- See Also
-
Links
- “Vector Quantized Image-to-Image Translation”, Et Al 2022
- “Draft-and-Revise: Effective Image Generation With Contextual RQ-Transformer”, Et Al 2022
- “Closing the Gap: Exact Maximum Likelihood Training of Generative Autoencoders Using Invertible Layers (AEF)”, Et Al 2022
- “AvatarCLIP: Zero-Shot Text-Driven Generation and Animation of 3D Avatars”, Et Al 2022
- “NaturalSpeech: End-to-End Text to Speech Synthesis With Human-Level Quality”, Et Al 2022
- “VQGAN-CLIP: Open Domain Image Generation and Editing With Natural Language Guidance”, Et Al 2022
- “TATS: Long Video Generation With Time-Agnostic VQGAN and Time-Sensitive Transformer”, Et Al 2022
- “Diffusion Probabilistic Modeling for Video Generation”, Et Al 2022
- “Polarity Sampling: Quality and Diversity Control of Pre-Trained Generative Networks via Singular Values”, Et Al 2022
- “Variational Autoencoders Without the Variation”, Et Al 2022
- “Vector-quantized Image Modeling With Improved VQGAN”, Et Al 2022
- “MLR: A Model of Working Memory for Latent Representations”, Et Al 2022
- “CM3: A Causal Masked Multimodal Model of the Internet”, Et Al 2022
- “Design Guidelines for Prompt Engineering Text-to-Image Generative Models”, 2022
- “DiffuseVAE: Efficient, Controllable and High-Fidelity Generation from Low-Dimensional Latents”, Et Al 2022
- “ERNIE-ViLG: Unified Generative Pre-training for Bidirectional Vision-Language Generation”, Et Al 2021
- “Discovering State Variables Hidden in Experimental Data”, Et Al 2021
- “High-Resolution Image Synthesis With Latent Diffusion Models”, Et Al 2021
- “VQ-DDM: Global Context With Discrete Diffusion in Vector Quantized Modelling for Image Generation”, Et Al 2021
- “Vector Quantized Diffusion Model for Text-to-Image Synthesis”, Et Al 2021
- “L-Verse: Bidirectional Generation Between Image and Text”, Et Al 2021
- “Passive Non-Line-of-Sight Imaging Using Optimal Transport”, Et Al 2021
- “Unsupervised Deep Learning Identifies Semantic Disentanglement in Single Inferotemporal Face Patch Neurons”, Et Al 2021
- “Telling Creative Stories Using Generative Visual Aids”, 2021
- “Illiterate DALL·E Learns to Compose”, Et Al 2021
- “Score-based Generative Modeling in Latent Space”, Et Al 2021
- “Vector Quantized Models for Planning”, Et Al 2021
- “NWT: Towards Natural Audio-to-video Generation With Representation Learning”, Et Al 2021
- “VideoGPT: Video Generation Using VQ-VAE and Transformers”, Et Al 2021
- “Symbolic Music Generation With Diffusion Models”, Et Al 2021
- “Deep Generative Modelling: A Comparative Review of VAEs, GANs, Normalizing Flows, Energy-Based and Autoregressive Models”, Bond-Et Al 2021
- “Greedy Hierarchical Variational Autoencoders (GHVAEs) for Large-Scale Video Prediction”, Et Al 2021
- “CW-VAE: Clockwork Variational Autoencoders”, Et Al 2021
- “Denoising Diffusion Implicit Models”, Et Al 2021
- “DALL·E 1: Creating Images from Text: We’ve Trained a Neural Network Called DALL·E That Creates Images from Text Captions for a Wide Range of Concepts Expressible in Natural Language”, Et Al 2021
- “VQ-GAN: Taming Transformers for High-Resolution Image Synthesis”, Et Al 2020
- “Very Deep VAEs Generalize Autoregressive Models and Can Outperform Them on Images”, 2020
- “NVAE: A Deep Hierarchical Variational Autoencoder”, 2020
