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Found 6 papers, 4 papers with code
Net2Brain: A Toolbox to compare artificial vision models with human brain responses
We introduce Net2Brain, a graphical and command-line user interface toolbox for comparing the representational spaces of artificial deep neural networks (DNNs) and human brain recordings.
What do navigation agents learn about their environment?
We use iSEE to probe the dynamic representations produced by these agents for the presence of information about the agent as well as the environment.
Duality Diagram Similarity: a generic framework for initialization selection in task transfer learning
In this paper, we tackle an open research question in transfer learning, which is selecting a model initialization to achieve high performance on a new task, given several pre-trained models.
The Algonauts Project: A Platform for Communication between the Sciences of Biological and Artificial Intelligence
Recently, researchers of natural intelligence have begun using those AI models to explore how the brain performs such tasks.
Representation Similarity Analysis for Efficient Task taxonomy & Transfer Learning
We next evaluate the relationship of RSA with the transfer learning performance on Taskonomy tasks and a new task: Pascal VOC semantic segmentation.
Deep Anchored Convolutional Neural Networks
Convolutional Neural Networks (CNNs) have been proven to be extremely successful at solving computer vision tasks.
