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Found 4 papers, 3 papers with code
Densely Connected $G$-invariant Deep Neural Networks with Signed Permutation Representations
In contrast to other $G$-invariant architectures in the literature, the preactivations of the$G$-DNNs presented here are able to transform by \emph{signed} permutation representations (signed perm-reps) of $G$.
A Classification of $G$-invariant Shallow Neural Networks
In this paper, we take a first step towards this goal; we prove a theorem that gives a classification of all $G$-invariant single-hidden-layer or ``shallow'' neural network ($G$-SNN) architectures with ReLU activation for any finite orthogonal group $G$, and we prove a second theorem that characterizes the inclusion maps or ``network morphisms'' between the architectures that can be leveraged during neural architecture search (NAS).
A Group-Equivariant Autoencoder for Identifying Spontaneously Broken Symmetries
We use group theory to deduce which symmetries of the system remain intact in all phases, and then use this information to constrain the parameters of the GE-autoencoder such that the encoder learns an order parameter invariant to these ``never-broken'' symmetries.
Impact of Graph Structures for QAOA on MaxCut
The quantum approximate optimization algorithm (QAOA) is a promising method of solving combinatorial optimization problems using quantum computing.
Combinatorial Optimization
Quantum Physics
