3 citations · 6 across the 8 of their papers we have counts for
3 papers · 1 filter
Wide Neural Networks Trained with Weight Decay Provably Exhibit Neural Collapse
Arthur Jacot, Peter Súkeník, Zihan Wang +1
Deep neural networks (DNNs) at convergence consistently represent the training data in the last layer via a highly symmetric geometric structure referred to as neural collapse. Thi…
Neural Collapse versus Low-rank Bias: Is Deep Neural Collapse Really Optimal?
Peter Súkeník, Marco Mondelli, Christoph Lampert
Deep neural networks (DNNs) exhibit a surprising structure in their final layer known as neural collapse (NC), and a growing body of works has currently investigated the propagatio…
Average gradient outer product as a mechanism for deep neural collapse
Daniel Beaglehole, Peter Súkeník, Marco Mondelli +1
Deep Neural Collapse (DNC) refers to the surprisingly rigid structure of the data representations in the final layers of Deep Neural Networks (DNNs). Though the phenomenon has been…