- See Also
-
Links
- “Generating and Imputing Tabular Data via Diffusion and Flow-based Gradient-Boosted Trees”, Jolicoeur-Martineau et al 2023
- “InstaFlow: One Step Is Enough for High-Quality Diffusion-Based Text-to-Image Generation”, Liu et al 2023
- “Diffusion Models Beat GANs on Image Classification”, Mukhopadhyay et al 2023
- “SDXL § Micro-Conditioning: Conditioning the Model on Image Size”, Podell et al 2023 (page 3 org stability)
- “SDXL: Improving Latent Diffusion Models for High-Resolution Image Synthesis”, Podell et al 2023
- “Beyond Surface Statistics: Scene Representations in a Latent Diffusion Model”, Chen et al 2023
- “Exposing Flaws of Generative Model Evaluation Metrics and Their Unfair Treatment of Diffusion Models”, Stein et al 2023
- “StyleDrop: Text-to-Image Generation in Any Style”, Sohn et al 2023
- “Tree-Ring Watermarks: Fingerprints for Diffusion Images That Are Invisible and Robust”, Wen et al 2023
- “Spontaneous Symmetry Breaking in Generative Diffusion Models”, Raya & Ambrogioni 2023
- “Generalizable Synthetic Image Detection via Language-guided Contrastive Learning”, Wu et al 2023
- “Diffusart: Enhancing Line Art Colorization With Conditional Diffusion Models”, Carrillo et al 2023
- “Reference-based Image Composition With Sketch via Structure-aware Diffusion Model”, Kim et al 2023
- “Masked Diffusion Transformer Is a Strong Image Synthesizer”, Gao et al 2023
- “AnimeDiffusion: Anime Face Line Drawing Colorization via Diffusion Models”, Cao et al 2023
- “Prompting AI Art: An Investigation into the Creative Skill of Prompt Engineering”, Oppenlaender et al 2023
- “Consistency Models”, Song et al 2023
- “Understanding the Diffusion Objective As a Weighted Integral of ELBOs”, Kingma & Gao 2023
- “Hard Prompts Made Easy: Gradient-Based Discrete Optimization for Prompt Tuning and Discovery”, Wen et al 2023
- “Dreamix: Video Diffusion Models Are General Video Editors”, Molad et al 2023
- “Training Stable Diffusion from Scratch Costs <$160k”, Stephenson & Seguin 2023
- “Imitating Human Behavior With Diffusion Models”, Pearce et al 2023
- “Archisound: Audio Generation With Diffusion”, Schneider 2023
- “Msanii: High Fidelity Music Synthesis on a Shoestring Budget”, Maina 2023
- “DIRAC: Neural Image Compression With a Diffusion-Based Decoder”, Goose et al 2023
- “Artificial Intelligence and Art: Identifying the Esthetic Judgment Factors That Distinguish Human & Machine-generated Artwork”, Samo & Highhouse 2023
- “Tune-A-Video: One-Shot Tuning of Image Diffusion Models for Text-to-Video Generation”, Wu et al 2022
- “Point·E: A System for Generating 3D Point Clouds from Complex Prompts”, Nichol et al 2022
- “The Stable Artist: Steering Semantics in Diffusion Latent Space”, Brack et al 2022
- “Multi-Concept Customization of Text-to-Image Diffusion”, Kumari et al 2022
- “Multi-resolution Textual Inversion”, Daras & Dimakis 2022
- “Latent Video Diffusion Models for High-Fidelity Video Generation With Arbitrary Lengths”, He et al 2022
- “DreamArtist: Towards Controllable One-Shot Text-to-Image Generation via Contrastive Prompt-Tuning”, Dong et al 2022
- “VectorFusion: Text-to-SVG by Abstracting Pixel-Based Diffusion Models”, Jain et al 2022
- “InstructPix2Pix: Learning to Follow Image Editing Instructions”, Brooks et al 2022
- “Null-text Inversion for Editing Real Images Using Guided Diffusion Models”, Mokady et al 2022
- “DiffusionDet: Diffusion Model for Object Detection”, Chen et al 2022
- “Versatile Diffusion: Text, Images and Variations All in One Diffusion Model”, Xu et al 2022
- “Rickrolling the Artist: Injecting Invisible Backdoors into Text-Guided Image Generation Models”, Struppek et al 2022
