Paper Citation Record · LEDGER

Machine Learning Gravity Compactifications on Negatively Curved Manifolds

As of 20 August 2026, this Paper Citation Record lists 75 of 75 outbound references and 2 inbound Pith citation observations for arXiv:2501.00093.

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

pith.paper-citation-record.v1
2501.00093 v1

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measured 75 of 75 reference resolution

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Pith citing papers itemized under the disclosed page cap.

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Source: arxiv_reference, observed 2026-07-01T16:55:50.610811Z

Reference resolution

75 of 75 outbound references displayed

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Outbound references

Observation 7f8adbf4-f2df-4665-9787-bb3ea87ce880 · outbound

This paper cites de Sitter Vacua in String Theory.

Machine Learning Gravity Compactifications on Negatively Curved Manifolds de Sitter Vacua in String Theory

Reference 1

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Observation fada508c-f6d5-453e-8f28-7fe49b8037bb · outbound

This paper cites Breaking supersymmetry with pure spinors,.

Machine Learning Gravity Compactifications on Negatively Curved Manifolds Breaking supersymmetry with pure spinors,

Reference 2

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Observation 3f894c7a-f1bb-4cab-8570-0c2bb66dc5e1 · outbound

This paper cites Tomasiello,Geometry of String Theory Compactifications.

Machine Learning Gravity Compactifications on Negatively Curved Manifolds Tomasiello,Geometry of String Theory Compactifications

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:10:04.936327Z

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Observation abee8cc4-3a9f-43d9-b4e4-44223cb4289b · outbound

This paper cites Polchinski and E.

Machine Learning Gravity Compactifications on Negatively Curved Manifolds Polchinski and E

Reference 4

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Observation c3349e17-98bf-4b4c-8c8a-d589514b659e · outbound

This paper cites Type IIA Moduli Stabilization.

Machine Learning Gravity Compactifications on Negatively Curved Manifolds Type IIA Moduli Stabilization

Reference 5

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Observation 60909a10-6be0-46b2-951f-f2c0b5e6f8c5 · outbound

This paper cites Scale-separated AdS$_4$ vacua of IIA orientifolds and M-theory.

Machine Learning Gravity Compactifications on Negatively Curved Manifolds Scale-separated AdS$_4$ vacua of IIA orientifolds and M-theory

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-10T23:10:03.712234Z

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Observation 503ebee1-fe5c-4dec-be4b-db3c0647eb1e · outbound

This paper cites Small Cosmological Constants in String Theory.

Machine Learning Gravity Compactifications on Negatively Curved Manifolds Small Cosmological Constants in String Theory

Reference 7

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Observation 681ea13a-fdd1-48ef-be97-65322ac72780 · outbound

This paper cites Gravity from thermodynamics: optimal transport and negative effective dimensions.

Machine Learning Gravity Compactifications on Negatively Curved Manifolds Gravity from thermodynamics: optimal transport and negative effective dimensions

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-10T23:10:03.720099Z

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Observation f4182e55-6ff6-4765-ad12-8cda15d8b760 · outbound

This paper cites Quantum corrections to DGKT and the Weak Gravity Conjecture.

Machine Learning Gravity Compactifications on Negatively Curved Manifolds Quantum corrections to DGKT and the Weak Gravity Conjecture

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-10T23:10:03.723594Z

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Observation df3a23d9-8a9f-4bb6-a50a-78f874ab2aed · outbound

This paper cites Snowmass White Paper: Cosmology at the Theory Frontier.

Machine Learning Gravity Compactifications on Negatively Curved Manifolds Snowmass White Paper: Cosmology at the Theory Frontier

Reference 10

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Observation 05169ba6-cd2d-4cad-8023-b4700cd3c485 · outbound

This paper cites TASI lectures on cosmological observables and string theory,.

