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Found 3 papers, 1 papers with code
Flood and Echo: Algorithmic Alignment of GNNs with Distributed Computing
However, this raises two core questions i) How can we enable nodes to gather the required information in a given graph ($\textit{information exchange}$), even if is far away and ii) How can we design an execution framework which enables this information exchange for extrapolation to larger graph sizes ($\textit{algorithmic alignment for extrapolation}$).
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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