- “EDiff-I: Text-to-Image Diffusion Models With an Ensemble of Expert Denoisers”, Balaji et al 2022
- “DiffusionDB: A Large-scale Prompt Gallery Dataset for Text-to-Image Generative Models”, Wang et al 2022
- “Imagic: Text-Based Real Image Editing With Diffusion Models”, Kawar et al 2022
- “Hierarchical Diffusion Models for Singing Voice Neural Vocoder”, Takahashi et al 2022
- “On Distillation of Guided Diffusion Models”, Meng et al 2022
- “Improving Sample Quality of Diffusion Models Using Self-Attention Guidance”, Hong et al 2022
- “RealSinger: Ultra-Realistic Singing Voice Generation via Stochastic Differential Equations”, Anonymous 2022
- “DreamFusion: Text-to-3D Using 2D Diffusion”, Poole et al 2022
- “Rectified Flow: A Marginal Preserving Approach to Optimal Transport”, Liu 2022
- “PFGM: Poisson Flow Generative Models”, Xu et al 2022
- “Brain Imaging Generation With Latent Diffusion Models”, Pinaya et al 2022
- “Soft Diffusion: Score Matching for General Corruptions”, Daras et al 2022
- “Flow Straight and Fast: Learning to Generate and Transfer Data With Rectified Flow”, Liu et al 2022
- “Frido: Feature Pyramid Diffusion for Complex Scene Image Synthesis”, Fan et al 2022
- “DreamBooth: Fine Tuning Text-to-Image Diffusion Models for Subject-Driven Generation”, Ruiz et al 2022
- “Understanding Diffusion Models: A Unified Perspective”, Luo 2022
- “Cold Diffusion: Inverting Arbitrary Image Transforms Without Noise”, Bansal et al 2022
- “Diffusion-QL: Diffusion Policies As an Expressive Policy Class for Offline Reinforcement Learning”, Wang et al 2022
- “Prompt-to-Prompt Image Editing With Cross Attention Control”, Hertz et al 2022
- “An Image Is Worth One Word: Personalizing Text-to-Image Generation Using Textual Inversion”, Gal et al 2022
- “Text-Guided Synthesis of Artistic Images With Retrieval-Augmented Diffusion Models”, Rombach et al 2022
- “NUWA-∞: Autoregressive over Autoregressive Generation for Infinite Visual Synthesis”, Wu et al 2022
- “IHDM: Generative Modelling With Inverse Heat Dissipation”, Rissanen et al 2022
- “DiffC: Lossy Compression With Gaussian Diffusion”, Theis et al 2022
- “Diffusion-GAN: Training GANs With Diffusion”, Wang et al 2022
- “Compositional Visual Generation With Composable Diffusion Models”, Liu et al 2022
- “Score-Based Generative Models Detect Manifolds”, Pidstrigach 2022
- “DPM-Solver: A Fast ODE Solver for Diffusion Probabilistic Model Sampling in Around 10 Steps”, Lu et al 2022
- “Elucidating the Design Space of Diffusion-Based Generative Models”, Karras et al 2022
- “Improved Vector Quantized Diffusion Models”, Tang et al 2022
- “Text2Human: Text-Driven Controllable Human Image Generation”, Jiang et al 2022
- “Maximum Likelihood Training of Implicit Nonlinear Diffusion Models”, Kim et al 2022
- “Flexible Diffusion Modeling of Long Videos”, Harvey et al 2022
- “Imagen: Photorealistic Text-to-Image Diffusion Models With Deep Language Understanding”, Saharia et al 2022
- “Planning With Diffusion for Flexible Behavior Synthesis”, Janner et al 2022
- “Diffusion Models for Adversarial Purification”, Nie et al 2022
- “Semi-Parametric Neural Image Synthesis”, Blattmann et al 2022
- “Video Diffusion Models”, Ho et al 2022
- “KNN-Diffusion: Image Generation via Large-Scale Retrieval”, Ashual et al 2022
- “Perception Prioritized Training of Diffusion Models”, Choi et al 2022
- “Diffusion Probabilistic Modeling for Video Generation”, Yang et al 2022
- “Diffusion Causal Models for Counterfactual Estimation”, Sanchez & Tsaftaris 2022
- “Learning Fast Samplers for Diffusion Models by Differentiating Through Sample Quality”, Watson et al 2022