Machine Learning Gravity Compactifications on Negatively Curved Manifolds TASI lectures on cosmological observables and string theory,

Reference 11

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Observation 322db0ea-9805-4cd4-a481-6180990cd6a8 · outbound

This paper cites Moduli Stabilization in String Theory.

Machine Learning Gravity Compactifications on Negatively Curved Manifolds Moduli Stabilization in String Theory

Reference 12

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Observation b32ee68b-8bac-420a-802c-c26c604b3329 · outbound

This paper cites New de Sitter Solutions,.

Machine Learning Gravity Compactifications on Negatively Curved Manifolds New de Sitter Solutions,

Reference 13

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Observation 5cacf33e-cba3-428e-b0ed-86dfc78264a4 · outbound

This paper cites Classical de Sitter Solutions of Ten-Dimensional Supergravity.

Machine Learning Gravity Compactifications on Negatively Curved Manifolds Classical de Sitter Solutions of Ten-Dimensional Supergravity

Reference 14

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Observation bb5896cf-2f22-4dc9-8cfc-e6b88b72be6f · outbound

This paper cites New de Sitter Solutions in Ten Dimensions and Orientifold Singularities.

Machine Learning Gravity Compactifications on Negatively Curved Manifolds New de Sitter Solutions in Ten Dimensions and Orientifold Singularities

Reference 15

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Observation f353b3b4-636f-4db9-a184-6b1067b097c2 · outbound

This paper cites 4D de Sitter from String Theory via 6D Supergravity.

Machine Learning Gravity Compactifications on Negatively Curved Manifolds 4D de Sitter from String Theory via 6D Supergravity

Reference 16

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Observation f7480663-7365-4dc0-b376-78a481cc2139 · outbound

This paper cites AdS$_8$ Solutions in Type II Supergravity.

Machine Learning Gravity Compactifications on Negatively Curved Manifolds AdS$_8$ Solutions in Type II Supergravity

Reference 17

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Observation 5c10186b-eaa9-4722-8c2c-35f3e2e05f3a · outbound

This paper cites A new approach to static numerical relativity, and its application to Kaluza-Klein black holes.

Machine Learning Gravity Compactifications on Negatively Curved Manifolds A new approach to static numerical relativity, and its application to Kaluza-Klein black holes

Reference 18

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Observation 3d467e85-721a-4ce9-9c0d-d7c0af08d1be · outbound

This paper cites Numerical Ricci-flat metrics on K3.

Machine Learning Gravity Compactifications on Negatively Curved Manifolds Numerical Ricci-flat metrics on K3

Reference 19

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Observation ce459c51-5d68-4e14-8780-cd89128e1e0d · outbound

This paper cites Numerical Calabi-Yau metrics.

Machine Learning Gravity Compactifications on Negatively Curved Manifolds Numerical Calabi-Yau metrics

Reference 20

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Observation 5838004f-74b1-4611-ac71-c42f860eacb2 · outbound

This paper cites Energy functionals for Calabi-Yau metrics.

Machine Learning Gravity Compactifications on Negatively Curved Manifolds Energy functionals for Calabi-Yau metrics

Reference 21

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Observation e3f9fa6c-485b-4392-9c57-99b672569d29 · outbound

This paper cites Numerical Kaehler-Einstein metric on the third del Pezzo.

Machine Learning Gravity Compactifications on Negatively Curved Manifolds Numerical Kaehler-Einstein metric on the third del Pezzo

Reference 22

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Observation 67188470-d831-49a8-be53-53d6ac00c81a · outbound

This paper cites Physics-informed machine learning,.

Machine Learning Gravity Compactifications on Negatively Curved Manifolds Physics-informed machine learning,

Reference 23

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Observation 70feef4c-b9d3-41b1-b8d6-356dc63f23d7 · outbound

This paper cites Artificial neural networks for solving ordinary and partial differential equations,.

