35 citations · 43 across the 11 of their papers we have counts for
4 papers · 1 filter
Accelerated AI Inference via Dynamic Execution Methods
Haim Barad, Jascha Achterberg, Tien Pei Chou +1
In this paper, we focus on Dynamic Execution techniques that optimize the computation flow based on input. This aims to identify simpler problems that can be solved using fewer res…
Dynamical similarity analysis can identify compositional dynamics developing in RNNs
Quentin Guilhot, Michał Wójcik, Jascha Achterberg +1
Methods for analyzing representations in neural systems have become a popular tool in both neuroscience and mechanistic interpretability. Having measures to compare how similar act…
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…
Multilevel Interpretability Of Artificial Neural Networks: Leveraging Framework And Methods From Neuroscience
Zhonghao He, Jascha Achterberg, Katie Collins +13
As deep learning systems are scaled up to many billions of parameters, relating their internal structure to external behaviors becomes very challenging. Although daunting, this pro…