Paper Citation Record · LEDGER

Efficient Neural and Numerical Methods for High-Quality Online Speech Spectrogram Inversion via Gradient Theorem

As of 8 August 2026, this Paper Citation Record lists 57 of 57 outbound references and 1 inbound Pith citation observation for arXiv:2505.24498.

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

pith.paper-citation-record.v1
2505.24498 v1

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measured 57 of 57 reference resolution

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Pith citing papers itemized under the disclosed page cap.

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

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Reference resolution

57 of 57 outbound references displayed

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External citation measurements

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Outbound references

Observation 6efc01c2-55ef-401c-9400-7c0abc058935 · outbound

This paper cites an unresolved cited work.

Efficient Neural and Numerical Methods for High-Quality Online Speech Spectrogram Inversion via Gradient Theorem Unresolved cited work

Reference 1

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This paper cites Then, phases (Φ) are recursively estimated via complex least squares, computed in linear time w.r.t.

Efficient Neural and Numerical Methods for High-Quality Online Speech Spectrogram Inversion via Gradient Theorem Then, phases (Φ) are recursively estimated via complex least squares, computed in linear time w.r.t

Reference 2

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Efficient Neural and Numerical Methods for High-Quality Online Speech Spectrogram Inversion via Gradient Theorem Unresolved cited work

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This paper cites copy-synthesis.

Efficient Neural and Numerical Methods for High-Quality Online Speech Spectrogram Inversion via Gradient Theorem copy-synthesis

Reference 4

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Efficient Neural and Numerical Methods for High-Quality Online Speech Spectrogram Inversion via Gradient Theorem Unresolved cited work

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This paper cites Efficient Neural and Numerical Methods for High-Quality Online Speech Spectrogram Inversion via Gradient Theorem.

Efficient Neural and Numerical Methods for High-Quality Online Speech Spectrogram Inversion via Gradient Theorem Efficient Neural and Numerical Methods for High-Quality Online Speech Spectrogram Inversion via Gradient Theorem

Reference 6

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Observation a7bc21ed-4547-4938-affb-a094e1851f30 · outbound

This paper cites Online Spectrogram Inversion via Gradient Theorem Consider the STFT of a functiony(t)∈L 2(R)w.r.t.

Efficient Neural and Numerical Methods for High-Quality Online Speech Spectrogram Inversion via Gradient Theorem Online Spectrogram Inversion via Gradient Theorem Consider the STFT of a functiony(t)∈L 2(R)w.r.t

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:26:53.524977Z

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Efficient Neural and Numerical Methods for High-Quality Online Speech Spectrogram Inversion via Gradient Theorem Unresolved cited work

Reference 8

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This paper cites Signal reconstruction from stft mag- nitude : A state of the art,.

Efficient Neural and Numerical Methods for High-Quality Online Speech Spectrogram Inversion via Gradient Theorem Signal reconstruction from stft mag- nitude : A state of the art,

Reference 9

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Observation 57b86396-ee82-433a-b41f-b43e25e7292a · outbound

This paper cites On phase retrieval of finite-length sequences using the initial time sample,.

Efficient Neural and Numerical Methods for High-Quality Online Speech Spectrogram Inversion via Gradient Theorem On phase retrieval of finite-length sequences using the initial time sample,

Reference 10

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Observation 232974d5-ecb4-4067-aa8f-c10d381c0db6 · outbound

This paper cites While results are good for our settings, other window and hop sizes, as well as enhanced/inconsistent spectrograms, remain to be evaluated.

Efficient Neural and Numerical Methods for High-Quality Online Speech Spectrogram Inversion via Gradient Theorem While results are good for our settings, other window and hop sizes, as well as enhanced/inconsistent spectrograms, remain to be evaluated

Reference 11

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This paper cites This work was done while AF was a re- search scientist intern at Meta Reality Labs.

Efficient Neural and Numerical Methods for High-Quality Online Speech Spectrogram Inversion via Gradient Theorem This work was done while AF was a re- search scientist intern at Meta Reality Labs

Reference 12

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This paper cites Deep speech 2: end-to-end speech recognition in English and Mandarin,.