- “Jukebox: We’re Introducing Jukebox, a Neural Net That Generates Music, including Rudimentary Singing, As Raw Audio in a Variety of Genres and Artist Styles. We’re Releasing the Model Weights and Code, along With a Tool to Explore the Generated Samples.”, Et Al 2020
- “Jukebox: A Generative Model for Music”, Et Al 2020
- “RL Agents Implicitly Learning Human Preferences”, 2020
- “Encoding Musical Style With Transformer Autoencoders”, Et Al 2019
- “Generating Furry Face Art from Sketches Using a GAN”, 2019
- “BART: Denoising Sequence-to-Sequence Pre-training for Natural Language Generation, Translation, and Comprehension”, Et Al 2019
- “Bayesian Parameter Estimation Using Conditional Variational Autoencoders for Gravitational-wave Astronomy”, Et Al 2019
- “In-field Whole Plant Maize Architecture Characterized by Latent Space Phenotyping”, Et Al 2019
- “Generating Diverse High-Fidelity Images With VQ-VAE-2”, Et Al 2019
- “Hierarchical Autoregressive Image Models With Auxiliary Decoders”, Et Al 2019
- “Anime Neural Net Graveyard”, 2019
- “How AI Training Scales”, Et Al 2018
- “An Empirical Model of Large-Batch Training”, Et Al 2018
- “Neural Probabilistic Motor Primitives for Humanoid Control”, Et Al 2018
- “Piano Genie”, Et Al 2018
- “IntroVAE: Introspective Variational Autoencoders for Photographic Image Synthesis”, Et Al 2018
- “InfoNCE: Representation Learning With Contrastive Predictive Coding (CPC)”, Et Al 2018
- “The Challenge of Realistic Music Generation: Modelling Raw Audio at Scale”, Et Al 2018
- “Self-Net: Lifelong Learning via Continual Self-Modeling”, Et Al 2018
- “XGAN: Unsupervised Image-to-Image Translation for Many-to-Many Mappings”, Et Al 2017
- “VQ-VAE: Neural Discrete Representation Learning”, Et Al 2017
- “Vision-Based Multi-Task Manipulation for Inexpensive Robots Using End-To-End Learning from Demonstration”, Et Al 2017
- “Beta-VAE: Learning Basic Visual Concepts With a Constrained Variational Framework”, Et Al 2017
- “Neural Audio Synthesis of Musical Notes With WaveNet Autoencoders”, Et Al 2017
- “Prediction and Control With Temporal Segment Models”, Et Al 2017
- “Discovering Objects and Their Relations from Entangled Scene Representations”, Et Al 2017
- “Categorical Reparameterization With Gumbel-Softmax”, Et Al 2016
- “The Concrete Distribution: A Continuous Relaxation of Discrete Random Variables”, Et Al 2016
- “Improving Sampling from Generative Autoencoders With Markov Chains”, Et Al 2016
- “Neural Photo Editing With Introspective Adversarial Networks”, Et Al 2016
- “Early Visual Concept Learning With Unsupervised Deep Learning”, Et Al 2016
- “Improving Variational Inference With Inverse Autoregressive Flow”, Et Al 2016
- “How Far Can We Go without Convolution: Improving Fully-connected Networks”, Et Al 2015
- “Semi-supervised Sequence Learning”, 2015
- “MADE: Masked Autoencoder for Distribution Estimation”, Et Al 2015
- “Analyzing Noise in Autoencoders and Deep Networks”, Et Al 2014
- “Auto-Encoding Variational Bayes”, 2013
- “A Connection Between Score Matching and Denoising Autoencoders”, 2011
- “Transformers As Variational Autoencoders”
- “Randomly Traversing the Manifold of Faces (2): Dataset: Labeled Faces in the Wild (LFW); Model: Variational Auto-Encoder (VAE) / Deep Latent Gaussian Model (DLGM).”
