Paper Citation Record · LEDGER

Variational methods for Learning Multilevel Genetic Algorithms using the Kantorovich Monad

As of 15 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 2026-08-15T06:32:42.880941+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

No source-named external measurement is stored.

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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Observation caa4a177-ffed-40bc-bc83-b96f263500d1 · outbound

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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Observation 094e3a02-f3f4-4d2a-b304-f38a408d07fc · outbound

This paper cites Cancer and the levels of selection.

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

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T20:27:16.435468Z

Source-reported events for the cited work

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Observation bf69f481-dc34-484e-819b-e95f62b3d230 · outbound

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

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T20:27:16.418932Z

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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

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T20:27:16.402781Z

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Observation 320e3a46-7146-44ff-9f97-f16c747e52b1 · outbound

This paper cites Evolution of cooperation by multilevel selection.

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

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T20:27:16.385970Z

Source-reported events for the cited work

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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

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T20:27:16.368630Z

Source-reported events for the cited work

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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

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T20:27:16.333854Z

Source-reported events for the cited work

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Observation 474bf042-7f52-4875-a821-ee64deb00ecd · outbound

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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Source-reported events for the cited work

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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

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T20:27:16.314052Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T20:27:16.293986Z

Source-reported events for the cited work

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Observation f48fc126-f29a-46a8-b56f-41426ef2b729 · outbound

This paper cites Variational Bayesian phylogenetic inference.

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

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T20:27:16.273713Z

Source-reported events for the cited work

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Observation bb7c734f-5985-46ef-8502-90f7fca17c78 · outbound

This paper cites Improved variational Bayesian phylogenetic inference with normalizing flows.

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

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T20:27:16.236001Z

Source-reported events for the cited work

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Observation 96a1b231-ee5a-4156-89f6-54b3de712a9b · outbound

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

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T20:27:16.213268Z

Source-reported events for the cited work

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Observation ea0ddf7a-7227-4ae6-bfc2-21cd8b1eeb9c · outbound

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

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T20:27:16.192063Z

Source-reported events for the cited work

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Observation 18579b72-08c1-4312-b53b-fbc636b1e1d2 · outbound

This paper cites Stochastic optimization, stochastic approximation and simulated annealing.

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

Reference 18

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Source-reported events for the cited work

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Observation 426e1f65-a757-4e81-8c0d-da6b894c35fd · outbound

This paper cites A review of Monte Carlo-based versions of the EM algorithm.

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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Observation ec3ce7fd-2059-4196-8b9d-16a17d9abfc4 · outbound

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

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T20:27:16.158537Z

Source-reported events for the cited work

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Observation 8fff98d2-0760-435e-99dc-7a93037f40e0 · outbound

This paper cites Estimating growth patterns and driver effects in tumor evolution from individual samples.

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

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T20:27:16.140690Z

Source-reported events for the cited work

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Observation a94945e1-a8d4-42b2-86e7-558195ed2271 · outbound

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

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T20:27:16.121094Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation d10a25f7-aafc-4751-991d-c1040ebd51ff · outbound

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

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T20:27:16.103676Z

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No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 5a730808-3439-4048-b493-14d010d41712 · outbound

This paper cites Microbial life history: the fundamental forces of biological design.

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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Source-reported events for the cited work

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Observation c6a6a97c-dcfe-4ac9-9f87-a13381f3e7ae · outbound

This paper cites The information theory of individuality.

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

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T20:27:16.043827Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation a13eb2a8-95d5-4285-a4d7-6fa313d2205b · outbound

This paper cites Implicit bilevel optimization: differentiating through bilevel optimization programming.

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

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T20:27:16.024844Z

Source-reported events for the cited work

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Observation 3bd5f20b-76e8-4c7f-9442-db506106759e · outbound

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

Resolution: unresolved; no resolver link, observed 2026-08-12T20:27:15.912616Z

Source-reported events for the cited work

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Pith citing papers

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