Efficient Neural and Numerical Methods for High-Quality Online Speech Spectrogram Inversion via Gradient Theorem Deep speech 2: end-to-end speech recognition in English and Mandarin,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:26:51.736684Z

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Observation e897823f-90f4-412d-b54c-38417b907ce5 · outbound

This paper cites Denoising speech based on deep learning and wavelet decomposition,.

Efficient Neural and Numerical Methods for High-Quality Online Speech Spectrogram Inversion via Gradient Theorem Denoising speech based on deep learning and wavelet decomposition,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:26:51.623093Z

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Observation 099b1798-3e60-4103-896e-8057d7f9af95 · outbound

This paper cites End-to-end speech separation with unfolded iterative phase reconstruction,.

Efficient Neural and Numerical Methods for High-Quality Online Speech Spectrogram Inversion via Gradient Theorem End-to-end speech separation with unfolded iterative phase reconstruction,

Reference 15

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Observation a8a7fa0f-f878-4ab6-8433-0d66d0b6346e · outbound

This paper cites T-GSA: Transformer with Gaussian-weighted self-attention for speech enhancement,.

Efficient Neural and Numerical Methods for High-Quality Online Speech Spectrogram Inversion via Gradient Theorem T-GSA: Transformer with Gaussian-weighted self-attention for speech enhancement,

Reference 16

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Observation 70792bbb-8003-4afc-8025-d324e56a47b4 · outbound

This paper cites GANSynth: Adversarial neural audio synthesis,.

Efficient Neural and Numerical Methods for High-Quality Online Speech Spectrogram Inversion via Gradient Theorem GANSynth: Adversarial neural audio synthesis,

Reference 17

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Observation e45c9492-5677-4f35-a6a8-daf9af8abfe3 · outbound

This paper cites The importance of phase in speech enhancement,.

Efficient Neural and Numerical Methods for High-Quality Online Speech Spectrogram Inversion via Gradient Theorem The importance of phase in speech enhancement,

Reference 18

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This paper cites Phasebook and friends: Leveraging discrete representations for source separation,.

Efficient Neural and Numerical Methods for High-Quality Online Speech Spectrogram Inversion via Gradient Theorem Phasebook and friends: Leveraging discrete representations for source separation,

Reference 19

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This paper cites A unified approach to short-time Fourier analysis and synthesis,.

Efficient Neural and Numerical Methods for High-Quality Online Speech Spectrogram Inversion via Gradient Theorem A unified approach to short-time Fourier analysis and synthesis,

Reference 20

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Efficient Neural and Numerical Methods for High-Quality Online Speech Spectrogram Inversion via Gradient Theorem Unresolved cited work

Reference 21

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This paper cites Magnitude-phase relationships for short-time Fourier transforms based on Gaussian analysis windows,.

Efficient Neural and Numerical Methods for High-Quality Online Speech Spectrogram Inversion via Gradient Theorem Magnitude-phase relationships for short-time Fourier transforms based on Gaussian analysis windows,

Reference 22

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Observation 36170640-e62f-44be-a31e-8c621b86b191 · outbound

This paper cites Signal reconstruction from short-time Fourier transform magnitude,.

Efficient Neural and Numerical Methods for High-Quality Online Speech Spectrogram Inversion via Gradient Theorem Signal reconstruction from short-time Fourier transform magnitude,

Reference 23

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This paper cites PhaseLift: Exact and stable signal recovery from magnitude measurements via con- vex programming,.

Efficient Neural and Numerical Methods for High-Quality Online Speech Spectrogram Inversion via Gradient Theorem PhaseLift: Exact and stable signal recovery from magnitude measurements via con- vex programming,

Reference 24

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Observation 5351b906-dfd1-4a5f-ae26-f0ddcc21bf37 · outbound

This paper cites Estimating a signal from a magni- tude spectrogram via convex optimization,.