- “From Data to Functa: Your Data Point Is a Function and You Should Treat It like One”, Dupont et al 2022
- “Denoising Diffusion Restoration Models”, Kawar et al 2022
- “DiffuseVAE: Efficient, Controllable and High-Fidelity Generation from Low-Dimensional Latents”, Pandey et al 2022
- “Itô-Taylor Sampling Scheme for Denoising Diffusion Probabilistic Models Using Ideal Derivatives”, Tachibana et al 2021
- “High-Resolution Image Synthesis With Latent Diffusion Models”, Rombach et al 2021
- “High Fidelity Visualization of What Your Self-Supervised Representation Knows About”, Bordes et al 2021
- “More Control for Free! Image Synthesis With Semantic Diffusion Guidance”, Liu et al 2021
- “Come-Closer-Diffuse-Faster: Accelerating Conditional Diffusion Models for Inverse Problems through Stochastic Contraction”, Chung et al 2021
- “VQ-DDM: Global Context With Discrete Diffusion in Vector Quantized Modelling for Image Generation”, Hu et al 2021
- “Diffusion Autoencoders: Toward a Meaningful and Decodable Representation”, Preechakul et al 2021
- “Vector Quantized Diffusion Model for Text-to-Image Synthesis”, Gu et al 2021
- “Blended Diffusion for Text-driven Editing of Natural Images”, Avrahami et al 2021
- “Classifier-Free Diffusion Guidance”, Ho & Salimans 2021
- “Unleashing Transformers: Parallel Token Prediction With Discrete Absorbing Diffusion for Fast High-Resolution Image Generation from Vector-Quantized Codes”, Bond-Taylor et al 2021
- “Restormer: Efficient Transformer for High-Resolution Image Restoration”, Zamir et al 2021
- “Tackling the Generative Learning Trilemma With Denoising Diffusion GANs”, Xiao et al 2021
- “Diffusion Normalizing Flow”, Zhang & Chen 2021
- “Palette: Image-to-Image Diffusion Models”, Saharia et al 2021
- “Unconditional Diffusion Guidance”, Ho & Salimans 2021
- “DiffusionCLIP: Text-guided Image Manipulation Using Diffusion Models”, Kim & Ye 2021
- “Progressive Distillation for Fast Sampling of Diffusion Models”, Salimans & Ho 2021
- “Generative Probabilistic Image Colorization”, Furusawa et al 2021
- “Bilateral Denoising Diffusion Models”, Lam et al 2021
- “ImageBART: Bidirectional Context With Multinomial Diffusion for Autoregressive Image Synthesis”, Esser et al 2021
- “Variational Diffusion Models”, Kingma et al 2021
- “LoRA: Low-Rank Adaptation of Large Language Models”, Hu et al 2021
- “PriorGrad: Improving Conditional Denoising Diffusion Models With Data-Dependent Adaptive Prior”, Lee et al 2021
- “Score-based Generative Modeling in Latent Space”, Vahdat et al 2021
- “CDM: Cascaded Diffusion Models for High Fidelity Image Generation”, Ho et al 2021
- “Learning to Efficiently Sample from Diffusion Probabilistic Models”, Watson et al 2021
- “Gotta Go Fast When Generating Data With Score-Based Models”, Jolicoeur-Martineau et al 2021
- “Diffusion Models Beat GANs on Image Synthesis”, Dhariwal & Nichol 2021
- “DiffSinger: Singing Voice Synthesis via Shallow Diffusion Mechanism”, Liu et al 2021
- “Image Super-Resolution via Iterative Refinement”, Saharia et al 2021
- “Learning Energy-Based Models by Diffusion Recovery Likelihood”, Gao et al 2021
- “Improved Denoising Diffusion Probabilistic Models”, Nichol & Dhariwal 2021
- “Denoising Diffusion Implicit Models”, Song et al 2021
- “Maximum Likelihood Training of Score-Based Diffusion Models”, Song et al 2021
- “Score-Based Generative Modeling through Stochastic Differential Equations”, Song et al 2020
- “Denoising Diffusion Probabilistic Models”, Ho et al 2020
- “Conceptual Captions: A Cleaned, Hypernymed, Image Alt-text Dataset For Automatic Image Captioning”, Sharma et al 2018