- Wikipedia
- Miscellaneous
- Link Bibliography
See Also
Links
“Vector Quantized Image-to-Image Translation”, Et Al 2022
“Vector Quantized Image-to-Image Translation”, 2022-07-27 ( ; similar)
“Draft-and-Revise: Effective Image Generation With Contextual RQ-Transformer”, Et Al 2022
“Draft-and-Revise: Effective Image Generation with Contextual RQ-Transformer”, 2022-06-09 ( ; similar)
“Closing the Gap: Exact Maximum Likelihood Training of Generative Autoencoders Using Invertible Layers (AEF)”, Et Al 2022
“Closing the gap: Exact maximum likelihood training of generative autoencoders using invertible layers (AEF)”, 2022-05-19 (similar)
“AvatarCLIP: Zero-Shot Text-Driven Generation and Animation of 3D Avatars”, Et Al 2022
“AvatarCLIP: Zero-Shot Text-Driven Generation and Animation of 3D Avatars”, 2022-05-17 ( ; similar; bibliography)
“NaturalSpeech: End-to-End Text to Speech Synthesis With Human-Level Quality”, Et Al 2022
“NaturalSpeech: End-to-End Text to Speech Synthesis with Human-Level Quality”, 2022-05-09 (similar; bibliography)
“VQGAN-CLIP: Open Domain Image Generation and Editing With Natural Language Guidance”, Et Al 2022
“VQGAN-CLIP: Open Domain Image Generation and Editing with Natural Language Guidance”, 2022-04-18 ( ; similar)
“TATS: Long Video Generation With Time-Agnostic VQGAN and Time-Sensitive Transformer”, Et Al 2022
“TATS: Long Video Generation with Time-Agnostic VQGAN and Time-Sensitive Transformer”, 2022-04-07 ( ; similar; bibliography)
“Diffusion Probabilistic Modeling for Video Generation”, Et Al 2022
“Diffusion Probabilistic Modeling for Video Generation”, 2022-03-16 ( ; similar)
“Polarity Sampling: Quality and Diversity Control of Pre-Trained Generative Networks via Singular Values”, Et Al 2022
“Polarity Sampling: Quality and Diversity Control of Pre-Trained Generative Networks via Singular Values”, 2022-03-03 ( ; similar; bibliography)
“Variational Autoencoders Without the Variation”, Et Al 2022
“Variational Autoencoders Without the Variation”, 2022-03-01 ( ; similar)
“Vector-quantized Image Modeling With Improved VQGAN”, Et Al 2022
“Vector-quantized Image Modeling with Improved VQGAN”, 2022-03-01 ( ; similar; bibliography)
“MLR: A Model of Working Memory for Latent Representations”, Et Al 2022
“MLR: A model of working memory for latent representations”, 2022-02-03 ( ; similar)
“CM3: A Causal Masked Multimodal Model of the Internet”, Et Al 2022
“CM3: A Causal Masked Multimodal Model of the Internet”, 2022-01-19 ( ; similar)
“Design Guidelines for Prompt Engineering Text-to-Image Generative Models”, 2022
“Design Guidelines for Prompt Engineering Text-to-Image Generative Models”, 2022-01-07 ( ; similar; bibliography)
“DiffuseVAE: Efficient, Controllable and High-Fidelity Generation from Low-Dimensional Latents”, Et Al 2022
“DiffuseVAE: Efficient, Controllable and High-Fidelity Generation from Low-Dimensional Latents”, 2022-01-02 ( ; similar)
“ERNIE-ViLG: Unified Generative Pre-training for Bidirectional Vision-Language Generation”, Et Al 2021
“ERNIE-ViLG: Unified Generative Pre-training for Bidirectional Vision-Language Generation”, 2021-12-31 ( ; similar; bibliography)
“Discovering State Variables Hidden in Experimental Data”, Et Al 2021
“Discovering State Variables Hidden in Experimental Data”, 2021-12-20 (similar)
“High-Resolution Image Synthesis With Latent Diffusion Models”, Et Al 2021
“High-Resolution Image Synthesis with Latent Diffusion Models”, 2021-12-20 ( ; backlinks; similar; bibliography)
