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Found 4 papers, 1 papers with code
Asymmetry in Low-Rank Adapters of Foundation Models
Specifically, when updating the parameter matrices of a neural network by adding a product $BA$, we observe that the $B$ and $A$ matrices have distinct functions: $A$ extracts features from the input, while $B$ uses these features to create the desired output.
Topology-Aware Surface Reconstruction for Point Clouds
We present an approach to inform the reconstruction of a surface from a point scan through topological priors.
Computational Geometry Graphics
Topological Approaches to Deep Learning
We perform topological data analysis on the internal states of convolutional deep neural networks to develop an understanding of the computations that they perform.
Exposition and Interpretation of the Topology of Neural Networks
We use topological data analysis to show that the information encoded in the weights of a CNN can be organized in terms of a topological data model and demonstrate how such information can be interpreted and utilized.
