1 citations · 1 across the 5 of their papers we have counts for
5 papers
LLMs Can See the Smoke but not the Fire: Evaluating Abductive Reasoning with Elenchos
Julius Steiglechner, Lucas Mahler, Gabriele Lohmann
Large language models (LLMs) excel at pattern recognition and text generation, but their capacity for abductive inference - inferring latent hypotheses that explain observed behavi…
UltraCortex: Submillimeter Ultra-High Field 9.4 T Brain MR Image Collection and Manual Cortical Segmentations
Lucas Mahler, Julius Steiglechner, Benjamin Bender +12
The UltraCortex repository (https://www.ultracortex.org) houses magnetic resonance imaging data of the human brain obtained at an ultra-high field strength of 9.4 T. It contains 86…
DISGAN: Wavelet-informed Discriminator Guides GAN to MRI Super-resolution with Noise Cleaning
Qi Wang, Lucas Mahler, Julius Steiglechner +3
MRI super-resolution (SR) and denoising tasks are fundamental challenges in the field of deep learning, which have traditionally been treated as distinct tasks with separate paired…
Pretraining is All You Need: A Multi-Atlas Enhanced Transformer Framework for Autism Spectrum Disorder Classification
Lucas Mahler, Qi Wang, Julius Steiglechner +4
Autism spectrum disorder (ASD) is a prevalent psychiatric condition characterized by atypical cognitive, emotional, and social patterns. Timely and accurate diagnosis is crucial fo…
A Three-Player GAN for Super-Resolution in Magnetic Resonance Imaging
Qi Wang, Lucas Mahler, Julius Steiglechner +3
Learning based single image super resolution (SISR) task is well investigated in 2D images. However, SISR for 3D Magnetics Resonance Images (MRI) is more challenging compared to 2D…