“VQ-DDM: Global Context With Discrete Diffusion in Vector Quantized Modelling for Image Generation”, Et Al 2021
“VQ-DDM: Global Context with Discrete Diffusion in Vector Quantized Modelling for Image Generation”, 2021-12-03 ( ; similar)
“Vector Quantized Diffusion Model for Text-to-Image Synthesis”, Et Al 2021
“Vector Quantized Diffusion Model for Text-to-Image Synthesis”, 2021-11-29 ( ; similar)
“L-Verse: Bidirectional Generation Between Image and Text”, Et Al 2021
“L-Verse: Bidirectional Generation Between Image and Text”, 2021-11-22 ( ; backlinks; similar; bibliography)
“Passive Non-Line-of-Sight Imaging Using Optimal Transport”, Et Al 2021
“Passive Non-Line-of-Sight Imaging Using Optimal Transport”, 2021-11-22 ( ; similar)
“Unsupervised Deep Learning Identifies Semantic Disentanglement in Single Inferotemporal Face Patch Neurons”, Et Al 2021
“Unsupervised deep learning identifies semantic disentanglement in single inferotemporal face patch neurons”, 2021-11-09 ( ; similar)
“Telling Creative Stories Using Generative Visual Aids”, 2021
“Telling Creative Stories Using Generative Visual Aids”, 2021-10-27 ( ; similar)
“Illiterate DALL·E Learns to Compose”, Et Al 2021
“Illiterate DALL·E Learns to Compose”, 2021-10-17 ( ; similar)
“Score-based Generative Modeling in Latent Space”, Et Al 2021
“Score-based Generative Modeling in Latent Space”, 2021-06-10 ( ; similar)
“Vector Quantized Models for Planning”, Et Al 2021
“Vector Quantized Models for Planning”, 2021-06-08 ( ; similar)
“NWT: Towards Natural Audio-to-video Generation With Representation Learning”, Et Al 2021
“NWT: Towards natural audio-to-video generation with representation learning”, 2021-06-08 ( ; similar)
“VideoGPT: Video Generation Using VQ-VAE and Transformers”, Et Al 2021
“VideoGPT: Video Generation using VQ-VAE and Transformers”, 2021-04-20 ( ; backlinks; similar; bibliography)
“Symbolic Music Generation With Diffusion Models”, Et Al 2021
“Symbolic Music Generation with Diffusion Models”, 2021-03-30 ( ; similar)
“Deep Generative Modelling: A Comparative Review of VAEs, GANs, Normalizing Flows, Energy-Based and Autoregressive Models”, Bond-Et Al 2021
“Deep Generative Modelling: A Comparative Review of VAEs, GANs, Normalizing Flows, Energy-Based and Autoregressive Models”, 2021-03-08 ( ; backlinks; similar)
“Greedy Hierarchical Variational Autoencoders (GHVAEs) for Large-Scale Video Prediction”, Et Al 2021
“Greedy Hierarchical Variational Autoencoders (GHVAEs) for Large-Scale Video Prediction”, 2021-03-06 ( ; similar)
“CW-VAE: Clockwork Variational Autoencoders”, Et Al 2021
“CW-VAE: Clockwork Variational Autoencoders”, 2021-02-18 ( ; similar)
“Denoising Diffusion Implicit Models”, Et Al 2021
“Denoising Diffusion Implicit Models”, 2021-01-25 ( ; similar)
“DALL·E 1: Creating Images from Text: We’ve Trained a Neural Network Called DALL·E That Creates Images from Text Captions for a Wide Range of Concepts Expressible in Natural Language”, Et Al 2021
“DALL·E 1: Creating Images from Text: We’ve trained a neural network called DALL·E that creates images from text captions for a wide range of concepts expressible in natural language”, 2021-01-05 ( ; backlinks; similar; bibliography)
“VQ-GAN: Taming Transformers for High-Resolution Image Synthesis”, Et Al 2020
“VQ-GAN: Taming Transformers for High-Resolution Image Synthesis”, 2020-12-17 ( ; backlinks; similar)
“Very Deep VAEs Generalize Autoregressive Models and Can Outperform Them on Images”, 2020
“Very Deep VAEs Generalize Autoregressive Models and Can Outperform Them on Images”, 2020-11-20 ( ; similar; bibliography)