Machine Learning Gravity Compactifications on Negatively Curved Manifolds Artificial neural networks for solving ordinary and partial differential equations,

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:10:04.904126Z

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Observation 03e83c6a-a845-4dcc-9c6b-fae7208a1875 · outbound

This paper cites Bootstrapping string models with entanglement minimization and Machine-Learning.

Machine Learning Gravity Compactifications on Negatively Curved Manifolds Bootstrapping string models with entanglement minimization and Machine-Learning

Reference 25

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Observation 1ae362f1-138a-4776-a059-a1142248c4aa · outbound

This paper cites Machine Learning Toric Duality in Brane Tilings.

Machine Learning Gravity Compactifications on Negatively Curved Manifolds Machine Learning Toric Duality in Brane Tilings

Reference 26

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Observation c5906a83-937e-4410-878f-b1aece2ca272 · outbound

This paper cites The S-matrix bootstrap with neural optimizers I: zero double discontinuity.

Machine Learning Gravity Compactifications on Negatively Curved Manifolds The S-matrix bootstrap with neural optimizers I: zero double discontinuity

Reference 27

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Observation 6e763fd8-fe3b-45aa-863f-3de7de5abc64 · outbound

This paper cites Rigor with Machine Learning from Field Theory to the Poincar\'e Conjecture.

Machine Learning Gravity Compactifications on Negatively Curved Manifolds Rigor with Machine Learning from Field Theory to the Poincar\'e Conjecture

Reference 28

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Observation 0994165f-1b63-4695-869e-d711c285a150 · outbound

This paper cites KAN: Kolmogorov-Arnold Networks.

Machine Learning Gravity Compactifications on Negatively Curved Manifolds KAN: Kolmogorov-Arnold Networks

Reference 29

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Observation 21f9e2b8-701d-4798-b1e2-50d28c8289bd · outbound

This paper cites Dgm: A deep learning algorithm for solving partial differential equations,.

Machine Learning Gravity Compactifications on Negatively Curved Manifolds Dgm: A deep learning algorithm for solving partial differential equations,

Reference 30

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Observation 3c3261ae-70d2-4c7e-ba08-8f4c007538b8 · outbound

This paper cites Machine learning Calabi-Yau metrics.

Machine Learning Gravity Compactifications on Negatively Curved Manifolds Machine learning Calabi-Yau metrics

Reference 31

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Observation b408cf48-2f5c-4665-8b99-7979c8079614 · outbound

This paper cites Numerical Calabi-Yau metrics from holomorphic networks.

Machine Learning Gravity Compactifications on Negatively Curved Manifolds Numerical Calabi-Yau metrics from holomorphic networks

Reference 32

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Observation a801b3be-24dc-4fa9-a79e-23c8240445e2 · outbound

This paper cites Neural Network Approximations for Calabi-Yau Metrics.

Machine Learning Gravity Compactifications on Negatively Curved Manifolds Neural Network Approximations for Calabi-Yau Metrics

Reference 33

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Observation 6e3f9a45-ad63-4ac5-bb40-fce14a1ea54c · outbound

This paper cites Learning Size and Shape of Calabi-Yau Spaces.

Machine Learning Gravity Compactifications on Negatively Curved Manifolds Learning Size and Shape of Calabi-Yau Spaces

Reference 34

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This paper cites Numerical Metrics for Complete Intersection and Kreuzer-Skarke Calabi-Yau Manifolds.

Machine Learning Gravity Compactifications on Negatively Curved Manifolds Numerical Metrics for Complete Intersection and Kreuzer-Skarke Calabi-Yau Manifolds

Reference 35

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This paper cites CYJAX: A package for Calabi-Yau metrics with JAX.

Machine Learning Gravity Compactifications on Negatively Curved Manifolds CYJAX: A package for Calabi-Yau metrics with JAX

Reference 36

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Observation dfe82502-a30e-4846-b8bf-e5650e2cb74d · outbound

This paper cites Not So Flat Metrics.