Efficient Neural and Numerical Methods for High-Quality Online Speech Spectrogram Inversion via Gradient Theorem Estimating a signal from a magni- tude spectrogram via convex optimization,

Reference 25

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Observation 5d5bfa93-57e5-4894-b0a6-2664eab063c2 · outbound

This paper cites An efficient algorithm for real-time spectrogram inversion,.

Efficient Neural and Numerical Methods for High-Quality Online Speech Spectrogram Inversion via Gradient Theorem An efficient algorithm for real-time spectrogram inversion,

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:26:49.012933Z

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Observation bf57b30d-34fb-4093-83ec-eea698985ba2 · outbound

This paper cites Signal estimation from modified short- time Fourier transform,.

Efficient Neural and Numerical Methods for High-Quality Online Speech Spectrogram Inversion via Gradient Theorem Signal estimation from modified short- time Fourier transform,

Reference 27

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Observation 1817f62e-3e97-49f8-aece-77307a7a3a1f · outbound

This paper cites A flexible online framework for projection-based STFT phase retrieval,.

Efficient Neural and Numerical Methods for High-Quality Online Speech Spectrogram Inversion via Gradient Theorem A flexible online framework for projection-based STFT phase retrieval,

Reference 28

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Observation 7fa8dd15-f223-4277-8098-d19cd8305d92 · outbound

This paper cites Inversion of auditory spectrograms, tradi- tional spectrograms, and other envelope representations,.

Efficient Neural and Numerical Methods for High-Quality Online Speech Spectrogram Inversion via Gradient Theorem Inversion of auditory spectrograms, tradi- tional spectrograms, and other envelope representations,

Reference 29

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This paper cites Phase retrieval with Bregman divergences and application to audio signal recovery,.

Efficient Neural and Numerical Methods for High-Quality Online Speech Spectrogram Inversion via Gradient Theorem Phase retrieval with Bregman divergences and application to audio signal recovery,

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:26:48.124970Z

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Observation 849eaeaa-7983-4830-b1e4-62eb97670ab8 · outbound

This paper cites Single pass spec- trogram inversion,.

Efficient Neural and Numerical Methods for High-Quality Online Speech Spectrogram Inversion via Gradient Theorem Single pass spec- trogram inversion,

Reference 31

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This paper cites Phase-locked vocoder,.

Efficient Neural and Numerical Methods for High-Quality Online Speech Spectrogram Inversion via Gradient Theorem Phase-locked vocoder,

Reference 32

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Observation 2fb478e8-db51-4155-9dc1-1baae636e0af · outbound

This paper cites Online phase reconstruction via DNN-based phase differences estimation,.

Efficient Neural and Numerical Methods for High-Quality Online Speech Spectrogram Inversion via Gradient Theorem Online phase reconstruction via DNN-based phase differences estimation,

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:26:47.520028Z

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Observation c60edbae-e9a8-47ef-a12e-6483d2351b24 · outbound

This paper cites Empirical Evaluation of Rectified Activations in Convolutional Network.

Efficient Neural and Numerical Methods for High-Quality Online Speech Spectrogram Inversion via Gradient Theorem Empirical Evaluation of Rectified Activations in Convolutional Network

Reference 34

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This paper cites A noniterative method for reconstruction of phase from STFT magnitude,.

Efficient Neural and Numerical Methods for High-Quality Online Speech Spectrogram Inversion via Gradient Theorem A noniterative method for reconstruction of phase from STFT magnitude,

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:26:47.194344Z

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Observation 6206aaa6-34ca-4ac5-854c-49415fbaa187 · outbound

This paper cites Real-time spectrogram inversion using phase gradient heap integration,.

Efficient Neural and Numerical Methods for High-Quality Online Speech Spectrogram Inversion via Gradient Theorem Real-time spectrogram inversion using phase gradient heap integration,

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:26:47.036909Z

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Observation 3bafad62-90e5-4325-9b80-0860db3ef2b8 · outbound

This paper cites WaveNet: A generative model for raw audio,.

Efficient Neural and Numerical Methods for High-Quality Online Speech Spectrogram Inversion via Gradient Theorem WaveNet: A generative model for raw audio,

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:26:46.838238Z

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Observation 26578eb4-17e7-44a6-9a82-29b2137ba77e · outbound

This paper cites HiFi-GAN: generative adversar- ial networks for efficient and high fidelity speech synthesis,.