“NVAE: A Deep Hierarchical Variational Autoencoder”, 2020
“NVAE: A Deep Hierarchical Variational Autoencoder”, 2020-07-08 ( ; similar; bibliography)
“Jukebox: We’re Introducing Jukebox, a Neural Net That Generates Music, including Rudimentary Singing, As Raw Audio in a Variety of Genres and Artist Styles. We’re Releasing the Model Weights and Code, along With a Tool to Explore the Generated Samples.”, Et Al 2020
“Jukebox: We’re introducing Jukebox, a neural net that generates music, including rudimentary singing, as raw audio in a variety of genres and artist styles. We’re releasing the model weights and code, along with a tool to explore the generated samples.”, 2020-04-30 ( ; backlinks; similar; bibliography)
“Jukebox: A Generative Model for Music”, Et Al 2020
“Jukebox: A Generative Model for Music”, 2020-04-30 ( ; backlinks; similar; bibliography)
“RL Agents Implicitly Learning Human Preferences”, 2020
“RL agents Implicitly Learning Human Preferences”, 2020-02-14 ( ; similar)
“Encoding Musical Style With Transformer Autoencoders”, Et Al 2019
“Encoding Musical Style with Transformer Autoencoders”, 2019-12-10 ( ; backlinks; similar)
“Generating Furry Face Art from Sketches Using a GAN”, 2019
“Generating Furry Face Art from Sketches using a GAN”, 2019-12-01 ( ; similar)
“BART: Denoising Sequence-to-Sequence Pre-training for Natural Language Generation, Translation, and Comprehension”, Et Al 2019
“BART: Denoising Sequence-to-Sequence Pre-training for Natural Language Generation, Translation, and Comprehension”, 2019-10-29 (similar; bibliography)
“Bayesian Parameter Estimation Using Conditional Variational Autoencoders for Gravitational-wave Astronomy”, Et Al 2019
“Bayesian parameter estimation using conditional variational autoencoders for gravitational-wave astronomy”, 2019-09-13 ( ; similar)
“In-field Whole Plant Maize Architecture Characterized by Latent Space Phenotyping”, Et Al 2019
“In-field whole plant maize architecture characterized by Latent Space Phenotyping”, 2019-09-10 ( ; backlinks; similar)
“Generating Diverse High-Fidelity Images With VQ-VAE-2”, Et Al 2019
“Generating Diverse High-Fidelity Images with VQ-VAE-2”, 2019-06-02 ( ; similar)
“Hierarchical Autoregressive Image Models With Auxiliary Decoders”, Et Al 2019
“Hierarchical Autoregressive Image Models with Auxiliary Decoders”, 2019-03-06 (similar)
“Anime Neural Net Graveyard”, 2019
“Anime Neural Net Graveyard”, 2019-02-04 ( ; backlinks; similar; bibliography)
“How AI Training Scales”, Et Al 2018
“How AI Training Scales”, 2018-12-14 ( ; backlinks; similar; bibliography)
“An Empirical Model of Large-Batch Training”, Et Al 2018
“An Empirical Model of Large-Batch Training”, 2018-12-14 ( ; similar)
“Neural Probabilistic Motor Primitives for Humanoid Control”, Et Al 2018
“Neural probabilistic motor primitives for humanoid control”, 2018-11-28 ( ; similar)
“Piano Genie”, Et Al 2018
“Piano Genie”, 2018-10-11 ( ; similar)
“IntroVAE: Introspective Variational Autoencoders for Photographic Image Synthesis”, Et Al 2018
“IntroVAE: Introspective Variational Autoencoders for Photographic Image Synthesis”, 2018-07-17 ( ; backlinks; similar)
“InfoNCE: Representation Learning With Contrastive Predictive Coding (CPC)”, Et Al 2018
“InfoNCE: Representation Learning with Contrastive Predictive Coding (CPC)”, 2018-07-10 ( ; similar)
“The Challenge of Realistic Music Generation: Modelling Raw Audio at Scale”, Et Al 2018
“The challenge of realistic music generation: modelling raw audio at scale”, 2018-06-26 ( ; similar)
