2 papers
stat.ML2026
Signal-to-Noise Ratio and Sample Size Govern Representational Alignment in Neural Networks
Ali Hussaini Umar, Alessandro Laio
Neural networks are known to develop latent representations that are , namely structurally similar across networks trained with different architectures, training protocols…
cs.LG2025
The Effect of Label Noise on the Information Content of Neural Representations
Ali Hussaini Umar, Franky Kevin Nando Tezoh, Jean Barbier +2
In supervised classification tasks, models are trained to predict a label for each data point. In real-world datasets, these labels are often noisy due to annotation errors. While…