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Jonni Virtema

2 accepted papers

2024

Complexity of Neural Network Training and ETR: Extensions with Effectively Continuous Functions

AAAI 2024technical

The training problem of neural networks (NNs) is known to be ER-complete with respect to ReLU and linear activation functions. We show that the training problem for NNs equipped with arbitrary activation functions is polynomial-time bireducible to the existential theory of the reals extended with th…

Cited by 7SourcePDFScholar
2024

Graph Neural Networks and Arithmetic Circuits

NeurIPS 2024poster

We characterize the computational power of neural networks that follow the graph neural network (GNN) architecture, not restricted to aggregate-combine GNNs or other particular types. We establish an exact correspondence between the expressivity of GNNs using diverse activation functions and arithme…

Cited by 2SourcePDFScholar