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edge computing

2,370 papers

#edge computing Open access Oct 2026

A C₄-Free Classification of Square Relations on Token Graphs

A C₄-Free Classification of Square Relations on Token Graphs with girth, tree and discretization witnesses Driven by Dean A. Kulik October 2026 Abstract Let FK(X) denote the K-token graph of a finite simple graph X: vertices are the K-subsets of V(X), adjacent when their symmetric difference is an edge. Two families of...

Dean Kulik · 0 citations
#edge computing Open access Oct 2026

Real-Time Two-Stage Screening Framework for UAV Autonomous Landing in Unknown Environments

This study addresses the challenge of autonomous landing of unmanned aerial vehicles (UAVs) in unknown environments by proposing a vision-based system that utilizes a single RGB-D camera. The core of our approach integrates an enhanced real-time semantic segmentation model based on the DDRNet architecture, incorporatin...

Satoshi Suzuki · 0 citations
#edge computing Open access Oct 2026

fgca: Python code and results for "Operator Choice and Echo Artefacts in Fuzzy Graph Cellular Automata for Cascade Spreading on Networks"

Python code and results accompanying the paper "Operator Choice and Echo Artefacts in Fuzzy Graph Cellular Automata for Cascade Spreading on Networks". The code implements a fuzzy graph cellular automaton: nodes of a graph with fuzzy edge memberships carry states in [0, 1] and update synchronously by combining neighbou...

KRISHNA KUMARI RENGANATHAN · 0 citations
#edge computing Open access Oct 2026

fgca: Python code and results for "Operator Choice and Echo Artefacts in Fuzzy Graph Cellular Automata for Cascade Spreading on Networks"

Python code and results accompanying the paper "Operator Choice and Echo Artefacts in Fuzzy Graph Cellular Automata for Cascade Spreading on Networks". The code implements a fuzzy graph cellular automaton: nodes of a graph with fuzzy edge memberships carry states in [0, 1] and update synchronously by combining neighbou...

KRISHNA KUMARI RENGANATHAN · 0 citations
#edge computing Open access Oct 2026

Rank Access and Closure Depth in the Relation-Layer Cohomology of Token Arenas

Rank Access and Closure Depth in the Relation-Layer Cohomology of Token Arenas A refuted conjecture, a refuted mechanism, and two species of invariant harmonic residue Driven by Dean Kulik October 2026 Abstract A Kdisj-type relation layer over a token arena assigns cohomology to a graph by declaring which closed loops...

Dean Kulik · 0 citations
#edge computing Open access Oct 2026

A C₄-Free Classification of Square Relations on Token Graphs

A C₄-Free Classification of Square Relations on Token Graphs with girth, tree and discretization witnesses Driven by Dean A. Kulik October 2026 Abstract Let FK(X) denote the K-token graph of a finite simple graph X: vertices are the K-subsets of V(X), adjacent when their symmetric difference is an edge. Two families of...

Dean Kulik · 0 citations
#edge computing Open access Oct 2026

Exact results for Kerr black holes: shadow areas and perimeters, capture of slow particles, and escape from near extremal horizons

We give exact results for several observables of Kerr black holes that have so far been computed numerically, by fits, or only at isolated parameter values. (i) The area of the shadow seen by an equatorial observer, for every spin, in complete elliptic integrals, together with its small-spin series and its near-extrema...

Jacob Goodchild · 0 citations
#edge computing Open access Oct 2026

Real-Time Two-Stage Screening Framework for UAV Autonomous Landing in Unknown Environments

This study addresses the challenge of autonomous landing of unmanned aerial vehicles (UAVs) in unknown environments by proposing a vision-based system that utilizes a single RGB-D camera. The core of our approach integrates an enhanced real-time semantic segmentation model based on the DDRNet architecture, incorporatin...

Satoshi Suzuki · 0 citations
#edge computing Open access Oct 2026

Real-Time Two-Stage Screening Framework for UAV Autonomous

This study addresses the challenge of autonomous landing of unmanned aerial vehicles (UAVs) in unknown environments by proposing a vision-based system that utilizes a single RGB-D camera. The core of our approach integrates an enhanced real-time semantic segmentation model based on the DDRNet architecture, incorporatin...

Satoshi Suzuki · 0 citations
#edge computing Open access Oct 2026

Architectural reorganization of functional connectivity after propofol anesthesia exceeds within-state measurement variability and is only marginally reversed during early recovery

Propofol anesthesia disrupts functional connectivity, but the magnitude of whole-brain architectural reorganization has not been calibrated against the variability of repeated measurement within a single state, and it is therefore unclear how much apparent reorganization reflects state change rather than estimation noi...

Drake H. Harbert · 0 citations
#edge computing Open access Oct 2026

Readers Are Functionals- Representation Control of the Relation Layer on Token Arenas

Readers Are Functionals- Representation Control of the Relation Layer on Token Arenas a multiplicity table, a faithful-reader certificate, and an isotypic correction to the rank budget Driven by Dean A. Kulik October 2026 Abstract Attaching 2-cells to a token graph and computing invariant cohomology under a symmetry gr...

Dean Kulik · 0 citations
#edge computing Open access Oct 2026

Refinement-Derived Algebraic Computation of Graph Automorphism Groups

We compute the automorphism group of a graph exactly, with a verified generatingset. Inside each class of an invariant colouring, individualisation and refinement yielda permutation group TC that contains the restriction of every automorphism; a normalseries of these groups turns the edges between classes into affine s...

Christos Karatzas · 0 citations

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Microsoft Research Blog Oct 6, 2026

What AI gets wrong and what failure teaches us

Jennifer Neville did not want to go into computer science—but that’s exactly where she landed. Neville discusses the starts and stops that led to her professional sweet spot and her work identifying “surprising failures” making it hard for AI to handle complexity.  The post What AI gets wrong and what failure teaches us appeared first on Microsoft Research.

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