V ox2Cortex: Fast explicit reconstruction of cortical surfaces from 3D MRI scans with geometric deep neural networks.

We argue that this is due, in part, to a common feature of many interpretability methods: they analyze model behavior by using a particular dataset.

Competing objectives arise when a model's capabilities

PaI methods manage to find trainable subnetworks that outperform random pruning, their performance in terms of both accuracy and computational reduction is far from satisfactory compared to post-training pruning and the understanding of PaI is missing.