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Found 4 papers, 1 papers with code
How to optimize neuroscience data utilization and experiment design for advancing primate visual and linguistic brain models?
In recent years, neuroscience has made significant progress in building large-scale artificial neural network (ANN) models of brain activity and behavior.
Rethinking the limiting dynamics of SGD: modified loss, phase space oscillations, and anomalous diffusion
In this work we explore the limiting dynamics of deep neural networks trained with stochastic gradient descent (SGD).
The Limiting Dynamics of SGD: Modified Loss, Phase Space Oscillations, and Anomalous Diffusion
In this work we explore the limiting dynamics of deep neural networks trained with stochastic gradient descent (SGD).
Validation and generalization of pixel-wise relevance in convolutional neural networks trained for face classification
To be interpretable and useful to humans, such a method should convey a model's learned classification strategy in a way that is robust to random initializations or spurious correlations in input data.
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