Some Results on Neural Network Stability, Consistency, and Convergence: Insights into Non-IID Data, High-Dimensional Settings, and Physics-Informed Neural Networks. - Ronald Katende; Henry Kasumba; Godwin Kakuba; John M. Mango (CoRR, 2024)

Efficient Matrix Decomposition for High-Dimensional Structured Systems: Theory and Applications. - Ronald Katende (CoRR, 2024)

Decentralized Neural Networks for Robust and Scalable Eigenvalue Computation. - Ronald Katende (CoRR, 2024)

Adaptive Error-Bounded Hierarchical Matrices for Efficient Neural Network Compression. - John M. Mango; Ronald Katende (CoRR, 2024)

Optimizing Neural Network Performance and Interpretability with Diophantine Equation Encoding. - Ronald Katende (CoRR, 2024)

Cross-Country Comparative Analysis of Climate Resilience and Localized Mapping in Data-Sparse Regions. - Ronald Katende (CoRR, 2024)

A Nonlinear Generalization of the Bauer-Fike Theorem and Novel Iterative Methods for Solving Nonlinear Eigenvalue Problems. - Ronald Katende (CoRR, 2024)

Symmetry-Enriched Learning: A Category-Theoretic Framework for Robust Machine Learning Models. - Ronald Katende (CoRR, 2024)

Structured Variational D-Decomposition for Accurate and Stable Low-Rank Approximation. - Ronald Katende (CoRR, 2025)

Stability Analysis of Physics-Informed Neural Networks via Variational Coercivity, Perturbation Bounds, and Concentration Estimates. - Ronald Katende (CoRR, 2025)

Causal Operator Discovery in Partial Differential Equations via Counterfactual Physics-Informed Neural Networks. - Ronald Katende (CoRR, 2025)

Variational Geometric Information Bottleneck: Learning the Shape of Understanding. - Ronald Katende (CoRR, 2025)

Preserving Extreme Singular Values with One Oblivious Sketch. - John M. Mango; Ronald Katende (CoRR, 2025)

Interpretive Efficiency: Information-Geometric Foundations of Data Usefulness. - Ronald Katende (CoRR, 2025)

Analytic and Variational Stability of Deep Learning Systems. - Ronald Katende (CoRR, 2025)

Why Smooth Stability Assumptions Fail for ReLU Learning. - Ronald Katende (CoRR, 2025)

A Frobenius-Optimal Projection for Enforcing Linear Conservation in Learned Dynamical Models. - John M. Mango; Ronald Katende (CoRR, 2025)

Non-asymptotic stability and consistency guarantees for physics-informed neural networks via coercive operator analysis. - Ronald Katende (Commun. Nonlinear Sci. Numer. Simul., 2026)

A Unified Matrix-Spectral Framework for Stability and Interpretability in Deep Learning. - Ronald Katende (CoRR, 2026)

A Function-Space Stability Boundary for Generalization in Interpolating Learning Systems. - Ronald Katende (CoRR, 2026)