3 citations · 7 across the 5 of their papers we have counts for
5 papers
Harmony in Diversity: Merging Neural Networks with Canonical Correlation Analysis
Stefan Horoi, Albert Manuel Orozco Camacho, Eugene Belilovsky +1
Combining the predictions of multiple trained models through ensembling is generally a good way to improve accuracy by leveraging the different learned features of the models, howe…
Reliability of CKA as a Similarity Measure in Deep Learning
MohammadReza Davari, Stefan Horoi, Amine Natik +3
Comparing learned neural representations in neural networks is a challenging but important problem, which has been approached in different ways. The Centered Kernel Alignment (CKA)…
Exploring the Geometry and Topology of Neural Network Loss Landscapes
Stefan Horoi, Jessie Huang, Bastian Rieck +3
Recent work has established clear links between the generalization performance of trained neural networks and the geometry of their loss landscape near the local minima to which th…
Advantages of biologically-inspired adaptive neural activation in RNNs during learning
Victor Geadah, Giancarlo Kerg, Stefan Horoi +2
Dynamic adaptation in single-neuron response plays a fundamental role in neural coding in biological neural networks. Yet, most neural activation functions used in artificial netwo…
Internal representation dynamics and geometry in recurrent neural networks
Stefan Horoi, Guillaume Lajoie, Guy Wolf
The efficiency of recurrent neural networks (RNNs) in dealing with sequential data has long been established. However, unlike deep, and convolution networks where we can attribute…