- “Research Ideas”, Gwern 2017
- “Improving Sampling from Generative Autoencoders With Markov Chains”, Creswell et al 2016
- “Deep Unsupervised Learning Using Nonequilibrium Thermodynamics”, Sohl-Dickstein et al 2015
- “A Connection Between Score Matching and Denoising Autoencoders”, Vincent 2011
- “Optimal Approximation of Signal Priors”, Hyvarinen 2008
- “Estimation of Non-Normalized Statistical Models by Score Matching”, Hyvarinen 2005
- “Generative Modeling by Estimating Gradients of the Data Distribution”
- Sort By Magic
- Wikipedia
- Miscellaneous
- Link Bibliography
See Also
Links
“Generating and Imputing Tabular Data via Diffusion and Flow-based Gradient-Boosted Trees”, Jolicoeur-Martineau et al 2023
“Generating and Imputing Tabular Data via Diffusion and Flow-based Gradient-Boosted Trees”
“InstaFlow: One Step Is Enough for High-Quality Diffusion-Based Text-to-Image Generation”, Liu et al 2023
“InstaFlow: One Step is Enough for High-Quality Diffusion-Based Text-to-Image Generation”
“Diffusion Models Beat GANs on Image Classification”, Mukhopadhyay et al 2023
“SDXL § Micro-Conditioning: Conditioning the Model on Image Size”, Podell et al 2023 (page 3 org stability)
“SDXL § Micro-Conditioning: Conditioning the Model on Image Size”
“SDXL: Improving Latent Diffusion Models for High-Resolution Image Synthesis”, Podell et al 2023
“SDXL: Improving Latent Diffusion Models for High-Resolution Image Synthesis”
“Beyond Surface Statistics: Scene Representations in a Latent Diffusion Model”, Chen et al 2023
“Beyond Surface Statistics: Scene Representations in a Latent Diffusion Model”
“Exposing Flaws of Generative Model Evaluation Metrics and Their Unfair Treatment of Diffusion Models”, Stein et al 2023
“StyleDrop: Text-to-Image Generation in Any Style”, Sohn et al 2023
“Tree-Ring Watermarks: Fingerprints for Diffusion Images That Are Invisible and Robust”, Wen et al 2023
“Tree-Ring Watermarks: Fingerprints for Diffusion Images that are Invisible and Robust”
“Spontaneous Symmetry Breaking in Generative Diffusion Models”, Raya & Ambrogioni 2023
“Spontaneous symmetry breaking in generative diffusion models”
“Generalizable Synthetic Image Detection via Language-guided Contrastive Learning”, Wu et al 2023
“Generalizable Synthetic Image Detection via Language-guided Contrastive Learning”
“Diffusart: Enhancing Line Art Colorization With Conditional Diffusion Models”, Carrillo et al 2023
“Diffusart: Enhancing Line Art Colorization with Conditional Diffusion Models”
“Reference-based Image Composition With Sketch via Structure-aware Diffusion Model”, Kim et al 2023
“Reference-based Image Composition with Sketch via Structure-aware Diffusion Model”
“Masked Diffusion Transformer Is a Strong Image Synthesizer”, Gao et al 2023
“Masked Diffusion Transformer is a Strong Image Synthesizer”
“AnimeDiffusion: Anime Face Line Drawing Colorization via Diffusion Models”, Cao et al 2023
“AnimeDiffusion: Anime Face Line Drawing Colorization via Diffusion Models”
“Prompting AI Art: An Investigation into the Creative Skill of Prompt Engineering”, Oppenlaender et al 2023
“Prompting AI Art: An Investigation into the Creative Skill of Prompt Engineering”
“Consistency Models”, Song et al 2023
“Understanding the Diffusion Objective As a Weighted Integral of ELBOs”, Kingma & Gao 2023
“Understanding the Diffusion Objective as a Weighted Integral of ELBOs”
“Hard Prompts Made Easy: Gradient-Based Discrete Optimization for Prompt Tuning and Discovery”, Wen et al 2023
“Hard Prompts Made Easy: Gradient-Based Discrete Optimization for Prompt Tuning and Discovery”
