Likelihood-Free Variational Autoencoders | Paper Citation Record

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This paper cites Auto-encoding variational bayes,.

Likelihood-Free Variational Autoencoders Auto-encoding variational bayes,

Reference 1

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Observation b1051c22-59d2-4fb3-8c7b-c2d014fab8fc · outbound

This paper cites Generative adversarial nets,.

Likelihood-Free Variational Autoencoders Generative adversarial nets,

Reference 2

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Observation 8d704956-7041-4e7a-9038-07ee4ad732f7 · outbound

This paper cites Variational inference with normalizing flows,.

Likelihood-Free Variational Autoencoders Variational inference with normalizing flows,

Reference 3

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Observation 6903fc7f-cfa3-4999-ac2c-cf336a07512c · outbound

This paper cites Make a face: To- wards arbitrary high fidelity face manipulation,.

Likelihood-Free Variational Autoencoders Make a face: To- wards arbitrary high fidelity face manipulation,

Reference 4

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Observation ed68856e-f3d4-4996-87a8-3c8b73affbf6 · outbound

This paper cites Introvae: Introspective variational autoencoders for photographic image synthesis,.

Likelihood-Free Variational Autoencoders Introvae: Introspective variational autoencoders for photographic image synthesis,

Reference 5

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Observation 889fdc3c-8800-4b0a-9c6c-3941f05531e0 · outbound

This paper cites Conditional variational autoencoder with adversarial learning for end-to-end text-to-speech,.

Likelihood-Free Variational Autoencoders Conditional variational autoencoder with adversarial learning for end-to-end text-to-speech,

Reference 6

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Observation 74436b20-a320-4656-872c-1e3c9804e0c6 · outbound

This paper cites Portaspeech: Portable and high-quality generative text-to- speech,.

Likelihood-Free Variational Autoencoders Portaspeech: Portable and high-quality generative text-to- speech,

Reference 7

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Observation bd1b36f2-f93a-48fe-9ff7-d9d58b191689 · outbound

This paper cites Vector quantized diffusion model for text-to-image synthesis,.

Likelihood-Free Variational Autoencoders Vector quantized diffusion model for text-to-image synthesis,

Reference 8

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Observation 81bf0e33-f969-43ed-8af6-9ef4ac0ff7ae · outbound

This paper cites Causal recurrent variational autoencoder for medical time series generation,.

Likelihood-Free Variational Autoencoders Causal recurrent variational autoencoder for medical time series generation,

Reference 9

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Observation 85d0d3fb-66bd-4a81-9061-f5b92817419e · outbound

This paper cites Markovian gaussian process variational autoencoders,.

Likelihood-Free Variational Autoencoders Markovian gaussian process variational autoencoders,

Reference 10

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Observation 1e9ab009-e22b-4b8d-9140-df06fee27d5c · outbound

This paper cites beta-vae: Learning basic visual concepts with a constrained variational framework,.

Likelihood-Free Variational Autoencoders beta-vae: Learning basic visual concepts with a constrained variational framework,

Reference 11

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Observation bcc2c708-b2e9-44e0-bcb9-a5eae11bd247 · outbound

This paper cites Isolating sources of disentanglement in variational autoencoders,.

Likelihood-Free Variational Autoencoders Isolating sources of disentanglement in variational autoencoders,

Reference 12

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Observation d3e1eaa2-ea88-4d4c-81f0-cf5539649f49 · outbound

This paper cites Distributional learning of variational autoencoder: application to syn- thetic data generation,.

Likelihood-Free Variational Autoencoders Distributional learning of variational autoencoder: application to syn- thetic data generation,

Reference 13

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Observation 437062b0-bcd4-48b8-830a-a1fe7699f515 · outbound

This paper cites Explicitly minimizing the blur error of variational autoencoders,.

Likelihood-Free Variational Autoencoders Explicitly minimizing the blur error of variational autoencoders,

Reference 14

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This paper cites An introduction to variational autoencoders,.

Likelihood-Free Variational Autoencoders An introduction to variational autoencoders,

Reference 15

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This paper cites Gaussian process prior varia- tional autoencoders,.

Likelihood-Free Variational Autoencoders Gaussian process prior varia- tional autoencoders,

Reference 16

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Observation 4c1aa2d3-e714-4703-bcc0-d680570b18ad · outbound

This paper cites Structured uncertainty prediction networks,.

Likelihood-Free Variational Autoencoders Structured uncertainty prediction networks,

Reference 17

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Observation 2a3cc196-76e7-4d1d-a55b-84095d17a0c7 · outbound

This paper cites Variational laplace autoencoders,.

Likelihood-Free Variational Autoencoders Variational laplace autoencoders,

Reference 18

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Observation 740bed35-2c5a-4e8f-892c-536ccf43f343 · outbound

This paper cites Poisson variational autoencoder,.

