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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 7Source ↗PDF ↗Scholar ↗
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 2Source ↗PDF ↗Scholar ↗