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Towards AGI
  • Home
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  • Topics&Papers
    • Adversarial Robustness
    • Alignment and Safety
    • CompPsych-FoMo
    • Compression and Fast Inference
    • Continual Learning at Scale
    • Emergence & Phase Transitions in ML
    • Foundation Models
    • Generalization (iid and ood)
    • High Performance Computing
    • Knowledge Fusion
    • Neural Scaling Laws
    • Out-of-Distribution Generalization
    • Scaling Laws in Nature
    • State Space Models
    • Time Series Foundation Models
Towards AGI
  • Home
  • Schedule
  • Topics&Papers
    • Adversarial Robustness
    • Alignment and Safety
    • CompPsych-FoMo
    • Compression and Fast Inference
    • Continual Learning at Scale
    • Emergence & Phase Transitions in ML
    • Foundation Models
    • Generalization (iid and ood)
    • High Performance Computing
    • Knowledge Fusion
    • Neural Scaling Laws
    • Out-of-Distribution Generalization
    • Scaling Laws in Nature
    • State Space Models
    • Time Series Foundation Models
  • More
    • Home
    • Schedule
    • Topics&Papers
      • Adversarial Robustness
      • Alignment and Safety
      • CompPsych-FoMo
      • Compression and Fast Inference
      • Continual Learning at Scale
      • Emergence & Phase Transitions in ML
      • Foundation Models
      • Generalization (iid and ood)
      • High Performance Computing
      • Knowledge Fusion
      • Neural Scaling Laws
      • Out-of-Distribution Generalization
      • Scaling Laws in Nature
      • State Space Models
      • Time Series Foundation Models

Scaling  Laws  in  Nature

Scaling laws and persistence in human brain activity

Neuronal long-range temporal correlations and avalanche dynamics are correlated with behavioral scaling laws

Scaling laws in the mammalian neocortex: does form provide clues to function?

A Gentle Introduction to Scaling Laws in Biological Systems 

A Connectomic Hypothesis for the Hominization of the Brain

Critical integration in neural and cognitive systems: Beyond power-law scaling as the hallmark of soft assembly

Critical Truths about Power Laws

Scale invariance in natural and artificial collective systems: a review

Toward an Instance Theory of Automatization 

New studies reveal how autism might alter synapse formation, pruning

More on criticality:

  • Beggs, J. M. (2008). The criticality hypothesis: how local cortical networks might optimize information processing. Philos. Trans. A Math. Phys. Eng. Sci.366, 329–343. doi: 10.1098/rsta.2007.2092

  • Shew, W. L., and Plenz, D. (2013). The functional benefits of criticality in the cortex. Neuroscientist19, 88–100. doi: 10.1177/1073858412445487

  • Shew, W. L., Yang, H., Petermann, T., Roy, R., and Plenz, D. (2009). Neuronal avalanches imply maximum dynamic range in cortical networks at criticality. J. Neurosci.29, 15595–15600. doi: 10.1523/JNEUROSCI.3864-09.2009

  • Shew, W. L., Yang, H., Yu, S., Roy, R., and Plenz, D. (2011). Information capacity and transmission are maximized in balanced cortical networks with neuronal avalanches. J. Neurosci.31, 55–63. doi: 10.1523/JNEUROSCI.4637-10.2011

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