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A Generalization of Amari's Bayesian Duality

Paper recorded by Signals 4 on 2026-09-08 in cs.AI. Abstract reproduced from arXiv; link to the original below.

Published 2026-09-08 on arXiv · recorded by Signals 4 on 2026-09-09

Category: cs.AI · 人工智能 · first seen 2026-09-09

Abstract

Amari's contributions to information geometry and machine learning are well known. Here, we revisit Amari's work on Bayesian duality which has not received as much attention. We connect Amari's Bayesian duality to a convex duality of Bayes' rule. Using this connection, we present a generalization of Amari's Bayesian duality and discuss its relevance for modern artificial intelligence.

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#147 most recent of 300 cs.AI papers we have recorded · ↑ newer: ExecCritic: Learn to Test, Test to Improve for Coding Agents · ↓ older: Canonical Color as a Lens into Concept Decodability in Vision Encoders
Cite this page: A Generalization of Amari's Bayesian Duality: the #147 most recent of 300 cs.AI papers we have recorded (as of 2026-09-08). Source: Signals 4 (Signals API) — https://data.jiangzhang.ca/signals4/t/papers/a-generalization-of-amari-s-bayesian-duality.html
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