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Found 3 papers, 1 papers with code
Flood and Echo Net: Algorithmically Aligned GNNs that Generalize
We test the Flood and Echo Net on a variety of synthetic tasks and the SALSA-CLRS benchmark and find that the algorithmic alignment of the execution improves generalization to larger graph sizes.
Euler Characteristic Transform Based Topological Loss for Reconstructing 3D Images from Single 2D Slices
We also show a favourable property, namely injectivity and discuss the stability of the topological loss function based on the Euler Characteristic Transform.
A Robust Classification Framework for Byzantine-Resilient Stochastic Gradient Descent
This paper proposes a Robust Gradient Classification Framework (RGCF) for Byzantine fault tolerance in distributed stochastic gradient descent.
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