Efficient Neural and Numerical Methods for High-Quality Online Speech Spectrogram Inversion via Gradient Theorem HiFi-GAN: generative adversar- ial networks for efficient and high fidelity speech synthesis,

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:26:46.638716Z

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Observation d4574192-64e1-4b07-bddb-ccb818b09988 · outbound

This paper cites VOCOS: Closing the gap between time-domain and Fourier-based neural vocoders for high-quality audio synthesis,.

Efficient Neural and Numerical Methods for High-Quality Online Speech Spectrogram Inversion via Gradient Theorem VOCOS: Closing the gap between time-domain and Fourier-based neural vocoders for high-quality audio synthesis,

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:26:46.413506Z

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Observation 95c01440-fc1e-4827-8a8f-dabdba0c29a1 · outbound

This paper cites Phase reconstruction from amplitude spec- trograms based on V on-Mises-distribution deep neural network,.

Efficient Neural and Numerical Methods for High-Quality Online Speech Spectrogram Inversion via Gradient Theorem Phase reconstruction from amplitude spec- trograms based on V on-Mises-distribution deep neural network,

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:26:46.200988Z

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 62e03612-205d-4b64-9027-237a686acc38 · outbound

This paper cites Phase reconstruction from amplitude spectrograms based on directional-statistics deep neural networks,.

Efficient Neural and Numerical Methods for High-Quality Online Speech Spectrogram Inversion via Gradient Theorem Phase reconstruction from amplitude spectrograms based on directional-statistics deep neural networks,

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:26:46.083908Z

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Observation 355e0868-9156-4abd-a087-129eac548d54 · outbound

This paper cites Recurrent phase recon- struction using estimated phase derivatives from deep neural net- works,.

Efficient Neural and Numerical Methods for High-Quality Online Speech Spectrogram Inversion via Gradient Theorem Recurrent phase recon- struction using estimated phase derivatives from deep neural net- works,

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:26:45.906358Z

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 15f89979-8d6d-440a-bff6-82e8f26f9fdb · outbound

This paper cites an unresolved cited work.

Efficient Neural and Numerical Methods for High-Quality Online Speech Spectrogram Inversion via Gradient Theorem Unresolved cited work

Reference 43

Resolution: unresolved; raw_fallback, observed 2026-08-07T12:26:52.722684Z

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Observation 43621eb2-6112-4de1-8a3b-6c87fbd3c6c8 · outbound

This paper cites Inter-frequency phase difference for phase reconstruction using deep neural networks and maximum likeli- hood,.

Efficient Neural and Numerical Methods for High-Quality Online Speech Spectrogram Inversion via Gradient Theorem Inter-frequency phase difference for phase reconstruction using deep neural networks and maximum likeli- hood,

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:26:45.723898Z

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Observation f5e72090-41e4-4f38-9856-d24b0fc2b7f7 · outbound

This paper cites Two-stage phase reconstruction using DNN and von Mises distribution-based maximum likelihood,.

Efficient Neural and Numerical Methods for High-Quality Online Speech Spectrogram Inversion via Gradient Theorem Two-stage phase reconstruction using DNN and von Mises distribution-based maximum likelihood,

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:26:45.558331Z

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Observation b8027eed-1bad-48b4-9c9d-0a49d7d2dd41 · outbound

This paper cites Batch normalization: Accelerating deep network training by reducing internal covariate shift,.

Efficient Neural and Numerical Methods for High-Quality Online Speech Spectrogram Inversion via Gradient Theorem Batch normalization: Accelerating deep network training by reducing internal covariate shift,

Reference 46

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Observation b6747c5d-e9b0-4f27-9396-d8087badbdac · outbound

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Efficient Neural and Numerical Methods for High-Quality Online Speech Spectrogram Inversion via Gradient Theorem Unresolved cited work

Reference 47

Resolution: unresolved; raw_fallback, observed 2026-08-07T12:26:45.375363Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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This paper cites an unresolved cited work.

