activity
20172026
most citedWhy rare-earth ferromagnets are so rare: insights from the p-wave Kondo model

13 citations · 30 across the 17 of their papers we have counts for

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Showing 2025Show all

5 papers · 1 filter

eess.IV2025

Comprehensive Evaluation of Quantitative Measurements from Automated Deep Segmentations of PSMA PET/CT Images

Obed Korshie Dzikunu, Amirhossein Toosi, Shadab Ahamed +4

This study performs a comprehensive evaluation of quantitative measurements as extracted from automated deep-learning-based segmentation methods, beyond traditional Dice Similarity…

physics.geo-ph2025

Inversion of Magnetic Data using Learned Dictionaries and Scale Space

Shadab Ahamed, Simon Ghyselincks, Pablo Chang Huang Arias +5

Magnetic data inversion is an important tool in geophysics, used to infer subsurface magnetic susceptibility distributions from surface magnetic field measurements. This inverse pr…

cs.LG2025

Iterative Flow Matching: Path Correction and Gradual Refinement for Enhanced Generative Modeling

Eldad Haber, Shadab Ahamed, Md. Shahriar Rahim Siddiqui +2

Generative models for image generation are now commonly used for a wide variety of applications, ranging from guided image generation for entertainment to solving inverse problems.…

eess.IV2025

Adaptive Voxel-Weighted Loss Using L1 Norms in Deep Neural Networks for Detection and Segmentation of Prostate Cancer Lesions in PET/CT Images

Obed Korshie Dzikunu, Shadab Ahamed, Amirhossein Toosi +2

Accurate automated detection of recurrent prostate cancer in PSMA PET/CT scans is challenging due to heterogeneous lesion size, activity, anatomical location, and intra- and inter-…

cs.LG2025★ 2 cited

Multiscale Training of Convolutional Neural Networks

Shadab Ahamed, Niloufar Zakariaei, Eldad Haber +1

Training convolutional neural networks (CNNs) on high-resolution images is often bottlenecked by the cost of evaluating gradients of the loss on the finest spatial mesh. To address…