106 citations · 182 across the 13 of their papers we have counts for
6 papers · 1 filter
In vivo labeling and quantitative imaging of neurons using MRI
Shana Li, Xiang Xu, Canjun Li +5
Mammalian brain is a complex organ that contains billions of neurons. These neurons form various neural circuits that control the perception, cognition, emotion and behavior. Devel…
Multimodal foundation models are better simulators of the human brain
Haoyu Lu, Qiongyi Zhou, Nanyi Fei +8
Multimodal learning, especially large-scale multimodal pre-training, has developed rapidly over the past few years and led to the greatest advances in artificial intelligence (AI).…
Non-weight modules over a Schr{ö}dinger-Virasoro type algebra
Jiajia Wen, Zhongyin Xu, Yanyong Hong
In this paper, we give a complete classification of all free -modules of rank 1 over a Schr{ö}dinger-Virasoro type algebr…
Applications of Generative Adversarial Networks in Neuroimaging and Clinical Neuroscience
Rongguang Wang, Vishnu Bashyam, Zhijian Yang +10
Generative adversarial networks (GANs) are one powerful type of deep learning models that have been successfully utilized in numerous fields. They belong to a broader family called…
Surreal-GAN:Semi-Supervised Representation Learning via GAN for uncovering heterogeneous disease-related imaging patterns
Zhijian Yang, Junhao Wen, Christos Davatzikos
A plethora of machine learning methods have been applied to imaging data, enabling the construction of clinically relevant imaging signatures of neurological and neuropsychiatric d…
Subtyping brain diseases from imaging data
Junhao Wen, Erdem Varol, Zhijian Yang +5
The imaging community has increasingly adopted machine learning (ML) methods to provide individualized imaging signatures related to disease diagnosis, prognosis, and response to t…