68 citations · 489 across the 32 of their papers we have counts for
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cs.CV2016★ 48 cited
Permutation-equivariant neural networks applied to dynamics prediction
Nicholas Guttenberg, Nathaniel Virgo, Olaf Witkowski +2
The introduction of convolutional layers greatly advanced the performance of neural networks on image tasks due to innately capturing a way of encoding and learning translation-inv…
cs.AI2016★ 2 cited
Neural Coarse-Graining: Extracting slowly-varying latent degrees of freedom with neural networks
Nicholas Guttenberg, Martin Biehl, Ryota Kanai
We present a loss function for neural networks that encompasses an idea of trivial versus non-trivial predictions, such that the network jointly determines its own prediction goals…