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Paper Citation Record · LEDGER

Black Hole Spectroscopy with Conditional Variational Autoencoder

As of 16 August 2026, this Paper Citation Record lists 83 of 83 outbound references and 0 inbound Pith citation observations for arXiv:2506.17618.

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pith.paper-citation-record.v1
2506.17618 v1

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Outbound references

Observation 5ae6eae0-f721-4bea-a1d6-4655d6024276 · outbound

This paper cites Parameter Estimation.

Black Hole Spectroscopy with Conditional Variational Autoencoder Parameter Estimation

Reference 1

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Observation 4e05a316-da42-405b-9fd4-dd5d6ec990d4 · outbound

This paper cites Observation of Gravitational Waves from a Binary Black Hole Merger.

Black Hole Spectroscopy with Conditional Variational Autoencoder Observation of Gravitational Waves from a Binary Black Hole Merger

Reference 2

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Observation 8c80907c-7833-4724-b32b-db6e458d6cc1 · outbound

This paper cites Properties of the Binary Black Hole Merger GW150914.

Black Hole Spectroscopy with Conditional Variational Autoencoder Properties of the Binary Black Hole Merger GW150914

Reference 3

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Observation b8dd88e0-d0c3-4756-9698-b89835f470d7 · outbound

This paper cites GWTC-2: Compact Binary Coalescences Observed by LIGO and Virgo During the First Half of the Third Observing Run.

Black Hole Spectroscopy with Conditional Variational Autoencoder GWTC-2: Compact Binary Coalescences Observed by LIGO and Virgo During the First Half of the Third Observing Run

Reference 4

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Observation cca244a9-2379-4bc0-974f-d9884bc0c24b · outbound

This paper cites GWTC-3: Compact Binary Coalescences Observed by LIGO and Virgo During the Second Part of the Third Observing Run.

Black Hole Spectroscopy with Conditional Variational Autoencoder GWTC-3: Compact Binary Coalescences Observed by LIGO and Virgo During the Second Part of the Third Observing Run

Reference 5

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Observation 0e7dd81b-f7e5-443c-bd5e-9d8fa4862d5e · outbound

This paper cites Tests of general relativity with GW150914.

Black Hole Spectroscopy with Conditional Variational Autoencoder Tests of general relativity with GW150914

Reference 6

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Observation dd459a44-059b-42cf-aed5-897f8835b8c3 · outbound

This paper cites Tests of General Relativity with GWTC-3.

Black Hole Spectroscopy with Conditional Variational Autoencoder Tests of General Relativity with GWTC-3

Reference 7

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Observation 335972ca-f73f-448b-8dcd-49b174ffb584 · outbound

This paper cites GW170817: Observation of Gravitational Waves from a Binary Neutron Star Inspiral.

Black Hole Spectroscopy with Conditional Variational Autoencoder GW170817: Observation of Gravitational Waves from a Binary Neutron Star Inspiral

Reference 8

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Observation 64d94f60-10ba-48d7-bc23-642215e46f66 · outbound

This paper cites Population Properties of Compact Objects from the Second LIGO-Virgo Gravitational-Wave Transient Catalog.

Black Hole Spectroscopy with Conditional Variational Autoencoder Population Properties of Compact Objects from the Second LIGO-Virgo Gravitational-Wave Transient Catalog

Reference 9

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Observation f8c04d48-c75c-410d-97bf-4983caa0bc81 · outbound

This paper cites The population of merging compact binaries inferred using gravitational waves through GWTC-3.

Black Hole Spectroscopy with Conditional Variational Autoencoder The population of merging compact binaries inferred using gravitational waves through GWTC-3

Reference 10

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Observation 0c22876f-df6b-481e-bb28-9ded6fcce60a · outbound

This paper cites Stability of a Schwarzschild singularity,.

Black Hole Spectroscopy with Conditional Variational Autoencoder Stability of a Schwarzschild singularity,

Reference 11

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Observation 91269459-635a-4cf3-9192-8a345b6d3b77 · outbound

This paper cites Scattering of Gravitational Radiation by a Schwarzschild Black-hole,.