Machine Learning Gravity Compactifications on Negatively Curved Manifolds Not So Flat Metrics

Reference 37

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This paper cites Lectures on Numerical and Machine Learning Methods for Approximating Ricci-flat Calabi-Yau Metrics.

Machine Learning Gravity Compactifications on Negatively Curved Manifolds Lectures on Numerical and Machine Learning Methods for Approximating Ricci-flat Calabi-Yau Metrics

Reference 38

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This paper cites Hyperbolic compactification of M-theory and de Sitter quantum gravity.

Machine Learning Gravity Compactifications on Negatively Curved Manifolds Hyperbolic compactification of M-theory and de Sitter quantum gravity

Reference 39

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This paper cites Adam: A Method for Stochastic Optimization.

Machine Learning Gravity Compactifications on Negatively Curved Manifolds Adam: A Method for Stochastic Optimization

Reference 40

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This paper cites Optimizers for Stabi- lizing Neural Simulation-based Inference,.

Machine Learning Gravity Compactifications on Negatively Curved Manifolds Optimizers for Stabi- lizing Neural Simulation-based Inference,

Reference 41

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Observation 77e1ac25-678e-4bc7-b6ff-7fa98d2a5392 · outbound

This paper cites Microcanonical Hamiltonian Monte Carlo.

Machine Learning Gravity Compactifications on Negatively Curved Manifolds Microcanonical Hamiltonian Monte Carlo

Reference 42

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This paper cites Capse.jl: efficient and auto-differentiable CMB power spectra emulation.

Machine Learning Gravity Compactifications on Negatively Curved Manifolds Capse.jl: efficient and auto-differentiable CMB power spectra emulation

Reference 43

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This paper cites Fluctuation without dissipation: Microcanonical Langevin Monte Carlo.

Machine Learning Gravity Compactifications on Negatively Curved Manifolds Fluctuation without dissipation: Microcanonical Langevin Monte Carlo

Reference 44

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This paper cites Born-Infeld (BI) for AI: Energy-Conserving Descent (ECD) for Optimization.

Machine Learning Gravity Compactifications on Negatively Curved Manifolds Born-Infeld (BI) for AI: Energy-Conserving Descent (ECD) for Optimization

Reference 45

Resolution: unresolved; no resolver link, observed 2026-08-10T23:10:03.866076Z

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This paper cites Improving Energy Conserving Descent for Machine Learning: Theory and Practice.

Machine Learning Gravity Compactifications on Negatively Curved Manifolds Improving Energy Conserving Descent for Machine Learning: Theory and Practice

Reference 46

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Observation ad66b0b0-1a19-42e6-8995-b94a442a9fd0 · outbound

This paper cites The AdEMAMix Optimizer: Better, Faster, Older.

Machine Learning Gravity Compactifications on Negatively Curved Manifolds The AdEMAMix Optimizer: Better, Faster, Older

Reference 47

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This paper cites Dehn Filling and Einstein Metrics in Higher Dimensions,.

Machine Learning Gravity Compactifications on Negatively Curved Manifolds Dehn Filling and Einstein Metrics in Higher Dimensions,

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:10:04.873749Z

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Observation 2891fd85-bcd6-456d-a315-7ef0f59bd4d9 · outbound

This paper cites Constructionofeinsteinmetricsbygeneralizeddehnfilling,.

Machine Learning Gravity Compactifications on Negatively Curved Manifolds Constructionofeinsteinmetricsbygeneralizeddehnfilling,

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:10:04.863807Z

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Observation 69d50272-272c-44bd-a708-6fd1dfc89d7f · outbound

This paper cites Hyperbolic manifolds that fibre alge- braically up to dimension 8,.

Machine Learning Gravity Compactifications on Negatively Curved Manifolds Hyperbolic manifolds that fibre alge- braically up to dimension 8,

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:10:04.853816Z

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Observation 51bde607-4af1-45a2-8ed2-31f6b87b2d00 · outbound

This paper cites Gnu general public license, http://www.gnu.org/licenses/gpl.html.

