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20232026
most citedGetting aligned on representational alignment

35 citations · 43 across the 11 of their papers we have counts for

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6 papers · 1 filter

cs.NE2026

The Principle of Maximum Heterogeneity Optimises Productivity in Distributed Production Systems Across Biology, Economics, and Computing

Guillhem Artis, Danyal Akarca, Jascha Achterberg

The world is full of systems of distributed agents, collaborating and competing in complex ways: firms and workers specialise within economies, neurons adapt their tuning across br…

cs.NE2025

Algorithm-hardware co-design of neuromorphic networks with dual memory pathways

Pengfei Sun, Zhe Su, Jascha Achterberg +3

Spiking neural networks excel at event-driven sensing. Yet, maintaining task-relevant context over long timescales both algorithmically and in hardware, while respecting both tight…

cs.NE2025

Exploiting heterogeneous delays for efficient computation in low-bit neural networks

Pengfei Sun, Jascha Achterberg, Zhe Su +2

Neural networks rely on learning synaptic weights. However, this overlooks other neural parameters that can also be learned and may be utilized by the brain. One such parameter is…

cs.NE2024★ 1 cited

Spatial embedding promotes a specific form of modularity with low entropy and heterogeneous spectral dynamics

Cornelia Sheeran, Andrew S. Ham, Duncan E. Astle +2

Understanding how biological constraints shape neural computation is a central goal of computational neuroscience. Spatially embedded recurrent neural networks provide a promising…

cs.NE2023★ 5 cited

Brain-inspired learning in artificial neural networks: a review

Samuel Schmidgall, Jascha Achterberg, Thomas Miconi +4

Artificial neural networks (ANNs) have emerged as an essential tool in machine learning, achieving remarkable success across diverse domains, including image and speech generation,…

cs.NE2023★ 1 cited

Building artificial neural circuits for domain-general cognition: a primer on brain-inspired systems-level architecture

Jascha Achterberg, Danyal Akarca, Moataz Assem +3

There is a concerted effort to build domain-general artificial intelligence in the form of universal neural network models with sufficient computational flexibility to solve a wide…