3 citations · 3 across the 2 of their papers we have counts for
2 papers
cs.LG2024
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…
cs.CV2022★ 3 cited
The Unreasonable Effectiveness of Fully-Connected Layers for Low-Data Regimes
Peter Kocsis, Peter Súkeník, Guillem Brasó +3
Convolutional neural networks were the standard for solving many computer vision tasks until recently, when Transformers of MLP-based architectures have started to show competitive…