Machine Learning Gravity Compactifications on Negatively Curved Manifolds Gnu general public license, http://www.gnu.org/licenses/gpl.html

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:10:04.842245Z

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Observation e8003f35-f598-4505-bd84-e1fa9e5a22e1 · outbound

This paper cites Leaps and bounds towards scale separation.

Machine Learning Gravity Compactifications on Negatively Curved Manifolds Leaps and bounds towards scale separation

Reference 52

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This paper cites Cheeger bounds on spin-two fields.

Machine Learning Gravity Compactifications on Negatively Curved Manifolds Cheeger bounds on spin-two fields

Reference 53

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Observation 9a89fad5-0236-4617-85e8-f7cf406d2a36 · outbound

This paper cites Effective potential and warp factor dynamics.

Machine Learning Gravity Compactifications on Negatively Curved Manifolds Effective potential and warp factor dynamics

Reference 54

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Observation 83dc2fa4-c53d-49ea-ac8f-f6b2ea26c359 · outbound

This paper cites Aspects of Supergravity Theories,.

Machine Learning Gravity Compactifications on Negatively Curved Manifolds Aspects of Supergravity Theories,

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:10:04.830660Z

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Observation 869482a1-4528-47cc-86f5-d43b1c315700 · outbound

This paper cites Supergravity description of field theories on curved manifolds and a no go theorem.

Machine Learning Gravity Compactifications on Negatively Curved Manifolds Supergravity description of field theories on curved manifolds and a no go theorem

Reference 56

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This paper cites An Expert's Guide to Training Physics-informed Neural Networks.

Machine Learning Gravity Compactifications on Negatively Curved Manifolds An Expert's Guide to Training Physics-informed Neural Networks

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Resolution: unresolved; no resolver link, observed 2026-08-10T23:10:03.912874Z

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This paper cites Learning representations by back-propagating errors,.

Machine Learning Gravity Compactifications on Negatively Curved Manifolds Learning representations by back-propagating errors,

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:10:04.819228Z

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Observation 4fdc0bc3-734b-4b19-a903-e29cbcf236b2 · outbound

This paper cites On the momentum term in gradient descent learning algorithms,.

Machine Learning Gravity Compactifications on Negatively Curved Manifolds On the momentum term in gradient descent learning algorithms,

Reference 59

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:10:04.808244Z

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This paper cites A comprehensive study of non- adaptive and residual-based adaptive sampling for physics-informed neural net- works,.

Machine Learning Gravity Compactifications on Negatively Curved Manifolds A comprehensive study of non- adaptive and residual-based adaptive sampling for physics-informed neural net- works,

Reference 60

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:10:04.797523Z

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Observation b864967d-0318-47d5-b1f4-98599ed2932d · outbound

This paper cites Statistical mechanics of deep learning,.

Machine Learning Gravity Compactifications on Negatively Curved Manifolds Statistical mechanics of deep learning,

Reference 61

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:10:04.786000Z

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This paper cites Hyperbolic four-manifolds.

Machine Learning Gravity Compactifications on Negatively Curved Manifolds Hyperbolic four-manifolds

Reference 62

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Machine Learning Gravity Compactifications on Negatively Curved Manifolds Vinberg,Geometry II: Spaces of Constant Curvature

Reference 63

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:10:04.775472Z

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This paper cites Foundations of hyperbolic manifolds,.

Machine Learning Gravity Compactifications on Negatively Curved Manifolds Foundations of hyperbolic manifolds,

Reference 64

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:10:04.764693Z

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Observation 43008973-6384-4b65-8dc2-ff88d2444f3a · outbound

This paper cites Topics on totally discontinuous groups,.

Machine Learning Gravity Compactifications on Negatively Curved Manifolds Topics on totally discontinuous groups,

Reference 65

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:10:04.753053Z

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This paper cites Counting hyperbolic mani- folds,.

