5 papers · 1 filter
From Performance to Representational Adequacy: A Representational Bootstrap Framework for Adaptive Biological Systems
Jacques Raynal, Pierre Slangen, Elsa Raynal +1
Observable performance is commonly used to characterize biological systems, yet aggregated outputs may remain insufficient for uniquely resolving observational conditions, and rich…
Detecting Explanatory Insufficiency in Learned Representations: A Framework for Representational Vigilance
Jacques Raynal, Pierre Slangen, Elsa Raynal +1
Learned representations are commonly evaluated through predictive performance, calibration, robustness, uncertainty estimation, and behavior under distribution shift. Yet these cri…
Bootstrap Theory of Representational Emergence (TBER): Explanatory Insufficiency, Transition Regimes, and the Emergence of New Representational Levels
Jacques Raynal, Pierre Slangen, Elsa Raynal +1
Representation learning is central to modern machine learning, yet most research focuses on optimizing representations after a framework has been selected. The Bootstrap Theory of…
From Observed Viability to Internal Predictive Approximation: A Single-Subject Latent-Space Analysis of Gait Dynamics Under Occlusal Constraint
Jacques Raynal, Pierre Slangen, Elsa Raynal +1
Understanding adaptive biomechanical systems requires distinguishing observable performance, static multivariate representation, longitudinal displacement, and internal approximati…
Observable Performance Does Not Fully Reflect Adaptive System Organization: A Multi-Level Analysis of Gait Dynamics Under Occlusal Constraint
Jacques Raynal, Pierre Slangen, Elsa Raynal +1
In biomechanical systems, observable performance is often used as a proxy for underlying organization, although similar outputs may arise from different adaptive configurations. Th…