A Demographic-Conditioned Variational Autoencoder for fMRI Distribution
Sampling and Removal of Confounds

A Demographic-Conditioned Variational Autoencoder for fMRI Distribution Sampling and Removal of Confounds

13 May 2024

Anton Orlichenko

Zhengming Ding

Julia M. Stephen

Vince D. Calhoun

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Papers citing "A Demographic-Conditioned Variational Autoencoder for fMRI Distribution Sampling and Removal of Confounds"

6 / 6 papers shown

Title
ImageNomer: description of a functional connectivity and omics analysis tool and case study identifying a race confound Anton Orlichenko Grant Daly Ziyu Zhou Anqi Liu Hui Shen Hong-Wen Deng Yu-Ping Wang 30 3 0 01 Feb 2023
High-Resolution Image Synthesis with Latent Diffusion Models Robin Rombach A. Blattmann Dominik Lorenz Patrick Esser Bjorn Ommer 3DV 437 15,515 0 20 Dec 2021
Diffusion Models Beat GANs on Image Synthesis Prafulla Dhariwal Alex Nichol 227 7,857 0 11 May 2021
Zero-Shot Text-to-Image Generation Aditya A. Ramesh Mikhail Pavlov Gabriel Goh Scott Gray Chelsea Voss Alec Radford Mark Chen Ilya Sutskever VLM 415 4,953 0 24 Feb 2021
Progress in Brain Computer Interfaces: Challenges and Trends S. Saha K. Mamun K. Ahmed R. Mostafa G. Naik A. Khandoker S. Darvishi M. Baumert 41 242 0 11 Jan 2019
Machine Learning for Neuroimaging with Scikit-Learn Alexandre Abraham Fabian Pedregosa Michael Eickenberg Philippe Gervais A. Mueller Jean Kossaifi Alexandre Gramfort Bertrand Thirion Gaël Varoquaux AI4CE 63 1,817 0 12 Dec 2014

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