Black Hole Spectroscopy with Conditional Variational Autoencoder Scattering of Gravitational Radiation by a Schwarzschild Black-hole,

Reference 12

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Observation f7b80ae5-eec9-4325-b48d-3b3d8948efdd · outbound

This paper cites Perturbation analysis for gravitational and electromagnetic radiation in a reissner-nordstroem geometry,.

Black Hole Spectroscopy with Conditional Variational Autoencoder Perturbation analysis for gravitational and electromagnetic radiation in a reissner-nordstroem geometry,

Reference 13

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Black Hole Spectroscopy with Conditional Variational Autoencoder Unresolved cited work

Reference 14

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Observation 5c8b37ca-9c0a-4bd7-b91a-6ced6b0abf1a · outbound

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Black Hole Spectroscopy with Conditional Variational Autoencoder Unresolved cited work

Reference 15

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Observation ff7cce4e-dc65-4276-bceb-8997cf9869d6 · outbound

This paper cites On gravitational-wave spectroscopy of massive black holes with the space interferometer LISA.

Black Hole Spectroscopy with Conditional Variational Autoencoder On gravitational-wave spectroscopy of massive black holes with the space interferometer LISA

Reference 16

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Observation 2300f091-07ce-4744-b2a5-99257674c331 · outbound

This paper cites Event horizons in static electrovac space-times,.

Black Hole Spectroscopy with Conditional Variational Autoencoder Event horizons in static electrovac space-times,

Reference 17

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Observation f2f70567-10b5-4f6b-a6c8-7640e35fd08c · outbound

This paper cites Axisymmetric Black Hole Has Only Two Degrees of Freedom,.

Black Hole Spectroscopy with Conditional Variational Autoencoder Axisymmetric Black Hole Has Only Two Degrees of Freedom,

Reference 18

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Observation fbead760-1a6a-4db0-8c70-315c7914916b · outbound

This paper cites Uniqueness of the Kerr black hole,.

Black Hole Spectroscopy with Conditional Variational Autoencoder Uniqueness of the Kerr black hole,

Reference 19

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Observation f1c44417-24e1-4149-a84a-68390dce2c3d · outbound

This paper cites Testing the No-Hair Theorem with Observations in the Electromagnetic Spectrum: II. Black-Hole Images.

Black Hole Spectroscopy with Conditional Variational Autoencoder Testing the No-Hair Theorem with Observations in the Electromagnetic Spectrum: II. Black-Hole Images

Reference 20

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Observation 6c4d793c-ecbb-4968-9256-d4e22b5895b3 · outbound

This paper cites Testing the no-hair theorem with black hole ringdowns using TIGER.

Black Hole Spectroscopy with Conditional Variational Autoencoder Testing the no-hair theorem with black hole ringdowns using TIGER

Reference 21

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Observation 45bede23-0469-47cc-a008-d3bc016ba020 · outbound

This paper cites Testing the no-hair theorem with GW150914.

Black Hole Spectroscopy with Conditional Variational Autoencoder Testing the no-hair theorem with GW150914

Reference 22

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Observation b9dbec78-bff0-49a4-9b1a-d68ee5551f18 · outbound

This paper cites Black-hole spectroscopy, the no-hair theorem and GW150914: Kerr vs. Occam.

Black Hole Spectroscopy with Conditional Variational Autoencoder Black-hole spectroscopy, the no-hair theorem and GW150914: Kerr vs. Occam

Reference 23

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Observation 4e96fd75-bb01-42b6-949b-9bd6d0516dd4 · outbound

This paper cites Observational Black Hole Spectroscopy: A time-domain multimode analysis of GW150914.

Black Hole Spectroscopy with Conditional Variational Autoencoder Observational Black Hole Spectroscopy: A time-domain multimode analysis of GW150914

Reference 24

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Observation 3b92053a-b312-4adb-98db-3039c62ace9d · outbound

This paper cites Analyzing black-hole ringdowns.

Black Hole Spectroscopy with Conditional Variational Autoencoder Analyzing black-hole ringdowns

Reference 25

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Observation d9f317da-cad5-4111-9a6f-185ae3f9bf0f · outbound

This paper cites Analysis of Ringdown Overtones in GW150914.

