1 citations · 1 across the 6 of their papers we have counts for
7 papers
MetaLearnNCA: Few-Shot Offline Meta-Learning via Interacting Neural Cellular Automata
Etienne Guichard, Stefano Nichele
Few-shot meta-learning traditionally formulates task adaptation either as analytical gradient descent through unrolled computational graphs or as metric-based distance comparisons…
Neural Cellular Automata Learn General Features in their Hidden Channels
Etienne Guichard, Stefano Nichele
Modern deep learning models achieve impressive generalization through over-parameterization, but this paradigm often struggles with overfitting and memorization in few-shot regimes…
Emergent Models: Intelligence from Tiny Substrates
Giacomo Bocchese, Nicola Giacobbo, Etienne Guichard +2
Emergent Models (EMs) are a machine learning paradigm based on simple yet open-ended substrates, such as cellular automata, in which modeling is treated not as the learning of a cl…
Mass Conservation as an Inductive Bias for Self-Organized Criticality in NCA Reservoirs
Tong Zhang, Etienne Guichard, Sidney Pontes-Filho +1
Self-organized criticality (SOC), a dynamical regime associated with maximal information processing, offers a promising foundation for reservoir computing. Recent work has shown th…
MaCE: General Mass Conserving Dynamics for Cellular Automata
Vassilis Papadopoulos, Etienne Guichard
We present Mass-Conserving Evolution (MaCE), a general method for implementing mass conservation in Cellular Automata (CA). MaCE is a simple evolution rule that can be easily 'atta…
ARC-NCA: Towards Developmental Solutions to the Abstraction and Reasoning Corpus
Etienne Guichard, Felix Reimers, Mia Kvalsund +2
The Abstraction and Reasoning Corpus (ARC), later renamed ARC-AGI, poses a fundamental challenge in artificial general intelligence (AGI), requiring solutions that exhibit robust a…
EngramNCA: a Neural Cellular Automaton Model of Memory Transfer
Etienne Guichard, Felix Reimers, Mia Kvalsund +2
This study introduces EngramNCA, a neural cellular automaton (NCA) that integrates both publicly visible states and private, cell-internal memory channels, drawing inspiration from…