1 citations · 2 across the 11 of their papers we have counts for
16 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…
Benchmarking the Connectomes of Caenorhabditis elegans within the Reservoir Computing Framework
Felix S. Reimers, Ola Huse Ramstad, Aliaksandr Hubin +1
The aim of this work is to examine the connectomes of Caenorhabditis elegans through a computational lens using the reservoir computing framework. Connectomes are mappings of biolo…
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…
Self-Replicating Neural Cellular Automata: Quantifying Emergent Phenotypic and Genotypic Diversity in an OpenEnded Substrate
Sanyam Jain, Felix Simon Reimers, Stefano Nichele
We study an in-silico substrate in which every pixel of a two-channel cellular-automata grid carries a tiny neural network (an agent) that senses its Moore neighborhood. A cell per…
Exploring napping paradigm for Recurrent Spiking Neural Networks
Andreas Massey, Stefano Nichele, Aliaksandr Hubin
Biological organisms minimize free energy by balancing two competing demands on their internal world model: it must be accurate enough to predict sensory input, yet simple enough t…
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…
Sleep-Based Homeostatic Regularization for Stabilizing Spike-Timing-Dependent Plasticity in Recurrent Spiking Neural Networks
Andreas Massey, Aliaksandr Hubin, Stefano Nichele +1
Spike-timing-dependent plasticity (STDP) provides a biologically-plausible learning mechanism for spiking neural networks (SNNs); however, Hebbian weight updates in architectures w…
Benchmarking the State of Networks with a Low-Cost Method Based on Reservoir Computing
Felix Simon Reimers, Carl-Hendrik Peters, Stefano Nichele
Using data from mobile network utilization in Norway, we showcase the possibility of monitoring the state of communication and mobility networks with a non-invasive, low-cost metho…
Reservoir Computing with Evolved Critical Neural Cellular Automata
Sidney Pontes-Filho, Stefano Nichele, Mikkel Lepperød
Criticality is a behavioral state in dynamical systems that is known to present the highest computation capabilities, i.e., information transmission, storage, and modification. The…
Frequency-Histogram Coarse Graining in Elementary Cellular Automata and 2D CA
Sanyam Jain, Stefano Nichele
Cellular automata and other discrete dynamical systems have long been studied as models of emergent complexity. Recently, neural cellular automata have been proposed as models to i…
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…
A Sensitivity Analysis of Cellular Automata and Heterogeneous Topology Networks: Partially-Local Cellular Automata and Homogeneous Homogeneous Random Boolean Networks
Tom Eivind Glover, Ruben Jahren, Francesco Martinuzzi +2
Elementary Cellular Automata (ECA) are a well-studied computational universe that is, despite its simple configurations, capable of impressive computational variety. Harvesting thi…
Emergent Dynamics in Heterogeneous Life-Like Cellular Automata
Aarati Shrestha, Felix Reimers, Sanyam Jain +4
The Game of Life (GoL), one well known 2D cellular automaton, does not typically ensure interesting long-term phenotypic dynamics. Therefore, while being Turing complete, GoL canno…
On when is Reservoir Computing with Cellular Automata Beneficial?
Tom Glover, Evgeny Osipov, Stefano Nichele
Reservoir Computing with Cellular Automata (ReCA) is a relatively novel and promising approach. It consists of 3 steps: an encoding scheme to inject the problem into the CA, the CA…
Capturing Emerging Complexity in Lenia
Sanyam Jain, Aarati Shrestha, Stefano Nichele
This research project investigates Lenia, an artificial life platform that simulates ecosystems of digital creatures. Lenia's ecosystem consists of simple, artificial organisms tha…