Black Hole Spectroscopy with Conditional Variational Autoencoder Analysis of Ringdown Overtones in GW150914

Reference 26

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This paper cites The Ringdown of GW190521: Hints of Multiple Quasinormal Modes with a Precessional Interpretation.

Black Hole Spectroscopy with Conditional Variational Autoencoder The Ringdown of GW190521: Hints of Multiple Quasinormal Modes with a Precessional Interpretation

Reference 27

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Observation 2a71ee2e-4c61-40f6-baa9-fb4fc2079c7c · outbound

This paper cites Probing Spacetime Symmetries Using Gravitational Wave Ringdown.

Black Hole Spectroscopy with Conditional Variational Autoencoder Probing Spacetime Symmetries Using Gravitational Wave Ringdown

Reference 28

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Observation 018a4b02-52e4-42d2-a6a3-1a324d76728c · outbound

This paper cites Testing the black-hole area law with GW150914.

Black Hole Spectroscopy with Conditional Variational Autoencoder Testing the black-hole area law with GW150914

Reference 29

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Observation 77d66bc8-6be6-4e80-8748-5ea3848d5517 · outbound

This paper cites Constraints on Kerr-Newman black holes from merger-ringdown gravitational-wave observations.

Black Hole Spectroscopy with Conditional Variational Autoencoder Constraints on Kerr-Newman black holes from merger-ringdown gravitational-wave observations

Reference 30

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This paper cites Constraining extra dimensions using observations of black hole quasi-normal modes.

Black Hole Spectroscopy with Conditional Variational Autoencoder Constraining extra dimensions using observations of black hole quasi-normal modes

Reference 31

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This paper cites Identifying modified theories of gravity using binary black-hole ringdowns.

Black Hole Spectroscopy with Conditional Variational Autoencoder Identifying modified theories of gravity using binary black-hole ringdowns

Reference 32

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Observation 593f67dd-1e0c-438c-b2de-4a3a79675f10 · outbound

This paper cites Black-hole ringdown as a probe of higher-curvature gravity theories.

Black Hole Spectroscopy with Conditional Variational Autoencoder Black-hole ringdown as a probe of higher-curvature gravity theories

Reference 33

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Observation f2ef16c5-5ab6-4304-ac77-7050f29b8ec3 · outbound

This paper cites Measuring deviations from the Kerr geometry with black hole ringdown.

Black Hole Spectroscopy with Conditional Variational Autoencoder Measuring deviations from the Kerr geometry with black hole ringdown

Reference 34

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This paper cites Bounds on tidal charges from gravitational-wave ringdown observations.

Black Hole Spectroscopy with Conditional Variational Autoencoder Bounds on tidal charges from gravitational-wave ringdown observations

Reference 35

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Observation 72b26d80-c766-463d-b140-fdc0093503ff · outbound

This paper cites Higher-derivative corrections to the Kerr quasinormal mode spectrum.

Black Hole Spectroscopy with Conditional Variational Autoencoder Higher-derivative corrections to the Kerr quasinormal mode spectrum

Reference 36

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This paper cites Black hole spectroscopy: from theory to experiment.

Black Hole Spectroscopy with Conditional Variational Autoencoder Black hole spectroscopy: from theory to experiment

Reference 37

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This paper cites Bilby: A user-friendly Bayesian inference library for gravitational-wave astronomy.

Black Hole Spectroscopy with Conditional Variational Autoencoder Bilby: A user-friendly Bayesian inference library for gravitational-wave astronomy

Reference 38

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Observation 552e87bc-3e85-4e69-a7cb-37a2cca7c6f2 · outbound

This paper cites An introduction to bayesian inference in gravitational-wave astronomy: Parameter estimation, model selection, and hierarchical models,.

Black Hole Spectroscopy with Conditional Variational Autoencoder An introduction to bayesian inference in gravitational-wave astronomy: Parameter estimation, model selection, and hierarchical models,

Reference 39

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Observation bef688ca-c348-47da-868a-12f6afcd34a5 · outbound

This paper cites Inferring Binary Properties from Gravitational Wave Signals.

