A geometric analysis of neural collapse with unconstrained features
We provide the first global optimization landscape analysis of Neural Collapse--an intriguing
empirical phenomenon that arises in the last-layer classifiers and features of neural …
empirical phenomenon that arises in the last-layer classifiers and features of neural …
Limitations of neural collapse for understanding generalization in deep learning
The recent work of Papyan, Han, & Donoho (2020) presented an intriguing" Neural
Collapse" phenomenon, showing a structural property of interpolating classifiers in the late …
Collapse" phenomenon, showing a structural property of interpolating classifiers in the late …
On the emergence of simplex symmetry in the final and penultimate layers of neural network classifiers
E Weinan, S Wojtowytsch - Mathematical and Scientific …, 2022 - proceedings.mlr.press
A recent numerical study observed that neural network classifiers enjoy a large degree of
symmetry in the penultimate layer. Namely, if $ h (x)= Af (x)+ b $ where $ A $ is a linear map …
symmetry in the penultimate layer. Namely, if $ h (x)= Af (x)+ b $ where $ A $ is a linear map …
Neural collapse for unconstrained feature model under cross-entropy loss with imbalanced data
W Hong, S Ling - arXiv preprint arXiv:2309.09725, 2023 - arxiv.org
Recent years have witnessed the huge success of deep neural networks (DNNs) in various
tasks of computer vision and text processing. Interestingly, these DNNs with massive …
tasks of computer vision and text processing. Interestingly, these DNNs with massive …
On the emergence of simplex symmetry in the final and penultimate layers of neural network classifiers
S Wojtowytsch - arXiv preprint arXiv:2012.05420, 2020 - arxiv.org
A recent numerical study observed that neural network classifiers enjoy a large degree of
symmetry in the penultimate layer. Namely, if $ h (x)= Af (x)+ b $ where $ A $ is a linear map …
symmetry in the penultimate layer. Namely, if $ h (x)= Af (x)+ b $ where $ A $ is a linear map …
Neural Collapse for Unconstrained Feature Model under Cross-entropy Loss with Imbalanced Data
W Hong, S Ling - Journal of Machine Learning Research, 2024 - jmlr.org
Neural Collapse (NC) is a fascinating phenomenon that arises during the terminal phase of
training (TPT) of deep neural networks (DNNs). Specifically, for balanced training datasets …
training (TPT) of deep neural networks (DNNs). Specifically, for balanced training datasets …
Validation is not verification: precise terminology and scientific methods in bioprocess modeling
J Smiatek, A Jung, E Bluhmki - Trends in Biotechnology, 2021 - cell.com
Advanced statistical approaches and new modeling procedures for biopharmaceutical
development and manufacturing have received increasing attention. With this forum article …
development and manufacturing have received increasing attention. With this forum article …
Robustness and complexity
SA Frank - Cell Systems, 2023 - cell.com
When a system robustly corrects component-level errors, the direct pressure on component
performance declines. Components become less reliable, maintain more genetic variability …
performance declines. Components become less reliable, maintain more genetic variability …
Optimization of transcription factor genetic circuits
SA Frank - Biology, 2022 - mdpi.com
Simple Summary Transcription factors (TFs) are proteins that bind to DNA and control the
expression of genes, including other TF genes. A common challenge in cellular biology is to …
expression of genes, including other TF genes. A common challenge in cellular biology is to …
On Interpretability of CNNs for Multimodal Medical Image Segmentation
S Lazendić, J Janssens, S Huang… - 2022 30th European …, 2022 - ieeexplore.ieee.org
Despite their huge potential, deep learning-based models are still not trustful enough to
warrant their adoption in clinical practice. The research on the interpretability and …
warrant their adoption in clinical practice. The research on the interpretability and …