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Found 4 papers, 2 papers with code
Emerging-properties Mapping Using Spatial Embedding Statistics: EMUSES
Understanding complex phenomena often requires analyzing high-dimensional data to uncover emergent properties that arise from multifactorial interactions.
Cultural evolution in populations of Large Language Models
We here present a framework for simulating cultural evolution in populations of LLMs, allowing the manipulation of variables known to be important in cultural evolution, such as network structure, personality, and the way social information is aggregated and transformed.
Deep Variational Lesion-Deficit Mapping
Here we initiate the application of deep generative neural network architectures to the task of lesion-deficit inference, formulating it as the estimation of an expressive hierarchical model of the joint lesion and deficit distributions conditioned on a latent neural substrate.
Individualized prescriptive inference in ischaemic stroke
The gold standard in the treatment of ischaemic stroke is set by evidence from randomized controlled trials.