Black Hole Spectroscopy with Conditional Variational Autoencoder Inferring Binary Properties from Gravitational Wave Signals

Reference 40

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Observation 33a2a5d7-dd0c-4bb6-bee4-b8faf4f7828a · outbound

This paper cites pyRing: a time-domain ringdown analysis python package.

Black Hole Spectroscopy with Conditional Variational Autoencoder pyRing: a time-domain ringdown analysis python package

Reference 41

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source=pdf_text observed=2026-08-15T19:11:25.181502Z digest=sha256:b7e58056a1da1167c7f0418b575cc0bcf4982ccf5aac9c719f607c5008326587

Observation f51f00db-01ad-4910-bf95-1024ae82b0d7 · outbound

This paper cites dynesty: a dynamic nested sampling package for estimating bayesian posteriors and evidences,.

Black Hole Spectroscopy with Conditional Variational Autoencoder dynesty: a dynamic nested sampling package for estimating bayesian posteriors and evidences,

Reference 42

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source=pdf_text observed=2026-08-15T19:11:25.185930Z digest=sha256:64fe5fe4f190951cdb2c086eae9b30aa73ef135fdf950ee7b2aac59186f7102f

Observation b16abe78-5992-4bbe-8ce6-3ceac7473137 · outbound

This paper cites johnveitch/cpnest: v0.11.4,.

Black Hole Spectroscopy with Conditional Variational Autoencoder johnveitch/cpnest: v0.11.4,

Reference 43

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Observation c120d88b-de4e-433f-925f-55b159e2abba · outbound

This paper cites Matching matched filtering with deep networks in gravitational-wave astronomy.

Black Hole Spectroscopy with Conditional Variational Autoencoder Matching matched filtering with deep networks in gravitational-wave astronomy

Reference 44

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Observation 7e38e6c5-31dd-460d-a957-aed6cd89b223 · outbound

This paper cites emcee: The MCMC Hammer.

Black Hole Spectroscopy with Conditional Variational Autoencoder emcee: The MCMC Hammer

Reference 45

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source=pdf_text observed=2026-08-15T19:11:25.199231Z digest=sha256:ac5b719691fb48d3ed53f7ff17474caea318ebb3c1221d431e640ce856106353

Observation 12966076-0fa9-4983-9292-06bec06a99b7 · outbound

This paper cites Probabilistic programming in python using pymc3,.

Black Hole Spectroscopy with Conditional Variational Autoencoder Probabilistic programming in python using pymc3,

Reference 46

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source=pdf_text observed=2026-08-15T19:11:25.203500Z digest=sha256:c9438d10c459829d0e06c5cbc1e2386b5fd40f54c26fffbe4303135d76562586

Observation 1f750343-5b59-4384-b9a4-441ba1bf5e1e · outbound

This paper cites Rapid identification of time-frequency domain gravitational wave signals from binary black holes using deep learning.

Black Hole Spectroscopy with Conditional Variational Autoencoder Rapid identification of time-frequency domain gravitational wave signals from binary black holes using deep learning

Reference 47

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source=pdf_text observed=2026-08-15T19:11:25.222031Z digest=sha256:657111494fcbe4763c4fc5659031ed5488a9954fce1c12fdb3efc69da1761fd2

Observation a91863aa-6a90-4236-be3b-bcf2f7e18956 · outbound

This paper cites Detecting and Denoising Gravitational Wave Signals from Binary Black Holes using Deep Learning.

Black Hole Spectroscopy with Conditional Variational Autoencoder Detecting and Denoising Gravitational Wave Signals from Binary Black Holes using Deep Learning

Reference 48

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source=pdf_text observed=2026-08-15T19:11:25.212402Z digest=sha256:21599b3798171783f2a08ba4e67d6585b2def2fe0794ef496d607398cc02aebf

Observation ea8dfd78-9de9-4b19-b269-1dc2df61b3a8 · outbound

This paper cites Convolutional Neural Networks for signal detection in real LIGO data.

