Paper Citation Record · LEDGER

MAGNET-KG: Maximum-Entropy Geometric Networks for Temporal Knowledge Graphs: Theoretical Foundations and Mathematical Framework

As of 18 August 2026, this Paper Citation Record lists 44 of 44 outbound references and 0 inbound Pith citation observations for arXiv:2509.10587.

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pith.paper-citation-record.v1
2509.10587 v1

Coverage vector

measured 44 of 44 reference resolution

Typed states for the displayed outbound observations.

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One-hop event checks from named stored sources.

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Pith citing papers itemized under the disclosed page cap.

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Reference resolution

44 of 44 outbound references displayed

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Outbound references

Observation a1d78851-215d-4d0a-b374-be02728b274e · outbound

This paper cites write newline.

MAGNET-KG: Maximum-Entropy Geometric Networks for Temporal Knowledge Graphs: Theoretical Foundations and Mathematical Framework write newline

Reference 1

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This paper cites @esa (Ref.

MAGNET-KG: Maximum-Entropy Geometric Networks for Temporal Knowledge Graphs: Theoretical Foundations and Mathematical Framework @esa (Ref

Reference 2

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MAGNET-KG: Maximum-Entropy Geometric Networks for Temporal Knowledge Graphs: Theoretical Foundations and Mathematical Framework Unresolved cited work

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MAGNET-KG: Maximum-Entropy Geometric Networks for Temporal Knowledge Graphs: Theoretical Foundations and Mathematical Framework Unresolved cited work

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This paper cites Lectures on functional equations and their applications, volume 19.

MAGNET-KG: Maximum-Entropy Geometric Networks for Temporal Knowledge Graphs: Theoretical Foundations and Mathematical Framework Lectures on functional equations and their applications, volume 19

Reference 5

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MAGNET-KG: Maximum-Entropy Geometric Networks for Temporal Knowledge Graphs: Theoretical Foundations and Mathematical Framework Neural network learning: Theoretical foundations

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MAGNET-KG: Maximum-Entropy Geometric Networks for Temporal Knowledge Graphs: Theoretical Foundations and Mathematical Framework Variational convergence for functions and operators

Reference 7

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MAGNET-KG: Maximum-Entropy Geometric Networks for Temporal Knowledge Graphs: Theoretical Foundations and Mathematical Framework Information and exponential families: in statistical theory

Reference 8

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This paper cites Rademacher and G aussian complexities: Risk bounds and structural results.

MAGNET-KG: Maximum-Entropy Geometric Networks for Temporal Knowledge Graphs: Theoretical Foundations and Mathematical Framework Rademacher and G aussian complexities: Risk bounds and structural results

Reference 9

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MAGNET-KG: Maximum-Entropy Geometric Networks for Temporal Knowledge Graphs: Theoretical Foundations and Mathematical Framework Rate distortion theory: A mathematical basis for data compression

Reference 10

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MAGNET-KG: Maximum-Entropy Geometric Networks for Temporal Knowledge Graphs: Theoretical Foundations and Mathematical Framework Concentration inequalities: A nonasymptotic theory of independence

Reference 11

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This paper cites On L ipschitz embedding of finite metric spaces in H ilbert space.

MAGNET-KG: Maximum-Entropy Geometric Networks for Temporal Knowledge Graphs: Theoretical Foundations and Mathematical Framework On L ipschitz embedding of finite metric spaces in H ilbert space

Reference 12

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This paper cites Convex optimization.

MAGNET-KG: Maximum-Entropy Geometric Networks for Temporal Knowledge Graphs: Theoretical Foundations and Mathematical Framework Convex optimization

Reference 13

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This paper cites Introduction to strong mixing conditions, volume 1.

MAGNET-KG: Maximum-Entropy Geometric Networks for Temporal Knowledge Graphs: Theoretical Foundations and Mathematical Framework Introduction to strong mixing conditions, volume 1

Reference 14

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MAGNET-KG: Maximum-Entropy Geometric Networks for Temporal Knowledge Graphs: Theoretical Foundations and Mathematical Framework Hyperbolic graph convolutional neural networks

Reference 15

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This paper cites Refh: A reference-based framework for hyperbolic knowledge graph embeddings.

MAGNET-KG: Maximum-Entropy Geometric Networks for Temporal Knowledge Graphs: Theoretical Foundations and Mathematical Framework Refh: A reference-based framework for hyperbolic knowledge graph embeddings

Reference 16

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MAGNET-KG: Maximum-Entropy Geometric Networks for Temporal Knowledge Graphs: Theoretical Foundations and Mathematical Framework Elements of information theory

Reference 17

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MAGNET-KG: Maximum-Entropy Geometric Networks for Temporal Knowledge Graphs: Theoretical Foundations and Mathematical Framework Analysis of survival data, volume 21

Reference 18

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MAGNET-KG: Maximum-Entropy Geometric Networks for Temporal Knowledge Graphs: Theoretical Foundations and Mathematical Framework An introduction to the theory of point processes: volume I : elementary theory and methods

Reference 19

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MAGNET-KG: Maximum-Entropy Geometric Networks for Temporal Knowledge Graphs: Theoretical Foundations and Mathematical Framework Differential geometry of curves and surfaces, volume 2

