3 citations · 3 across the 7 of their papers we have counts for
3 papers · 1 filter
Integral Signatures of Activation Functions: A 9-Dimensional Taxonomy and Stability Theory for Deep Learning
Ankur Mali, Lawrence Hall, Jake Williams +1
Activation functions govern the expressivity and stability of neural networks, yet existing comparisons remain largely heuristic. We propose a rigorous framework for their classifi…
Bridging Predictive Coding and MDL: A Two-Part Code Framework for Deep Learning
Benjamin Prada, Shion Matsumoto, Abdul Malik Zekri +1
We present the first theoretical framework that connects predictive coding (PC), a biologically inspired local learning rule, with the minimum description length (MDL) principle in…
TeLU Activation Function for Fast and Stable Deep Learning
Alfredo Fernandez, Ankur Mali
We propose the Hyperbolic Tangent Exponential Linear Unit (TeLU), a neural network hidden activation function defined as TeLU(x)=xtanh(exp(x)). TeLU's design is grounded in the cor…