Black Hole Spectroscopy with Conditional Variational Autoencoder Convolutional Neural Networks for signal detection in real LIGO data

Reference 49

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source=pdf_text observed=2026-08-15T19:11:25.216651Z digest=sha256:c6dab32210bbbe2c4680e332cfd0c456772139e5bc65a60898bdcdffba809005

Observation b5a79e26-ba0a-487e-b99a-cd02968da0a4 · outbound

This paper cites Nonlinear noise regression in gravitational-wave detectors with convolutional neural networks.

Black Hole Spectroscopy with Conditional Variational Autoencoder Nonlinear noise regression in gravitational-wave detectors with convolutional neural networks

Reference 50

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source=pdf_text observed=2026-08-15T19:11:25.239032Z digest=sha256:63956fbe11a16dec6d74ed7e77add5a6ed093546340c2f7e08ac1b141f5ea8c5

Observation 42006fd3-c698-4a2b-a6db-fbbaa7a4cd71 · outbound

This paper cites Noise Reduction in Gravitational-wave Data via Deep Learning.

Black Hole Spectroscopy with Conditional Variational Autoencoder Noise Reduction in Gravitational-wave Data via Deep Learning

Reference 51

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source=pdf_text observed=2026-08-15T19:11:25.227040Z digest=sha256:12d6952d092b5bb46786fb0d819ed63592203656aea6c8bdd31d7d8007c24554

Observation 274fdb4d-95d0-4a74-9286-9359c37ebd47 · outbound

This paper cites Machine-learning non-stationary noise out of gravitational wave detectors.

Black Hole Spectroscopy with Conditional Variational Autoencoder Machine-learning non-stationary noise out of gravitational wave detectors

Reference 52

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source=pdf_text observed=2026-08-15T19:11:25.233646Z digest=sha256:c836c1b7eb5ccdc4e33aa755060309e8d38bdf244b33ecef49247ad7e3dfbd25

Observation f2287b4d-6c5f-4bc9-85a0-23bf7190a3e0 · outbound

This paper cites NNETFIX: An artificial neural network-based denoising engine for gravitational-wave signals.

Black Hole Spectroscopy with Conditional Variational Autoencoder NNETFIX: An artificial neural network-based denoising engine for gravitational-wave signals

Reference 53

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source=pdf_text observed=2026-08-15T19:11:25.253305Z digest=sha256:6591264599558d4eb64666471795a56af6d3f3a5d96d6adda54151af961d2a21

Observation 3ad0fc6f-2d89-4ec9-a162-92809eba8993 · outbound

This paper cites Gravitational Wave Denoising of Binary Black Hole Mergers with Deep Learning.

Black Hole Spectroscopy with Conditional Variational Autoencoder Gravitational Wave Denoising of Binary Black Hole Mergers with Deep Learning

Reference 54

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source=pdf_text observed=2026-08-15T19:11:25.244331Z digest=sha256:fa5fdde412a000977763ca5f78263c488d6182c58cc3b47f28af77ce38caf387

Observation cfe894bf-1600-457a-a5d3-e929f0353081 · outbound

This paper cites Application of dictionary learning to denoise LIGO's blip noise transients.

Black Hole Spectroscopy with Conditional Variational Autoencoder Application of dictionary learning to denoise LIGO's blip noise transients

Reference 55

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source=pdf_text observed=2026-08-15T19:11:25.248790Z digest=sha256:dc0755d05695ee5ae170f054baafebe494760d025ad2d5a0252dd047bb81cf46

Observation db257ee3-ccb8-4680-a0ce-7e781e365a2f · outbound

This paper cites NRSurNN3dq4: A Deep Learning Powered Numerical Relativity Surrogate for Binary Black Hole Waveforms,.

Black Hole Spectroscopy with Conditional Variational Autoencoder NRSurNN3dq4: A Deep Learning Powered Numerical Relativity Surrogate for Binary Black Hole Waveforms,

Reference 56

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source=pdf_text observed=2026-08-15T19:11:25.268025Z digest=sha256:632ebfb8a19027cff29fb0232e42b327952eddf93c19fe92c24f1eb5fd853701

Observation 7debb33e-d82a-4134-baf7-8d481e7f724f · outbound

This paper cites Denoising gravitational-wave signals from binary black holes with dilated convolutional autoencoder.