“Self-Net: Lifelong Learning via Continual Self-Modeling”, Et Al 2018
“Self-Net: Lifelong Learning via Continual Self-Modeling”, 2018-05-25 ( ; similar)
“XGAN: Unsupervised Image-to-Image Translation for Many-to-Many Mappings”, Et Al 2017
“XGAN: Unsupervised Image-to-Image Translation for Many-to-Many Mappings”, 2017-11-14 ( ; similar)
“VQ-VAE: Neural Discrete Representation Learning”, Et Al 2017
“VQ-VAE: Neural Discrete Representation Learning”, 2017-11-02 ( ; similar)
“Vision-Based Multi-Task Manipulation for Inexpensive Robots Using End-To-End Learning from Demonstration”, Et Al 2017
“Vision-Based Multi-Task Manipulation for Inexpensive Robots Using End-To-End Learning from Demonstration”, 2017-07-10 ( ; similar)
“Beta-VAE: Learning Basic Visual Concepts With a Constrained Variational Framework”, Et Al 2017
“beta-VAE: Learning Basic Visual Concepts with a Constrained Variational Framework”, 2017-04-18 (similar)
“Neural Audio Synthesis of Musical Notes With WaveNet Autoencoders”, Et Al 2017
“Neural Audio Synthesis of Musical Notes with WaveNet Autoencoders”, 2017-04-05 ( ; similar)
“Prediction and Control With Temporal Segment Models”, Et Al 2017
“Prediction and Control with Temporal Segment Models”, 2017-03-12 ( ; similar)
“Discovering Objects and Their Relations from Entangled Scene Representations”, Et Al 2017
“Discovering objects and their relations from entangled scene representations”, 2017-02-16 ( ; similar)
“Categorical Reparameterization With Gumbel-Softmax”, Et Al 2016
“Categorical Reparameterization with Gumbel-Softmax”, 2016-11-03 ( ; similar)
“The Concrete Distribution: A Continuous Relaxation of Discrete Random Variables”, Et Al 2016
“The Concrete Distribution: A Continuous Relaxation of Discrete Random Variables”, 2016-11-02 ( ; similar)
“Improving Sampling from Generative Autoencoders With Markov Chains”, Et Al 2016
“Improving Sampling from Generative Autoencoders with Markov Chains”, 2016-10-28 ( ; similar)
“Neural Photo Editing With Introspective Adversarial Networks”, Et Al 2016
“Neural Photo Editing with Introspective Adversarial Networks”, 2016-09-22 ( ; backlinks; similar)
“Early Visual Concept Learning With Unsupervised Deep Learning”, Et Al 2016
“Early Visual Concept Learning with Unsupervised Deep Learning”, 2016-06-17 (similar)
“Improving Variational Inference With Inverse Autoregressive Flow”, Et Al 2016
“Improving Variational Inference with Inverse Autoregressive Flow”, 2016-06-15 (similar)
“How Far Can We Go without Convolution: Improving Fully-connected Networks”, Et Al 2015
“How far can we go without convolution: Improving fully-connected networks”, 2015-11-09 ( ; backlinks; similar)
“Semi-supervised Sequence Learning”, 2015
“Semi-supervised Sequence Learning”, 2015-11-04 ( ; backlinks; similar)
“MADE: Masked Autoencoder for Distribution Estimation”, Et Al 2015
“MADE: Masked Autoencoder for Distribution Estimation”, 2015-02-12
“Analyzing Noise in Autoencoders and Deep Networks”, Et Al 2014
“Analyzing noise in autoencoders and deep networks”, 2014-06-06 (similar)
“Auto-Encoding Variational Bayes”, 2013
“Auto-Encoding Variational Bayes”, 2013-12-20 ( ; similar)
“A Connection Between Score Matching and Denoising Autoencoders”, 2011
“A Connection Between Score Matching and Denoising Autoencoders”, 2011-07-01 ( ; similar; bibliography)
“Transformers As Variational Autoencoders”
“Randomly Traversing the Manifold of Faces (2): Dataset: Labeled Faces in the Wild (LFW); Model: Variational Auto-Encoder (VAE) / Deep Latent Gaussian Model (DLGM).”