Reference 20

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MAGNET-KG: Maximum-Entropy Geometric Networks for Temporal Knowledge Graphs: Theoretical Foundations and Mathematical Framework Hyperbolic groups

Reference 21

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MAGNET-KG: Maximum-Entropy Geometric Networks for Temporal Knowledge Graphs: Theoretical Foundations and Mathematical Framework The minimum description length principle

Reference 22

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MAGNET-KG: Maximum-Entropy Geometric Networks for Temporal Knowledge Graphs: Theoretical Foundations and Mathematical Framework Dyre: A dynamic reasoning network for temporal knowledge graph completion

Reference 23

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MAGNET-KG: Maximum-Entropy Geometric Networks for Temporal Knowledge Graphs: Theoretical Foundations and Mathematical Framework Chronor: A time-aware embedding model for temporal knowledge graph completion

Reference 24

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MAGNET-KG: Maximum-Entropy Geometric Networks for Temporal Knowledge Graphs: Theoretical Foundations and Mathematical Framework Roth: Relation-wise rotation for hyperbolic knowledge graph embedding

Reference 25

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MAGNET-KG: Maximum-Entropy Geometric Networks for Temporal Knowledge Graphs: Theoretical Foundations and Mathematical Framework Spectra of some self-exciting and mutually exciting point processes

Reference 26

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MAGNET-KG: Maximum-Entropy Geometric Networks for Temporal Knowledge Graphs: Theoretical Foundations and Mathematical Framework Probability theory: the logic of science

Reference 27

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MAGNET-KG: Maximum-Entropy Geometric Networks for Temporal Knowledge Graphs: Theoretical Foundations and Mathematical Framework Gevrey stability of hydrostatic approximate for the Navier-Stokes equations in a thin domain

Reference 28

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MAGNET-KG: Maximum-Entropy Geometric Networks for Temporal Knowledge Graphs: Theoretical Foundations and Mathematical Framework The Lyman Alpha Reference Sample XI: Efficient Turbulence Driven Ly{\alpha} Escape and the Analysis of IR, CO and [C II]158 {\mu}m

Reference 29

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MAGNET-KG: Maximum-Entropy Geometric Networks for Temporal Knowledge Graphs: Theoretical Foundations and Mathematical Framework Introduction to R iemannian manifolds , volume 176

Reference 30

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MAGNET-KG: Maximum-Entropy Geometric Networks for Temporal Knowledge Graphs: Theoretical Foundations and Mathematical Framework xerte: a cross-modal entity and relation type enhanced model for temporal knowledge graph completion

Reference 31

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MAGNET-KG: Maximum-Entropy Geometric Networks for Temporal Knowledge Graphs: Theoretical Foundations and Mathematical Framework On the method of bounded differences

Reference 32

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MAGNET-KG: Maximum-Entropy Geometric Networks for Temporal Knowledge Graphs: Theoretical Foundations and Mathematical Framework Foundations of machine learning

Reference 33

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MAGNET-KG: Maximum-Entropy Geometric Networks for Temporal Knowledge Graphs: Theoretical Foundations and Mathematical Framework Poincar \'e embeddings for learning hierarchical representations

Reference 34

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MAGNET-KG: Maximum-Entropy Geometric Networks for Temporal Knowledge Graphs: Theoretical Foundations and Mathematical Framework A generalization of the probit and logit methods for dose response curves

Reference 35

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MAGNET-KG: Maximum-Entropy Geometric Networks for Temporal Knowledge Graphs: Theoretical Foundations and Mathematical Framework Convex analysis

Reference 36

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MAGNET-KG: Maximum-Entropy Geometric Networks for Temporal Knowledge Graphs: Theoretical Foundations and Mathematical Framework Variational analysis, volume 317

Reference 37

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MAGNET-KG: Maximum-Entropy Geometric Networks for Temporal Knowledge Graphs: Theoretical Foundations and Mathematical Framework On the density of families of sets

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MAGNET-KG: Maximum-Entropy Geometric Networks for Temporal Knowledge Graphs: Theoretical Foundations and Mathematical Framework A mathematical theory of communication

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MAGNET-KG: Maximum-Entropy Geometric Networks for Temporal Knowledge Graphs: Theoretical Foundations and Mathematical Framework Rotate: Knowledge graph embedding by relational rotation in complex space

Reference 40

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MAGNET-KG: Maximum-Entropy Geometric Networks for Temporal Knowledge Graphs: Theoretical Foundations and Mathematical Framework Asymptotic statistics, volume 3

Reference 41

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MAGNET-KG: Maximum-Entropy Geometric Networks for Temporal Knowledge Graphs: Theoretical Foundations and Mathematical Framework Statistical learning theory, volume 1

Reference 42

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MAGNET-KG: Maximum-Entropy Geometric Networks for Temporal Knowledge Graphs: Theoretical Foundations and Mathematical Framework Maximum likelihood estimation of misspecified models

Reference 43

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MAGNET-KG: Maximum-Entropy Geometric Networks for Temporal Knowledge Graphs: Theoretical Foundations and Mathematical Framework Rates of convergence for empirical processes of stationary mixing sequences

Reference 44

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