Black Hole Spectroscopy with Conditional Variational Autoencoder Denoising gravitational-wave signals from binary black holes with dilated convolutional autoencoder

Reference 57

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source=pdf_text observed=2026-08-15T19:11:25.257866Z digest=sha256:fe83a6fc1d98142e1d8dc5b0990938cbd4fd4f8f89dd78b100fa6af76e9be051

Observation b76d92d9-afc7-4458-8352-6b2d37eb0195 · outbound

This paper cites Gravitational-wave surrogate models powered by artificial neural networks: The ANN-Sur for waveform generation.

Black Hole Spectroscopy with Conditional Variational Autoencoder Gravitational-wave surrogate models powered by artificial neural networks: The ANN-Sur for waveform generation

Reference 58

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source=pdf_text observed=2026-08-15T19:11:25.262760Z digest=sha256:2f0832f6fb0f0b4555ef3870beaf199f8e008d481239eba9dcf09a5383c94903

Observation 17fce9ff-27e1-4561-a080-168a59e79b20 · outbound

This paper cites Use of conditional variational auto encoder to analyze ringdown gravitational waves.

Black Hole Spectroscopy with Conditional Variational Autoencoder Use of conditional variational auto encoder to analyze ringdown gravitational waves

Reference 59

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source=pdf_text observed=2026-08-15T19:11:25.281539Z digest=sha256:12cbf5c9f77132a233656cbbb7f00f5430212533bc24e781f5e9a09962063d91

Observation c15ff125-f54b-49ad-bd4f-67a75a20a5e2 · outbound

This paper cites Bayesian parameter estimation using conditional variational autoencoders for gravitational-wave astronomy.

Black Hole Spectroscopy with Conditional Variational Autoencoder Bayesian parameter estimation using conditional variational autoencoders for gravitational-wave astronomy

Reference 60

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source=pdf_text observed=2026-08-15T19:11:25.272299Z digest=sha256:e9fbfd520859dc2fadb156c09e45048881d4b80a4178cfa6ff447e70b70d9278

Observation 5a73fa7e-a18b-41a1-96ca-284056eb1634 · outbound

This paper cites Gravitational-wave parameter estimation with autoregressive neural network flows.

Black Hole Spectroscopy with Conditional Variational Autoencoder Gravitational-wave parameter estimation with autoregressive neural network flows

Reference 61

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source=pdf_text observed=2026-08-15T19:11:25.276856Z digest=sha256:bdcb535206bd5bcd8811671c66a29fb0fb0152dc67e3c5f0e3bceefb60dfb0d0

Observation 523563da-f8e0-46e5-9871-d70894217844 · outbound

This paper cites Merger-Ringdown Consistency: A New Test of Strong Gravity using Deep Learning.

Black Hole Spectroscopy with Conditional Variational Autoencoder Merger-Ringdown Consistency: A New Test of Strong Gravity using Deep Learning

Reference 62

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source=pdf_text observed=2026-08-15T19:11:25.296775Z digest=sha256:5f4b627a9864500d6af3b1243fc3c5046a6b338efeddbdfeddaa964294f3c32a

Observation 6ae29b3e-622b-4ec6-8145-2f00806ed197 · outbound

This paper cites Complete parameter inference for GW150914 using deep learning.

Black Hole Spectroscopy with Conditional Variational Autoencoder Complete parameter inference for GW150914 using deep learning

Reference 63

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source=pdf_text observed=2026-08-15T19:11:25.286230Z digest=sha256:e1834476fa94e249d3b8b38564055c9c807db5c7a04169c38555a9411ed6453e

Observation 46abc031-c9bd-43e8-8c20-9e100e55a94e · outbound

This paper cites Real-time gravitational-wave science with neural posterior estimation.

Black Hole Spectroscopy with Conditional Variational Autoencoder Real-time gravitational-wave science with neural posterior estimation

Reference 64

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source=pdf_text observed=2026-08-15T19:11:25.292298Z digest=sha256:0af01e0cbc1f9405f355e30e8b8c3bb909512c8f602cecbe4f3d792001506cc1

Observation 32a2036d-3e3a-483e-a19c-ab8a12549b80 · outbound

This paper cites Simulation-based inference of black hole ringdowns in the time domain.