Likelihood-Free Variational Autoencoders Poisson variational autoencoder,

Reference 19

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Observation 4042dbe0-7e7c-41a7-ad90-ab866011345e · outbound

This paper cites Variational autoencoders for sparse and overdispersed discrete data,.

Likelihood-Free Variational Autoencoders Variational autoencoders for sparse and overdispersed discrete data,

Reference 20

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Observation 4c15e964-6ed6-46ad-b65b-3fc2c0f86c00 · outbound

This paper cites Autoencoding Variational Inference For Topic Models.

Likelihood-Free Variational Autoencoders Autoencoding Variational Inference For Topic Models

Reference 21

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This paper cites t3-variational autoencoder: Learning heavy- tailed data with student’s t and power divergence,.

Likelihood-Free Variational Autoencoders t3-variational autoencoder: Learning heavy- tailed data with student’s t and power divergence,

Reference 22

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Observation 49268f46-5ed5-4cbf-89f7-9356875a226b · outbound

This paper cites Student-t variational autoen- coder for robust density estimation.

Likelihood-Free Variational Autoencoders Student-t variational autoen- coder for robust density estimation

Reference 23

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This paper cites Nvae: A deep hierarchical variational autoencoder,.

Likelihood-Free Variational Autoencoders Nvae: A deep hierarchical variational autoencoder,

Reference 24

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This paper cites Ladder variational autoencoders,.

Likelihood-Free Variational Autoencoders Ladder variational autoencoders,

Reference 25

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Observation 3b6adfcd-6103-4ea8-b737-e10a98268e84 · outbound

This paper cites Learning Hierarchical Features from Generative Models.

Likelihood-Free Variational Autoencoders Learning Hierarchical Features from Generative Models

Reference 26

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This paper cites Autoencoding beyond pixels using a learned similarity metric,.

Likelihood-Free Variational Autoencoders Autoencoding beyond pixels using a learned similarity metric,

Reference 27

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This paper cites Adversarial symmetric variational autoencoder,.

Likelihood-Free Variational Autoencoders Adversarial symmetric variational autoencoder,

Reference 28

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Observation 9b819431-7821-45a5-8b9c-4af759e68cc1 · outbound

This paper cites VAEBM: A Symbiosis between Variational Autoencoders and Energy-based Models.

Likelihood-Free Variational Autoencoders VAEBM: A Symbiosis between Variational Autoencoders and Energy-based Models

Reference 29

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This paper cites Energy-calibrated vae with test time free lunch,.

Likelihood-Free Variational Autoencoders Energy-calibrated vae with test time free lunch,

Reference 30

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This paper cites Joint training of variational auto-encoder and latent energy-based model,.

Likelihood-Free Variational Autoencoders Joint training of variational auto-encoder and latent energy-based model,

Reference 31

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This paper cites A contrastive learning approach for training variational autoencoder priors,.

Likelihood-Free Variational Autoencoders A contrastive learning approach for training variational autoencoder priors,

Reference 32

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This paper cites Strictly proper scoring rules, prediction, and estimation,.

Likelihood-Free Variational Autoencoders Strictly proper scoring rules, prediction, and estimation,

Reference 33

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Observation 76176dee-a092-4d4c-b408-958f0af311a5 · outbound

This paper cites Likelihood-Free Inference with Generative Neural Networks via Scoring Rule Minimization.

Likelihood-Free Variational Autoencoders Likelihood-Free Inference with Generative Neural Networks via Scoring Rule Minimization

Reference 34

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This paper cites Disco nets: Dissimilarity coefficients networks,.

Likelihood-Free Variational Autoencoders Disco nets: Dissimilarity coefficients networks,

Reference 35

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This paper cites A spectral energy distance for parallel speech synthesis,.

Likelihood-Free Variational Autoencoders A spectral energy distance for parallel speech synthesis,

Reference 36

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Observation 415a2d40-7630-468b-9c0e-d2f29db6ba82 · outbound

This paper cites Generative machine learning methods for multi- variate ensemble postprocessing,.

Likelihood-Free Variational Autoencoders Generative machine learning methods for multi- variate ensemble postprocessing,

Reference 37

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This paper cites Engression: extrapolation through the lens of distributional regression,.

Likelihood-Free Variational Autoencoders Engression: extrapolation through the lens of distributional regression,

Reference 38

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This paper cites Probabilistic forecasting with gener- ative networks via scoring rule minimization,.

Likelihood-Free Variational Autoencoders Probabilistic forecasting with gener- ative networks via scoring rule minimization,

Reference 39

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Observation 6268bb0e-40bb-4f18-842b-f6b7258a6ad4 · outbound

This paper cites Adversarial Autoencoders.