“Dreamix: Video Diffusion Models Are General Video Editors”, Molad et al 2023
“Training Stable Diffusion from Scratch Costs <$160k”, Stephenson & Seguin 2023
“Imitating Human Behavior With Diffusion Models”, Pearce et al 2023
“Archisound: Audio Generation With Diffusion”, Schneider 2023
“Msanii: High Fidelity Music Synthesis on a Shoestring Budget”, Maina 2023
“Msanii: High Fidelity Music Synthesis on a Shoestring Budget”
“DIRAC: Neural Image Compression With a Diffusion-Based Decoder”, Goose et al 2023
“DIRAC: Neural Image Compression with a Diffusion-Based Decoder”
“Artificial Intelligence and Art: Identifying the Esthetic Judgment Factors That Distinguish Human & Machine-generated Artwork”, Samo & Highhouse 2023
“Tune-A-Video: One-Shot Tuning of Image Diffusion Models for Text-to-Video Generation”, Wu et al 2022
“Tune-A-Video: One-Shot Tuning of Image Diffusion Models for Text-to-Video Generation”
“Point·E: A System for Generating 3D Point Clouds from Complex Prompts”, Nichol et al 2022
“Point·E: A System for Generating 3D Point Clouds from Complex Prompts”
“The Stable Artist: Steering Semantics in Diffusion Latent Space”, Brack et al 2022
“The Stable Artist: Steering Semantics in Diffusion Latent Space”
“Multi-Concept Customization of Text-to-Image Diffusion”, Kumari et al 2022
“Multi-resolution Textual Inversion”, Daras & Dimakis 2022
“Latent Video Diffusion Models for High-Fidelity Video Generation With Arbitrary Lengths”, He et al 2022
“Latent Video Diffusion Models for High-Fidelity Video Generation with Arbitrary Lengths”
“DreamArtist: Towards Controllable One-Shot Text-to-Image Generation via Contrastive Prompt-Tuning”, Dong et al 2022
“DreamArtist: Towards Controllable One-Shot Text-to-Image Generation via Contrastive Prompt-Tuning”
“VectorFusion: Text-to-SVG by Abstracting Pixel-Based Diffusion Models”, Jain et al 2022
“VectorFusion: Text-to-SVG by Abstracting Pixel-Based Diffusion Models”
“InstructPix2Pix: Learning to Follow Image Editing Instructions”, Brooks et al 2022
“InstructPix2Pix: Learning to Follow Image Editing Instructions”
“Null-text Inversion for Editing Real Images Using Guided Diffusion Models”, Mokady et al 2022
“Null-text Inversion for Editing Real Images using Guided Diffusion Models”
“DiffusionDet: Diffusion Model for Object Detection”, Chen et al 2022
“Versatile Diffusion: Text, Images and Variations All in One Diffusion Model”, Xu et al 2022
“Versatile Diffusion: Text, Images and Variations All in One Diffusion Model”
“Rickrolling the Artist: Injecting Invisible Backdoors into Text-Guided Image Generation Models”, Struppek et al 2022
“Rickrolling the Artist: Injecting Invisible Backdoors into Text-Guided Image Generation Models”
“EDiff-I: Text-to-Image Diffusion Models With an Ensemble of Expert Denoisers”, Balaji et al 2022
“eDiff-I: Text-to-Image Diffusion Models with an Ensemble of Expert Denoisers”
“DiffusionDB: A Large-scale Prompt Gallery Dataset for Text-to-Image Generative Models”, Wang et al 2022
“DiffusionDB: A Large-scale Prompt Gallery Dataset for Text-to-Image Generative Models”
“Imagic: Text-Based Real Image Editing With Diffusion Models”, Kawar et al 2022
“Imagic: Text-Based Real Image Editing with Diffusion Models”
“Hierarchical Diffusion Models for Singing Voice Neural Vocoder”, Takahashi et al 2022
“Hierarchical Diffusion Models for Singing Voice Neural Vocoder”
“On Distillation of Guided Diffusion Models”, Meng et al 2022
“Improving Sample Quality of Diffusion Models Using Self-Attention Guidance”, Hong et al 2022
“Improving Sample Quality of Diffusion Models Using Self-Attention Guidance”
