3 citations · 4 across the 13 of their papers we have counts for
7 papers · 1 filter
What Must Survive? Exact Task-Information--State Frontiers Under Partial Task Revelation
Ronald Katende
A state may need to be compressed before its exact downstream task is known. For a finite family of linear task operators $\{T_u\}_{u\in\U}$, we characterize exactly how much state…
Interpretive Efficiency: Information-Geometric Foundations of Data Usefulness
Ronald Katende
Interpretability is central to trustworthy machine learning, yet existing metrics rarely quantify how effectively data support an interpretive representation. We propose Interpreti…
Geometry as a Missing Axis of Representation Quality: The Variational Geometric Information Bottleneck under Data Scarcity
Ronald Katende
We study latent geometry as an explicit component of representation quality in data-scarce learning. For an encoder (ϕ), we define (Q_{β,γ}(ϕ)=I(ϕ(X);Y)-β\mathcal C(ϕ)-γd_{\mathrm{…
Counterfactual Operator Relevance for PDE Discovery: Screening, Pruning, and Identifiability
Ronald Katende
We study operator relevance in data-driven partial differential equation (PDE) discovery. Sparse residual methods can select terms that improve residual fit, but residual contribut…
Decentralized Neural Networks for Robust and Scalable Eigenvalue Computation
Ronald Katende
This paper introduces a novel method for eigenvalue computation using a distributed cooperative neural network framework. Unlike traditional techniques that face scalability challe…
Symmetry-Enriched Learning: A Category-Theoretic Framework for Robust Machine Learning Models
Ronald Katende
This manuscript presents a novel framework that integrates higher-order symmetries and category theory into machine learning. We introduce new mathematical constructs, including hy…
Optimizing Neural Network Performance and Interpretability with Diophantine Equation Encoding
Ronald Katende
This paper explores the integration of Diophantine equations into neural network (NN) architectures to improve model interpretability, stability, and efficiency. By encoding and de…