69 citations · 106 across the 15 of their papers we have counts for
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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…
cs.AI2016★ 14 cited
Towards information based spatiotemporal patterns as a foundation for agent representation in dynamical systems
Martin Biehl, Takashi Ikegami, Daniel Polani
We present some arguments why existing methods for representing agents fall short in applications crucial to artificial life. Using a thought experiment involving a fictitious dyna…