Black Hole Spectroscopy with Conditional Variational Autoencoder Simulation-based inference of black hole ringdowns in the time domain

Reference 65

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source=pdf_text observed=2026-08-15T19:11:25.310340Z digest=sha256:d6355e8e8052243ee63c6f98e162cce159a61e042637c62095db7c4aaf6d37c9

Observation 8f82e842-eed1-47c1-b045-84f903cb36c8 · outbound

This paper cites Statistically-informed deep learning for gravitational wave parameter estimation.

Black Hole Spectroscopy with Conditional Variational Autoencoder Statistically-informed deep learning for gravitational wave parameter estimation

Reference 66

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source=pdf_text observed=2026-08-15T19:11:25.301259Z digest=sha256:3b7c1923b1042048c9d2b4546e20f3ce9636c93c292cdf5ffd3e13d9ff9cc774

Observation dece5d0c-58c6-4a25-96ef-970e03bdf07f · outbound

This paper cites Rapid Mass Parameter Estimation of Binary Black Hole Coalescences Using Deep Learning.

Black Hole Spectroscopy with Conditional Variational Autoencoder Rapid Mass Parameter Estimation of Binary Black Hole Coalescences Using Deep Learning

Reference 67

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source=pdf_text observed=2026-08-15T19:11:25.305777Z digest=sha256:7933106e70924b06b6cd4ce6a25d191d12bd6980f8cb30473d0889d5541a3210

Observation 7ce2c735-3af0-4b90-8f61-8c5a43833cf8 · outbound

This paper cites Learning structured output representation using deep conditional generative models,.

Black Hole Spectroscopy with Conditional Variational Autoencoder Learning structured output representation using deep conditional generative models,

Reference 68

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source=pdf_text observed=2026-08-15T19:11:25.323390Z digest=sha256:591aa73905f5a1b74fca06ff9e65f256fe22f15df4a7d86ab9337a7e4972119e

Observation ca3fb1d5-a9c0-4cce-b15c-5dd05d74da41 · outbound

This paper cites Rapid Likelihood Free Inference of Compact Binary Coalescences using Accelerated Hardware.

Black Hole Spectroscopy with Conditional Variational Autoencoder Rapid Likelihood Free Inference of Compact Binary Coalescences using Accelerated Hardware

Reference 69

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source=pdf_text observed=2026-08-15T19:11:25.314484Z digest=sha256:dafc9e9129ea903da4418b09f084c180e68176fddffdb8edc09ece617e1bbe26

Observation cd1ac30f-e649-418b-823d-b567baed6341 · outbound

This paper cites Parameter estimation of microlensed gravitational waves with Conditional Variational Autoencoders.

Black Hole Spectroscopy with Conditional Variational Autoencoder Parameter estimation of microlensed gravitational waves with Conditional Variational Autoencoders

Reference 70

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source=pdf_text observed=2026-08-15T19:11:25.318631Z digest=sha256:aa49d69be20f06b72ab1a1201a3d8eb704efa8f19689fd216d162ec67a5e4ca6

Observation 930059ad-d791-4b50-a5bc-d43d5b7574e9 · outbound

This paper cites An introduction to variational autoencoders,.

Black Hole Spectroscopy with Conditional Variational Autoencoder An introduction to variational autoencoders,

Reference 71

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source=pdf_text observed=2026-08-15T19:11:25.342773Z digest=sha256:2f6165206b02b7d24ca49e6e0c5f6b1258e5ea45cf847fde21e3128e5b6d6bc2

Observation 466eee91-73c5-46ed-805c-8a54caf1077f · outbound

This paper cites Tutorial on variational autoencoders,.

Black Hole Spectroscopy with Conditional Variational Autoencoder Tutorial on variational autoencoders,

Reference 72

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source=pdf_text observed=2026-08-15T19:11:25.348328Z digest=sha256:61326c5d0e6e62a297249e4f665b25a7b039689213ba099408663c252f9b0be4

Observation d2883043-7a70-4b51-bb4c-3810eac608fd · outbound

This paper cites Controlling Structured Output Representations from Attributes using Conditional Generative Models.

