From the 2 of 13 linked papers with an AI index.
13 papers
Learning in Infinitesimal Non-Compositional Sketches
Sridhar Mahadevan
The paper proposes a categorical framework called LINCS that models machine learning problems as sketches and addresses non‑compositionality by lifting these sketches to tangent ca…
Agentic Skill Optimization over Lie Algebroids
Sridhar Mahadevan
The paper introduces LASKO, a Lie algebroid‑based framework for optimizing agentic skill edits (e.g., prompts, rubrics) by modeling edit policies as sections of a controlled Lie al…
Odyssey: Constructing Verifiable Local Truth-Preserving Foundation Models
Sridhar Mahadevan
We introduce a categorical framework called ODYSSEY for constructing verifiable, local truth-preserving foundation models as compositions of foundries: building-block architectural…
Infinitesimal Causality
Sridhar Mahadevan
Interventions can be varied continuously in many causal models. Differentiating a specified smooth intervention protocol produces vector fields on a statistical model, and their Li…
Latent Confounded Causal Discovery via Lie Bracket Geometry
Sridhar Mahadevan
We study causal discovery from observational and interventional regimes when latent variables may affect the measured system. Our first algorithm, BRIDGE (Bracket Residuals for Int…
Causal Density Functions
Sridhar Mahadevan
We study the full density ratio between a specified intervention regime and an observational regime , , under the prerequisite . We call the…