Feb 25, 2022 · Abstract:Processing sets or other unordered, potentially variable-sized inputs in neural networks is usually handled by aggregating a number ...
May 20, 2022 · This paper proposes a novel aggregation method for processing sets and other unordered inputs (which require permutation invariance) in neural ...
Processing sets or other unordered, potentially variable-sized inputs in neural networks is usually handled by aggregating a number of input tensors.
Here we provide another useful perspective on Equilibrium. Aggregation which is connecting the method to prior work in Bayesian inference and continuing one ...
Feb 25, 2022 · We validate its efficiency on three different tasks: median estimation, class counting, and molecular property prediction. In all experiments, ...
On the search of a principally more powerful aggregation strategy, we propose an optimization-based method called Equilibrium Aggregation. We show that many ...
The equilibrium aggregation layer from the “Equilibrium Aggregation: Encoding Sets via Optimization” paper. The output of this layer y is defined ...
Jul 3, 2022 · Equilibrium Aggregation: Encoding Sets via Optimization. Sergey ... Equilibrium Aggregation perform set aggregation into 256-.
In this post, we will look at a core building block of many graph neural networks: permutation invariant aggregation functions. We start with a general ...
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Nov 2, 2022 · Lillicrap. “Equilibrium aggregation: encoding sets via optimization.” In Uncertainty in Artificial Intelligence, pp. 139–149. PMLR, 2022.