4 papers
Weight-Space Linear Recurrent Neural Networks
Roussel Desmond Nzoyem, Nawid Keshtmand, Enrique Crespo Fernandez +4
We introduce WARP (Weight-space Adaptive Recurrent Prediction), a simple yet powerful model that unifies weight-space learning with linear recurrence to redefine sequence modeling.…
Neural Context Flows for Meta-Learning of Dynamical Systems
Roussel Desmond Nzoyem, David A. W. Barton, Tom Deakin
Neural Ordinary Differential Equations (NODEs) often struggle to adapt to new dynamic behaviors caused by parameter changes in the underlying physical system, even when these dynam…
Towards Foundational Models for Dynamical System Reconstruction: Hierarchical Meta-Learning via Mixture of Experts
Roussel Desmond Nzoyem, Grant Stevens, Amarpal Sahota +2
As foundational models reshape scientific discovery, a bottleneck persists in dynamical system reconstruction (DSR): the ability to learn across system hierarchies. Many meta-learn…
Reevaluating Meta-Learning Optimization Algorithms Through Contextual Self-Modulation
Roussel Desmond Nzoyem, David A. W. Barton, Tom Deakin
Contextual Self-Modulation (CSM) (Nzoyem et al., 2025) is a potent regularization mechanism for Neural Context Flows (NCFs) which demonstrates powerful meta-learning on physical sy…