1 citations · 1 across the 4 of their papers we have counts for
5 papers
Pixel-Space Diffusion Transformers
Renye Yan, Jikang Cheng, You Wu +8
Latent diffusion models (LDMs) enable efficient high-resolution image synthesis by denoising in a VAE-compressed latent space. However, fixed visual tokenizers can discard fine tex…
Large-Scale AI and Foundation Models for Neuroscience: A Comprehensive Review
Shihao Yang, Xiying Huang, Danilo Bernardo +10
The development of large-scale artificial intelligence (AI) models is influencing neuroscience research by enabling end-to-end learning from raw brain signals and neural data. In t…
Diffusion Models for Computational Neuroimaging: A Survey
Haokai Zhao, Haowei Lou, Lina Yao +4
Computational neuroimaging involves analyzing brain images or signals to provide mechanistic insights and predictive tools for human cognition and behavior. While diffusion models…
Brain-Cognition Fingerprinting via Graph-GCCA with Contrastive Learning
Yixin Wang, Wei Peng, Yu Zhang +3
Many longitudinal neuroimaging studies aim to improve the understanding of brain aging and diseases by studying the dynamic interactions between brain function and cognition. Doing…
Evaluating the Quality of Brain MRI Generators
Jiaqi Wu, Wei Peng, Binxu Li +2
Deep learning models generating structural brain MRIs have the potential to significantly accelerate discovery of neuroscience studies. However, their use has been limited in part…