“RealSinger: Ultra-Realistic Singing Voice Generation via Stochastic Differential Equations”, Anonymous 2022
“RealSinger: Ultra-Realistic Singing Voice Generation via Stochastic Differential Equations”
“DreamFusion: Text-to-3D Using 2D Diffusion”, Poole et al 2022
“Rectified Flow: A Marginal Preserving Approach to Optimal Transport”, Liu 2022
“Rectified Flow: A Marginal Preserving Approach to Optimal Transport”
“PFGM: Poisson Flow Generative Models”, Xu et al 2022
“Brain Imaging Generation With Latent Diffusion Models”, Pinaya et al 2022
“Soft Diffusion: Score Matching for General Corruptions”, Daras et al 2022
“Flow Straight and Fast: Learning to Generate and Transfer Data With Rectified Flow”, Liu et al 2022
“Flow Straight and Fast: Learning to Generate and Transfer Data with Rectified Flow”
“Frido: Feature Pyramid Diffusion for Complex Scene Image Synthesis”, Fan et al 2022
“Frido: Feature Pyramid Diffusion for Complex Scene Image Synthesis”
“DreamBooth: Fine Tuning Text-to-Image Diffusion Models for Subject-Driven Generation”, Ruiz et al 2022
“DreamBooth: Fine Tuning Text-to-Image Diffusion Models for Subject-Driven Generation”
“Understanding Diffusion Models: A Unified Perspective”, Luo 2022
“Cold Diffusion: Inverting Arbitrary Image Transforms Without Noise”, Bansal et al 2022
“Cold Diffusion: Inverting Arbitrary Image Transforms Without Noise”
“Diffusion-QL: Diffusion Policies As an Expressive Policy Class for Offline Reinforcement Learning”, Wang et al 2022
“Diffusion-QL: Diffusion Policies as an Expressive Policy Class for Offline Reinforcement Learning”
“Prompt-to-Prompt Image Editing With Cross Attention Control”, Hertz et al 2022
“Prompt-to-Prompt Image Editing with Cross Attention Control”
“An Image Is Worth One Word: Personalizing Text-to-Image Generation Using Textual Inversion”, Gal et al 2022
“An Image is Worth One Word: Personalizing Text-to-Image Generation using Textual Inversion”
“Text-Guided Synthesis of Artistic Images With Retrieval-Augmented Diffusion Models”, Rombach et al 2022
“Text-Guided Synthesis of Artistic Images with Retrieval-Augmented Diffusion Models”
“NUWA-∞: Autoregressive over Autoregressive Generation for Infinite Visual Synthesis”, Wu et al 2022
“NUWA-∞: Autoregressive over Autoregressive Generation for Infinite Visual Synthesis”
“IHDM: Generative Modelling With Inverse Heat Dissipation”, Rissanen et al 2022
“DiffC: Lossy Compression With Gaussian Diffusion”, Theis et al 2022
“Diffusion-GAN: Training GANs With Diffusion”, Wang et al 2022
“Compositional Visual Generation With Composable Diffusion Models”, Liu et al 2022
“Compositional Visual Generation with Composable Diffusion Models”
“Score-Based Generative Models Detect Manifolds”, Pidstrigach 2022
“DPM-Solver: A Fast ODE Solver for Diffusion Probabilistic Model Sampling in Around 10 Steps”, Lu et al 2022
“DPM-Solver: A Fast ODE Solver for Diffusion Probabilistic Model Sampling in Around 10 Steps”
“Elucidating the Design Space of Diffusion-Based Generative Models”, Karras et al 2022
“Elucidating the Design Space of Diffusion-Based Generative Models”
“Improved Vector Quantized Diffusion Models”, Tang et al 2022
“Text2Human: Text-Driven Controllable Human Image Generation”, Jiang et al 2022
“Text2Human: Text-Driven Controllable Human Image Generation”
“Maximum Likelihood Training of Implicit Nonlinear Diffusion Models”, Kim et al 2022
“Maximum Likelihood Training of Implicit Nonlinear Diffusion Models”
“Flexible Diffusion Modeling of Long Videos”, Harvey et al 2022
“Imagen: Photorealistic Text-to-Image Diffusion Models With Deep Language Understanding”, Saharia et al 2022
“Imagen: Photorealistic Text-to-Image Diffusion Models with Deep Language Understanding”