Likelihood-Free Variational Autoencoders Adversarial Autoencoders

Reference 40

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This paper cites Adversarial Feature Learning.

Likelihood-Free Variational Autoencoders Adversarial Feature Learning

Reference 41

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This paper cites Adversarially Learned Inference.

Likelihood-Free Variational Autoencoders Adversarially Learned Inference

Reference 42

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This paper cites Improved techniques for training gans,.

Likelihood-Free Variational Autoencoders Improved techniques for training gans,

Reference 43

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This paper cites MVG-CRPS: A Robust Loss Function for Multivariate Probabilistic Forecasting.

Likelihood-Free Variational Autoencoders MVG-CRPS: A Robust Loss Function for Multivariate Probabilistic Forecasting

Reference 44

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This paper cites Energy statistics: A class of statistics based on distances,.

Likelihood-Free Variational Autoencoders Energy statistics: A class of statistics based on distances,

Reference 45

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This paper cites A global geometric framework for nonlinear dimensionality reduction,.

Likelihood-Free Variational Autoencoders A global geometric framework for nonlinear dimensionality reduction,

Reference 46

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This paper cites an unresolved cited work.

Likelihood-Free Variational Autoencoders Unresolved cited work

Reference 47

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This paper cites Generating images with perceptual similarity metrics based on deep networks,.

Likelihood-Free Variational Autoencoders Generating images with perceptual similarity metrics based on deep networks,

Reference 48

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This paper cites Diagnosing and enhancing V AE models,.

Likelihood-Free Variational Autoencoders Diagnosing and enhancing V AE models,

Reference 49

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This paper cites Simple and effective vae training with calibrated decoders,.

Likelihood-Free Variational Autoencoders Simple and effective vae training with calibrated decoders,

Reference 50

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This paper cites A general and adaptive robust loss function,.

Likelihood-Free Variational Autoencoders A general and adaptive robust loss function,

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:42:35.332725Z

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Observation ea5e8cec-835c-442e-8e99-1ccc13e62172 · outbound

This paper cites Focal frequency loss for image reconstruction and synthesis,.

Likelihood-Free Variational Autoencoders Focal frequency loss for image reconstruction and synthesis,

Reference 52

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This paper cites Wasserstein Auto-Encoders.

Likelihood-Free Variational Autoencoders Wasserstein Auto-Encoders

Reference 53

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This paper cites Adversarial variational bayes: Unifying variational autoencoders and generative adversarial networks,.

Likelihood-Free Variational Autoencoders Adversarial variational bayes: Unifying variational autoencoders and generative adversarial networks,

Reference 54

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Observation 2421ce14-ad3f-4996-bb4b-fb3f498a61ac · outbound

This paper cites Deterministic decoding for discrete data in variational autoen- coders,.

Likelihood-Free Variational Autoencoders Deterministic decoding for discrete data in variational autoen- coders,

Reference 55

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Observation 492f83e7-49b3-4f65-81d3-fb1df2b2be71 · outbound

This paper cites Pixel recurrent neural networks,.

Likelihood-Free Variational Autoencoders Pixel recurrent neural networks,

Reference 56

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Observation b796cfc1-4fdc-440c-8b54-f48fe1bf8919 · outbound

This paper cites PixelCNN++: Improving the PixelCNN with Discretized Logistic Mixture Likelihood and Other Modifications.

Likelihood-Free Variational Autoencoders PixelCNN++: Improving the PixelCNN with Discretized Logistic Mixture Likelihood and Other Modifications

Reference 57

Resolution: unresolved; no resolver link, observed 2026-08-16T10:42:35.083424Z

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Observation 08287b42-27c0-4a96-aadb-b030b0b16a05 · outbound

This paper cites From Variational to Deterministic Autoencoders.

Likelihood-Free Variational Autoencoders From Variational to Deterministic Autoencoders

Reference 58

Resolution: unresolved; no resolver link, observed 2026-08-16T10:42:35.087479Z

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Observation 39f442f7-fa23-41db-b430-8fa87b7d0ae3 · outbound

This paper cites InfoVAE: Information Maximizing Variational Autoencoders.

Likelihood-Free Variational Autoencoders InfoVAE: Information Maximizing Variational Autoencoders

Reference 59

Resolution: unresolved; no resolver link, observed 2026-08-16T10:42:35.091004Z

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Observation d4c74f49-9ff1-4c30-88c7-0faf13b4b68a · outbound

This paper cites L2 loss assumes that the reconstruction error follows a Gaussian distribution, making it sensitive to outliers.

Likelihood-Free Variational Autoencoders L2 loss assumes that the reconstruction error follows a Gaussian distribution, making it sensitive to outliers

Reference 60

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:42:35.280752Z

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No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

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