475 citations · 561 across the 9 of their papers we have counts for
9 papers
End-to-end topographic networks as models of cortical map formation and human visual behaviour: moving beyond convolutions
Zejin Lu, Adrien Doerig, Victoria Bosch +4
Computational models are an essential tool for understanding the origin and functions of the topographic organisation of the primate visual system. Yet, vision is most commonly mod…
The Algonauts Project 2023 Challenge: How the Human Brain Makes Sense of Natural Scenes
A. T. Gifford, B. Lahner, S. Saba-Sadiya +6
The sciences of biological and artificial intelligence are ever more intertwined. Neural computational principles inspire new intelligent machines, which are in turn used to advanc…
Net2Brain: A Toolbox to compare artificial vision models with human brain responses
Domenic Bersch, Kshitij Dwivedi, Martina Vilas +2
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 reco…
The Algonauts Project 2021 Challenge: How the Human Brain Makes Sense of a World in Motion
R. M. Cichy, K. Dwivedi, B. Lahner +8
The sciences of natural and artificial intelligence are fundamentally connected. Brain-inspired human-engineered AI are now the standard for predicting human brain responses during…
Duality Diagram Similarity: a generic framework for initialization selection in task transfer learning
Kshitij Dwivedi, Jiahui Huang, Radoslaw Martin Cichy +1
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-trai…
The Algonauts Project: A Platform for Communication between the Sciences of Biological and Artificial Intelligence
Radoslaw Martin Cichy, Gemma Roig, Alex Andonian +6
In the last decade, artificial intelligence (AI) models inspired by the brain have made unprecedented progress in performing real-world perceptual tasks like object classification…
Recurrence is required to capture the representational dynamics of the human visual system
Tim C Kietzmann, Courtney J Spoerer, Lynn Sörensen +3
The human visual system is an intricate network of brain regions that enables us to recognize the world around us. Despite its abundant lateral and feedback connections, object pro…
Deep Neural Networks predict Hierarchical Spatio-temporal Cortical Dynamics of Human Visual Object Recognition
Radoslaw M. Cichy, Aditya Khosla, Dimitrios Pantazis +2
The complex multi-stage architecture of cortical visual pathways provides the neural basis for efficient visual object recognition in humans. However, the stage-wise computations t…
Can visual information encoded in cortical columns be decoded from magnetoencephalography data in humans?
Radoslaw Martin Cichy, Dimitrios Pantazis
It is a principal open question whether noninvasive imaging methods in humans can decode information encoded at a spatial scale as fine as the basic functional unit of cortex: cort…