Black Hole Spectroscopy with Conditional Variational Autoencoder Controlling Structured Output Representations from Attributes using Conditional Generative Models

Reference 73

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local_arxiv, observed 2026-08-15T19:11:25.603097Z

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Observation 0053e6ae-e193-47cc-aaf0-79cfca94951c · outbound

This paper cites Auto-Encoding Variational Bayes.

Black Hole Spectroscopy with Conditional Variational Autoencoder Auto-Encoding Variational Bayes

Reference 74

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source=pdf_text observed=2026-08-15T19:11:25.337960Z digest=sha256:788c45e787ccf7468af0af3408f2c2b6c98f408b799c70c8a3db561cf5a2a069

Observation ea75bca6-5905-40cc-9521-c2030506243f · outbound

This paper cites Exciting black hole modes via misaligned coalescences: II. The mode content of late-time coalescence waveforms.

Black Hole Spectroscopy with Conditional Variational Autoencoder Exciting black hole modes via misaligned coalescences: II. The mode content of late-time coalescence waveforms

Reference 75

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source=pdf_text observed=2026-08-15T19:11:25.368800Z digest=sha256:d039a2b20ee4f156f0b1408efc1a25cdf317e4ecd19aa61a70172fbad6a4d5a8

Observation 720b4944-4aa0-4d8b-871d-b0570b7ab409 · outbound

This paper cites Angular emission patterns of remnant black holes.

Black Hole Spectroscopy with Conditional Variational Autoencoder Angular emission patterns of remnant black holes

Reference 76

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source=pdf_text observed=2026-08-15T19:11:25.374004Z digest=sha256:f5b5a9c4612983d78e20545ba168d5efbc4b75cc4bb5a5da9cb4340a66d9ac1f

Observation fe71008e-3547-4ff3-8773-abf224b98b51 · outbound

This paper cites Brane-world gravity.

Black Hole Spectroscopy with Conditional Variational Autoencoder Brane-world gravity

Reference 77

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Unavailable: canonical work link unavailable.

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Observation 3ecf3764-9b7d-40e3-8c70-1b3e6243f14d · outbound

This paper cites Advanced LIGO.

Black Hole Spectroscopy with Conditional Variational Autoencoder Advanced LIGO

Reference 78

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Observation 466a811a-8537-4b98-8868-f0c7e4522830 · outbound

This paper cites Advanced LIGO detector performance in the fourth observing run.

Black Hole Spectroscopy with Conditional Variational Autoencoder Advanced LIGO detector performance in the fourth observing run

Reference 79

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unresolved
no resolver link, observed 2026-08-15T19:11:25.363654Z

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Unavailable: canonical work link unavailable.

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Observation f68e2e4e-8320-440e-b786-d78d6e1f8705 · outbound

This paper cites An Introduction to Extra Dimensions.

Black Hole Spectroscopy with Conditional Variational Autoencoder An Introduction to Extra Dimensions

Reference 83

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verified exact
local_arxiv, observed 2026-08-15T19:11:25.484750Z

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No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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Observation 0bd38248-0dda-4209-815f-13a2176ab1e9 · outbound

This paper cites an unresolved cited work.

Black Hole Spectroscopy with Conditional Variational Autoencoder Unresolved cited work

Reference 2015

Resolution
unresolved
raw_fallback, observed 2026-08-15T19:11:27.198143Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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Observation 7ec88026-703e-416c-beb3-7143ec709efa · outbound

This paper cites Tutorial on Variational Autoencoders.

Black Hole Spectroscopy with Conditional Variational Autoencoder Tutorial on Variational Autoencoders

Reference 2021

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unresolved
no resolver link, observed 2026-08-15T19:11:25.354060Z

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Unavailable: canonical work link unavailable.

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Observation 96198f8e-e9b3-4592-bd44-53b68defe730 · outbound

This paper cites an unresolved cited work.

Black Hole Spectroscopy with Conditional Variational Autoencoder Unresolved cited work

Reference 2022

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verified exact
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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Pith citing papers

No inbound Pith citation observations are available.