1 citations · 1 across the 3 of their papers we have counts for
4 papers
MIRAGE: Robust multi-modal architectures translate fMRI-to-image models from vision to mental imagery
Reese Kneeland, Cesar Kadir Torrico Villanueva, Jordyn Ojeda +4
To be useful for downstream applications, vision decoding models that are trained to reconstruct seen images from human brain activity must be able to generalize to internally gene…
Brain-optimized inference improves reconstructions of fMRI brain activity
Reese Kneeland, Jordyn Ojeda, Ghislain St-Yves +1
The release of large datasets and developments in AI have led to dramatic improvements in decoding methods that reconstruct seen images from human brain activity. We evaluate the p…
Second Sight: Using brain-optimized encoding models to align image distributions with human brain activity
Reese Kneeland, Jordyn Ojeda, Ghislain St-Yves +1
Two recent developments have accelerated progress in image reconstruction from human brain activity: large datasets that offer samples of brain activity in response to many thousan…
Reconstructing seen images from human brain activity via guided stochastic search
Reese Kneeland, Jordyn Ojeda, Ghislain St-Yves +1
Visual reconstruction algorithms are an interpretive tool that map brain activity to pixels. Past reconstruction algorithms employed brute-force search through a massive library to…