391 citations · 1.4k across the 26 of their papers we have counts for
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Deep Ensembles: A Loss Landscape Perspective
Stanislav Fort, Huiyi Hu, Balaji Lakshminarayanan
Deep ensembles have been empirically shown to be a promising approach for improving accuracy, uncertainty and out-of-distribution robustness of deep learning models. While deep ens…
Emergent properties of the local geometry of neural loss landscapes
Stanislav Fort, Surya Ganguli
The local geometry of high dimensional neural network loss landscapes can both challenge our cherished theoretical intuitions as well as dramatically impact the practical success o…
Large Scale Structure of Neural Network Loss Landscapes
Stanislav Fort, Stanislaw Jastrzebski
There are many surprising and perhaps counter-intuitive properties of optimization of deep neural networks. We propose and experimentally verify a unified phenomenological model of…
Stiffness: A New Perspective on Generalization in Neural Networks
Stanislav Fort, Paweł Krzysztof Nowak, Stanislaw Jastrzebski +1
In this paper we develop a new perspective on generalization of neural networks by proposing and investigating the concept of a neural network stiffness. We measure how stiff a net…