Efficient Neural and Numerical Methods for High-Quality Online Speech Spectrogram Inversion via Gradient Theorem Unresolved cited work

Reference 48

Resolution: unresolved; raw_fallback, observed 2026-08-07T12:26:45.210640Z

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 0d103f4d-1a7f-422c-8a9f-370b6ec5ec41 · outbound

This paper cites A technique for accelerating the convergence of restarted GMRES,.

Efficient Neural and Numerical Methods for High-Quality Online Speech Spectrogram Inversion via Gradient Theorem A technique for accelerating the convergence of restarted GMRES,

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:26:45.023293Z

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Observation 3b1fb291-bf02-4813-98fd-11835de1455b · outbound

This paper cites Librispeech: An ASR corpus based on public domain audio books,.

Efficient Neural and Numerical Methods for High-Quality Online Speech Spectrogram Inversion via Gradient Theorem Librispeech: An ASR corpus based on public domain audio books,

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:26:44.833843Z

Source-reported events for the cited work

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Observation d57ddd73-17c5-41fd-96ba-826d3dc3b93e · outbound

This paper cites Delving deep into rectifiers: Surpassing human- level performance on imagenet classification,.

Efficient Neural and Numerical Methods for High-Quality Online Speech Spectrogram Inversion via Gradient Theorem Delving deep into rectifiers: Surpassing human- level performance on imagenet classification,

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:26:44.675939Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 84585eed-30c6-4aa8-bf5c-a3ea322dfb9b · outbound

This paper cites On the variance of the adaptive learning rate and beyond,.

Efficient Neural and Numerical Methods for High-Quality Online Speech Spectrogram Inversion via Gradient Theorem On the variance of the adaptive learning rate and beyond,

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:26:44.483946Z

Source-reported events for the cited work

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Observation 49e242c4-5fb8-4a3b-bf68-f1e740fd7174 · outbound

This paper cites SGDR: Stochastic gradient descent with warm restarts,.

Efficient Neural and Numerical Methods for High-Quality Online Speech Spectrogram Inversion via Gradient Theorem SGDR: Stochastic gradient descent with warm restarts,

Reference 53

Resolution: unresolved; no resolver link, observed 2026-08-07T12:26:42.660848Z

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Unavailable: canonical work link unavailable.

Observation 8e9e0d68-c5b6-4b9e-a729-6c8f69ba0d8a · outbound

This paper cites Subspectral normalization for neural audio data processing,.

Efficient Neural and Numerical Methods for High-Quality Online Speech Spectrogram Inversion via Gradient Theorem Subspectral normalization for neural audio data processing,

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:26:44.315282Z

Source-reported events for the cited work

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Observation ffce23b0-c486-403b-8c45-6b6cd9233113 · outbound

This paper cites An algorithm for predicting the intelli- gibility of speech masked by modulated noise maskers,.

Efficient Neural and Numerical Methods for High-Quality Online Speech Spectrogram Inversion via Gradient Theorem An algorithm for predicting the intelli- gibility of speech masked by modulated noise maskers,

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:26:44.193704Z

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Observation efcd7eeb-81ed-47b5-b96f-77f87334fc84 · outbound

This paper cites Phase reconstruction in single chan- nel speech enhancement based on phase gradients and estimated clean-speech amplitudes,.

Efficient Neural and Numerical Methods for High-Quality Online Speech Spectrogram Inversion via Gradient Theorem Phase reconstruction in single chan- nel speech enhancement based on phase gradients and estimated clean-speech amplitudes,

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:26:44.059024Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 3acf1dd1-4e83-409e-8cf5-da500dfaee8a · outbound

This paper cites Fast spectrogram inversion using multi-head convolutional neural networks,.

Efficient Neural and Numerical Methods for High-Quality Online Speech Spectrogram Inversion via Gradient Theorem Fast spectrogram inversion using multi-head convolutional neural networks,

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:26:43.848466Z

Source-reported events for the cited work

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Pith citing papers

Observation 928c7f62-6786-4e02-9886-639ab021237a · inbound