Search Results for author: Grace W. Lindsay

Found 6 papers, 0 papers with code

Grounding Neuroscience in Behavioral Changes using Artificial Neural Networks

no code implementations13 Nov 2023 Grace W. Lindsay

Here I focus on grounding this goal in the specific question of how a given change in behavior is produced by a change in neural circuits or activity.

Testing the Tools of Systems Neuroscience on Artificial Neural Networks

no code implementations14 Feb 2022 Grace W. Lindsay

I provide here both a roadmap for performing this testing and a list of tools that are suitable to be tested on ANNs.

Divergent representations of ethological visual inputs emerge from supervised, unsupervised, and reinforcement learning

no code implementations3 Dec 2021 Grace W. Lindsay, Josh Merel, Tom Mrsic-Flogel, Maneesh Sahani

Artificial neural systems trained using reinforcement, supervised, and unsupervised learning all acquire internal representations of high dimensional input.

reinforcement-learning Reinforcement Learning (RL) +1

Convolutional Neural Networks as a Model of the Visual System: Past, Present, and Future

no code implementations20 Jan 2020 Grace W. Lindsay

Convolutional neural networks (CNNs) were inspired by early findings in the study of biological vision.

Object Recognition

Feature-based Attention in Convolutional Neural Networks

no code implementations19 Nov 2015 Grace W. Lindsay

Furthermore, the comparisons performed here suggest that a proposed model of biological FBA (the "feature similarity gain model") is effective in increasing performance.

Object object-detection +2

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