts 10 m Sentinel‑2 optical images into 1 m resolution sea‑ice surface elevation maps, enabling high‑resoluti…
#sea ice #roughness estimation #diffusion models #super-resolution
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