“Planning With Diffusion for Flexible Behavior Synthesis”, Janner et al 2022
“Diffusion Models for Adversarial Purification”, Nie et al 2022
“Semi-Parametric Neural Image Synthesis”, Blattmann et al 2022
“Video Diffusion Models”, Ho et al 2022
“KNN-Diffusion: Image Generation via Large-Scale Retrieval”, Ashual et al 2022
“Perception Prioritized Training of Diffusion Models”, Choi et al 2022
“Diffusion Probabilistic Modeling for Video Generation”, Yang et al 2022
“Diffusion Causal Models for Counterfactual Estimation”, Sanchez & Tsaftaris 2022
“Learning Fast Samplers for Diffusion Models by Differentiating Through Sample Quality”, Watson et al 2022
“Learning Fast Samplers for Diffusion Models by Differentiating Through Sample Quality”
“From Data to Functa: Your Data Point Is a Function and You Should Treat It like One”, Dupont et al 2022
“From data to functa: Your data point is a function and you should treat it like one”
“Denoising Diffusion Restoration Models”, Kawar et al 2022
“DiffuseVAE: Efficient, Controllable and High-Fidelity Generation from Low-Dimensional Latents”, Pandey et al 2022
“DiffuseVAE: Efficient, Controllable and High-Fidelity Generation from Low-Dimensional Latents”
“Itô-Taylor Sampling Scheme for Denoising Diffusion Probabilistic Models Using Ideal Derivatives”, Tachibana et al 2021
“Itô-Taylor Sampling Scheme for Denoising Diffusion Probabilistic Models using Ideal Derivatives”
“High-Resolution Image Synthesis With Latent Diffusion Models”, Rombach et al 2021
“High-Resolution Image Synthesis with Latent Diffusion Models”
“High Fidelity Visualization of What Your Self-Supervised Representation Knows About”, Bordes et al 2021
“High Fidelity Visualization of What Your Self-Supervised Representation Knows About”
“More Control for Free! Image Synthesis With Semantic Diffusion Guidance”, Liu et al 2021
“More Control for Free! Image Synthesis with Semantic Diffusion Guidance”
“Come-Closer-Diffuse-Faster: Accelerating Conditional Diffusion Models for Inverse Problems through Stochastic Contraction”, Chung et al 2021
“VQ-DDM: Global Context With Discrete Diffusion in Vector Quantized Modelling for Image Generation”, Hu et al 2021
“VQ-DDM: Global Context with Discrete Diffusion in Vector Quantized Modelling for Image Generation”
“Diffusion Autoencoders: Toward a Meaningful and Decodable Representation”, Preechakul et al 2021
“Diffusion Autoencoders: Toward a Meaningful and Decodable Representation”
“Vector Quantized Diffusion Model for Text-to-Image Synthesis”, Gu et al 2021
“Vector Quantized Diffusion Model for Text-to-Image Synthesis”
“Blended Diffusion for Text-driven Editing of Natural Images”, Avrahami et al 2021
“Blended Diffusion for Text-driven Editing of Natural Images”
“Classifier-Free Diffusion Guidance”, Ho & Salimans 2021
“Unleashing Transformers: Parallel Token Prediction With Discrete Absorbing Diffusion for Fast High-Resolution Image Generation from Vector-Quantized Codes”, Bond-Taylor et al 2021
“Restormer: Efficient Transformer for High-Resolution Image Restoration”, Zamir et al 2021
“Restormer: Efficient Transformer for High-Resolution Image Restoration”
“Tackling the Generative Learning Trilemma With Denoising Diffusion GANs”, Xiao et al 2021
“Tackling the Generative Learning Trilemma with Denoising Diffusion GANs”
“Diffusion Normalizing Flow”, Zhang & Chen 2021
“Palette: Image-to-Image Diffusion Models”, Saharia et al 2021
“Unconditional Diffusion Guidance”, Ho & Salimans 2021
“DiffusionCLIP: Text-guided Image Manipulation Using Diffusion Models”, Kim & Ye 2021
“DiffusionCLIP: Text-guided Image Manipulation Using Diffusion Models”
