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Paper Citation Record · LEDGER

Variational methods for Learning Multilevel Genetic Algorithms using the Kantorovich Monad

As of 23 August 2026, this Paper Citation Record lists 27 of 27 outbound references and 0 inbound Pith citation observations for arXiv:2411.09779.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2411.09779 v1

Coverage vector

measured 27 of 27 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-12T20:27:15.912616Z

measured 27 of 27 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-23T06:30:58.430688+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: cited_works

Reference resolution

27 of 27 outbound references displayed

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External citation measurements

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Outbound references

Observation 0ecb6a64-732a-4ce2-94ab-48d476884afa · outbound

This paper cites The major transitions in evolution revisited.

Variational methods for Learning Multilevel Genetic Algorithms using the Kantorovich Monad The major transitions in evolution revisited

Reference 1

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This paper cites Evolution and the levels of selection.

Variational methods for Learning Multilevel Genetic Algorithms using the Kantorovich Monad Evolution and the levels of selection

Reference 2

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Variational methods for Learning Multilevel Genetic Algorithms using the Kantorovich Monad Cancer and the levels of selection

Reference 3

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This paper cites Compositional evolution: the impact of sex, symbiosis and modularity on the gradualist framework of evolution.

Variational methods for Learning Multilevel Genetic Algorithms using the Kantorovich Monad Compositional evolution: the impact of sex, symbiosis and modularity on the gradualist framework of evolution

Reference 4

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Observation 561479ad-a990-4c34-b7f3-7e873a26b39a · outbound

This paper cites Hierarchically consistent test problems for genetic algorithms.

Variational methods for Learning Multilevel Genetic Algorithms using the Kantorovich Monad Hierarchically consistent test problems for genetic algorithms

Reference 5

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Variational methods for Learning Multilevel Genetic Algorithms using the Kantorovich Monad Evolution of cooperation by multilevel selection

Reference 6

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Observation 41cc9fe6-4df6-4b3d-b11b-c0857b5068e3 · outbound

This paper cites The generalized Price equation: forces that change population statistics.

Variational methods for Learning Multilevel Genetic Algorithms using the Kantorovich Monad The generalized Price equation: forces that change population statistics

Reference 7

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Observation 2343e9e8-b8d0-4665-8157-14135c28206e · outbound

This paper cites Cyclic and multilevel causation in evolutionary pro- cesses.

Variational methods for Learning Multilevel Genetic Algorithms using the Kantorovich Monad Cyclic and multilevel causation in evolutionary pro- cesses

Reference 8

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Observation 309f579e-e945-446d-8162-fc77f2917673 · outbound

This paper cites The metric monad for probabilistic nondeterminism.

Variational methods for Learning Multilevel Genetic Algorithms using the Kantorovich Monad The metric monad for probabilistic nondeterminism

Reference 9

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This paper cites Wasserstein Auto-Encoders.

Variational methods for Learning Multilevel Genetic Algorithms using the Kantorovich Monad Wasserstein Auto-Encoders

Reference 10

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Observation d4b43ce0-d3af-4127-b8db-37b9bbaa3f5f · outbound

This paper cites Inferring phylogenies.

Variational methods for Learning Multilevel Genetic Algorithms using the Kantorovich Monad Inferring phylogenies

Reference 11

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Observation 08956d42-700f-4048-bd06-c970010e80d9 · outbound

This paper cites Variational combinatorial sequential Monte Carlo methods for Bayesian phylogenetic inference.

Variational methods for Learning Multilevel Genetic Algorithms using the Kantorovich Monad Variational combinatorial sequential Monte Carlo methods for Bayesian phylogenetic inference

Reference 12

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Variational methods for Learning Multilevel Genetic Algorithms using the Kantorovich Monad Variational Bayesian phylogenetic inference

Reference 13

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Variational methods for Learning Multilevel Genetic Algorithms using the Kantorovich Monad Improved variational Bayesian phylogenetic inference with normalizing flows

Reference 14

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Observation deac4a98-db94-48c4-9f25-a6f07dd5e5db · outbound

This paper cites Smoothing-based optimization.

Variational methods for Learning Multilevel Genetic Algorithms using the Kantorovich Monad Smoothing-based optimization

Reference 15

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This paper cites Evolutionary Theory: Mathematical and conceptual foundations.

Variational methods for Learning Multilevel Genetic Algorithms using the Kantorovich Monad Evolutionary Theory: Mathematical and conceptual foundations

Reference 16

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This paper cites How Many Levels Are There? How Insights from Evolutionary Transitions in Individuality Help Measure the Hierarchical Complexity of Life.

Variational methods for Learning Multilevel Genetic Algorithms using the Kantorovich Monad How Many Levels Are There? How Insights from Evolutionary Transitions in Individuality Help Measure the Hierarchical Complexity of Life

Reference 17

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Variational methods for Learning Multilevel Genetic Algorithms using the Kantorovich Monad Stochastic optimization, stochastic approximation and simulated annealing

Reference 18

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Variational methods for Learning Multilevel Genetic Algorithms using the Kantorovich Monad A review of Monte Carlo-based versions of the EM algorithm

Reference 19

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This paper cites Passenger mutations in more than 2,500 cancer genomes: overall molecular functional impact and consequences.

Variational methods for Learning Multilevel Genetic Algorithms using the Kantorovich Monad Passenger mutations in more than 2,500 cancer genomes: overall molecular functional impact and consequences

Reference 20

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Variational methods for Learning Multilevel Genetic Algorithms using the Kantorovich Monad Estimating growth patterns and driver effects in tumor evolution from individual samples

Reference 21

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This paper cites Lineage tracing reveals the phylodynamics, plasticity, and paths of tumor evolution.

Variational methods for Learning Multilevel Genetic Algorithms using the Kantorovich Monad Lineage tracing reveals the phylodynamics, plasticity, and paths of tumor evolution

Reference 22

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This paper cites CloneSig can jointly infer intra-tumor heterogeneity and mutational signature activity in bulk tumor sequencing data.

Variational methods for Learning Multilevel Genetic Algorithms using the Kantorovich Monad CloneSig can jointly infer intra-tumor heterogeneity and mutational signature activity in bulk tumor sequencing data

Reference 23

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Variational methods for Learning Multilevel Genetic Algorithms using the Kantorovich Monad Microbial life history: the fundamental forces of biological design

Reference 24

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Variational methods for Learning Multilevel Genetic Algorithms using the Kantorovich Monad The information theory of individuality

Reference 25

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Variational methods for Learning Multilevel Genetic Algorithms using the Kantorovich Monad Implicit bilevel optimization: differentiating through bilevel optimization programming

Reference 26

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This paper cites Position: Categorical Deep Learning is an Algebraic Theory of All Architectures.

Variational methods for Learning Multilevel Genetic Algorithms using the Kantorovich Monad Position: Categorical Deep Learning is an Algebraic Theory of All Architectures

Reference 27

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