Machine Learning Gravity Compactifications on Negatively Curved Manifolds Counting hyperbolic mani- folds,

Reference 66

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:10:04.739728Z

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Observation 17a3af15-170c-41fa-8f4a-62524b8af733 · outbound

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Machine Learning Gravity Compactifications on Negatively Curved Manifolds Unresolved cited work

Reference 67

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This paper cites Besse,Einstein Manifolds.

Machine Learning Gravity Compactifications on Negatively Curved Manifolds Besse,Einstein Manifolds

Reference 68

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:10:04.721225Z

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Observation 3df9f489-fee0-4a1f-8fc9-c26a2bf2d6ef · outbound

This paper cites On right-angled reflection groups in hyperbolic spaces,.

Machine Learning Gravity Compactifications on Negatively Curved Manifolds On right-angled reflection groups in hyperbolic spaces,

Reference 69

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:10:04.709068Z

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Observation 94eb3e05-8e71-47a8-b050-58731d1ede2e · outbound

This paper cites Right-angled coxeter polytopes, hyperbolic six-manifolds, and a problem of siegel,.

Machine Learning Gravity Compactifications on Negatively Curved Manifolds Right-angled coxeter polytopes, hyperbolic six-manifolds, and a problem of siegel,

Reference 70

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:10:04.696751Z

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Observation 0c2164f5-7876-48bf-a3e2-3ee7aeab9f3b · outbound

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Machine Learning Gravity Compactifications on Negatively Curved Manifolds Poisson,A relativist’s toolkit: the mathematics of black-hole mechanics

Reference 71

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:10:04.686064Z

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Observation b98fdc13-345e-48fb-8317-51694bf081ff · outbound

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Machine Learning Gravity Compactifications on Negatively Curved Manifolds Unresolved cited work

Reference 72

Resolution: unresolved; raw_fallback, observed 2026-08-10T23:10:04.676154Z

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Observation 89e6ab6d-789a-4ce6-8dee-1a779aa4bb7a · outbound

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Machine Learning Gravity Compactifications on Negatively Curved Manifolds Unresolved cited work

Reference 73

Resolution: unresolved; raw_fallback, observed 2026-08-10T23:10:04.666158Z

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Observation e4eca6ec-70b4-4a2c-8779-358c5d14203f · outbound

This paper cites Understanding and mitigat- ing gradient flow pathologies in physics-informed neural networks,.

Machine Learning Gravity Compactifications on Negatively Curved Manifolds Understanding and mitigat- ing gradient flow pathologies in physics-informed neural networks,

Reference 74

Resolution: unresolved; no resolver link, observed 2026-08-10T23:10:03.973964Z

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Observation 64ac8ffd-19f9-4e90-bfec-d2fcab5abf75 · outbound

This paper cites Fourier features let networks learn high frequency functions in low dimensional domains,.

Machine Learning Gravity Compactifications on Negatively Curved Manifolds Fourier features let networks learn high frequency functions in low dimensional domains,

Reference 75

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:10:04.655024Z

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Pith citing papers

Observation 866d202d-ccb1-47ed-a3f0-364e4c5f4d81 · inbound

Minimal surfaces, Knots, and Neural Networks cites this paper.

Minimal surfaces, Knots, and Neural Networks Machine Learning Gravity Compactifications on Negatively Curved Manifolds

Reference 33

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Observation b23a0baf-db52-4d60-aec3-a2e220b40700 · inbound

Black Hole Black Boxes: Numerical Black Hole Metrics via AInstein Neural Networks cites this paper.

Black Hole Black Boxes: Numerical Black Hole Metrics via AInstein Neural Networks Machine Learning Gravity Compactifications on Negatively Curved Manifolds

Reference 41

Resolution: unresolved; no resolver link, observed 2026-07-11T06:56:17.499687Z

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