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Found 6 papers, 4 papers with code
FroSSL: Frobenius Norm Minimization for Efficient Multiview Self-Supervised Learning
However, these two approaches are difficult to combine due to the computational complexity of computing eigenvalues.
DiME: Maximizing Mutual Information by a Difference of Matrix-Based Entropies
We introduce an information-theoretic quantity with similar properties to mutual information that can be estimated from data without making explicit assumptions on the underlying distribution.
The Representation Jensen-Rényi Divergence
We introduce a divergence measure between data distributions based on operators in reproducing kernel Hilbert spaces defined by kernels.
Max-sliced Bures Distance for Interpreting Discrepancies
We propose the max-sliced Bures distance, a lower bound on the max-sliced Wasserstein-2 distance, to identify the instances associated with the maximum discrepancy between two samples.
Multivariate Extension of Matrix-based Renyi's α-order Entropy Functional
The matrix-based Renyi's \alpha-order entropy functional was recently introduced using the normalized eigenspectrum of a Hermitian matrix of the projected data in a reproducing kernel Hilbert space (RKHS).
Integrating Flexible Normalization into Mid-Level Representations of Deep Convolutional Neural Networks
Deep convolutional neural networks (CNNs) are becoming increasingly popular models to predict neural responses in visual cortex.