Wikipedia
Miscellaneous
Link Bibliography
-
https://arxiv.org/abs/2205.08535
: “AvatarCLIP: Zero-Shot Text-Driven Generation and Animation of 3D Avatars”, Fangzhou Hong, Mingyuan Zhang, Liang Pan, Zhongang Cai, Lei Yang, Ziwei Liu: -
https://arxiv.org/abs/2205.04421#microsoft
: “NaturalSpeech: End-to-End Text to Speech Synthesis With Human-Level Quality”, : -
https://arxiv.org/abs/2204.03638#facebook
: “TATS: Long Video Generation With Time-Agnostic VQGAN and Time-Sensitive Transformer”, Songwei Ge, Thomas Hayes, Harry Yang, Xi Yin, Guan Pang, David Jacobs, Jia-Bin Huang, Devi Parikh: -
https://arxiv.org/abs/2203.01993
: “Polarity Sampling: Quality and Diversity Control of Pre-Trained Generative Networks via Singular Values”, Ahmed Imtiaz Humayun, Randall Balestriero, Richard Baraniuk: -
https://arxiv.org/abs/2110.04627#google
: “Vector-quantized Image Modeling With Improved VQGAN”, : -
2022-liu.pdf
: “Design Guidelines for Prompt Engineering Text-to-Image Generative Models”, Vivian Liu, Lydia B. Chilton: -
https://arxiv.org/abs/2112.15283#baidu
: “ERNIE-ViLG: Unified Generative Pre-training for Bidirectional Vision-Language Generation”, Han Zhang, Weichong Yin, Yewei Fang, Lanxin Li, Boqiang Duan, Zhihua Wu, Yu Sun, Hao Tian, Hua Wu, Haifeng Wang: -
https://arxiv.org/abs/2112.10752
: “High-Resolution Image Synthesis With Latent Diffusion Models”, Robin Rombach, Andreas Blattmann, Dominik Lorenz, Patrick Esser, Björn Ommer: -
https://arxiv.org/abs/2111.11133
: “L-Verse: Bidirectional Generation Between Image and Text”, : -
https://arxiv.org/abs/2104.10157
: “VideoGPT: Video Generation Using VQ-VAE and Transformers”, Wilson Yan, Yunzhi Zhang, Pieter Abbeel, Aravind Srinivas: -
https://openai.com/blog/dall-e/
: “DALL·E 1: Creating Images from Text: We’ve Trained a Neural Network Called DALL·E That Creates Images from Text Captions for a Wide Range of Concepts Expressible in Natural Language”, : -
https://arxiv.org/abs/2011.10650#openai
: “Very Deep VAEs Generalize Autoregressive Models and Can Outperform Them on Images”, Rewon Child: -
https://arxiv.org/abs/2007.03898#nvidia
: “NVAE: A Deep Hierarchical Variational Autoencoder”, Arash Vahdat, Jan Kautz: -
https://openai.com/blog/jukebox/
: “Jukebox: We’re Introducing Jukebox, a Neural Net That Generates Music, including Rudimentary Singing, As Raw Audio in a Variety of Genres and Artist Styles. We’re Releasing the Model Weights and Code, along With a Tool to Explore the Generated Samples.”, Prafulla Dhariwal, Heewoo Jun, Christine Payne, Jong Wook Kim, Alec Radford, Ilya Sutskever: -
https://cdn.openai.com/papers/jukebox.pdf
: “Jukebox: A Generative Model for Music”, Prafulla Dhariwal, Heewoo Jun, Christine Payne, Jong Wook Kim, Alec Radford, Ilya Sutskever: -
https://arxiv.org/abs/1910.13461#facebook
: “BART: Denoising Sequence-to-Sequence Pre-training for Natural Language Generation, Translation, and Comprehension”, : -
face-graveyard
: “Anime Neural Net Graveyard”, Gwern Branwen: -
https://openai.com/blog/science-of-ai/
: “How AI Training Scales”, Sam McCandlish, Jared Kaplan, Dario Amodei: -
2011-vincent.pdf
: “A Connection Between Score Matching and Denoising Autoencoders”, Pascal Vincent: