activity
20212026
most citedAssessing aesthetics of generated abstract images using correlation structure

2 citations · 2 across the 6 of their papers we have counts for

collaborators

7 papers

cs.LG2026

Architecture Generalization with MetaNCA

Meet Barot, Daniel Berenberg, Sina Khajehabdollahi

Self-organization is an emergent property of life, driven by the collective behavior of individual components acting on local information. Biological neurons, through local interac…

cs.NE2026

Distilling a Modular Reservoir Through a Genomic Bottleneck

Mani Hamidi, Sina Khajehabdollahi, Charley M. Wu +1

The intricate structures of biological neural networks largely emerge during development, guided by a comparatively compressed blueprint encoded in the genome. The connectivity tha…

cs.AI2025

Expedition & Expansion: Leveraging Semantic Representations for Goal-Directed Exploration in Continuous Cellular Automata

Sina Khajehabdollahi, Gautier Hamon, Marko Cvjetko +3

Discovering diverse visual patterns in continuous cellular automata (CA) is challenging due to the vastness and redundancy of high-dimensional behavioral spaces. Traditional explor…

cs.NE2024

Modular Growth of Hierarchical Networks: Efficient, General, and Robust Curriculum Learning

Mani Hamidi, Sina Khajehabdollahi, Emmanouil Giannakakis +3

Structural modularity is a pervasive feature of biological neural networks, which have been linked to several functional and computational advantages. Yet, the use of modular archi…

q-bio.NC2024

Network bottlenecks and task structure control the evolution of interpretable learning rules in a foraging agent

Emmanouil Giannakakis, Sina Khajehabdollahi, Anna Levina

Developing reliable mechanisms for continuous local learning is a central challenge faced by biological and artificial systems. Yet, how the environmental factors and structural co…

cs.NE2023

Emergent mechanisms for long timescales depend on training curriculum and affect performance in memory tasks

Sina Khajehabdollahi, Roxana Zeraati, Emmanouil Giannakakis +3

Recurrent neural networks (RNNs) in the brain and in silico excel at solving tasks with intricate temporal dependencies. Long timescales required for solving such tasks can arise f…