“Progressive Distillation for Fast Sampling of Diffusion Models”, Salimans & Ho 2021
“Progressive Distillation for Fast Sampling of Diffusion Models”
“Generative Probabilistic Image Colorization”, Furusawa et al 2021
“Bilateral Denoising Diffusion Models”, Lam et al 2021
“ImageBART: Bidirectional Context With Multinomial Diffusion for Autoregressive Image Synthesis”, Esser et al 2021
“ImageBART: Bidirectional Context with Multinomial Diffusion for Autoregressive Image Synthesis”
“Variational Diffusion Models”, Kingma et al 2021
“LoRA: Low-Rank Adaptation of Large Language Models”, Hu et al 2021
“PriorGrad: Improving Conditional Denoising Diffusion Models With Data-Dependent Adaptive Prior”, Lee et al 2021
“PriorGrad: Improving Conditional Denoising Diffusion Models with Data-Dependent Adaptive Prior”
“Score-based Generative Modeling in Latent Space”, Vahdat et al 2021
“CDM: Cascaded Diffusion Models for High Fidelity Image Generation”, Ho et al 2021
“CDM: Cascaded Diffusion Models for High Fidelity Image Generation”
“Learning to Efficiently Sample from Diffusion Probabilistic Models”, Watson et al 2021
“Learning to Efficiently Sample from Diffusion Probabilistic Models”
“Gotta Go Fast When Generating Data With Score-Based Models”, Jolicoeur-Martineau et al 2021
“Gotta Go Fast When Generating Data with Score-Based Models”
“Diffusion Models Beat GANs on Image Synthesis”, Dhariwal & Nichol 2021
“DiffSinger: Singing Voice Synthesis via Shallow Diffusion Mechanism”, Liu et al 2021
“DiffSinger: Singing Voice Synthesis via Shallow Diffusion Mechanism”
“Image Super-Resolution via Iterative Refinement”, Saharia et al 2021
“Learning Energy-Based Models by Diffusion Recovery Likelihood”, Gao et al 2021
“Learning Energy-Based Models by Diffusion Recovery Likelihood”
“Improved Denoising Diffusion Probabilistic Models”, Nichol & Dhariwal 2021
“Denoising Diffusion Implicit Models”, Song et al 2021
“Maximum Likelihood Training of Score-Based Diffusion Models”, Song et al 2021
“Maximum Likelihood Training of Score-Based Diffusion Models”
“Score-Based Generative Modeling through Stochastic Differential Equations”, Song et al 2020
“Score-Based Generative Modeling through Stochastic Differential Equations”
“Denoising Diffusion Probabilistic Models”, Ho et al 2020
“Research Ideas”, Gwern 2017
“Improving Sampling from Generative Autoencoders With Markov Chains”, Creswell et al 2016
“Improving Sampling from Generative Autoencoders with Markov Chains”
“Deep Unsupervised Learning Using Nonequilibrium Thermodynamics”, Sohl-Dickstein et al 2015
“Deep Unsupervised Learning using Nonequilibrium Thermodynamics”
“A Connection Between Score Matching and Denoising Autoencoders”, Vincent 2011
“A Connection Between Score Matching and Denoising Autoencoders”
“Optimal Approximation of Signal Priors”, Hyvarinen 2008
“Estimation of Non-Normalized Statistical Models by Score Matching”, Hyvarinen 2005
“Estimation of Non-Normalized Statistical Models by Score Matching”
“Generative Modeling by Estimating Gradients of the Data Distribution”
“Generative Modeling by Estimating Gradients of the Data Distribution”
Sort By Magic
Annotations sorted by machine learning into inferred 'tags'. This provides an alternative way to browse: instead of by date order, one can browse in topic order. The 'sorted' list has been automatically clustered into multiple sections & auto-labeled for easier browsing.
Beginning with the newest annotation, it uses the embedding of each annotation to attempt to create a list of nearest-neighbor annotations, creating a progression of topics. For more details, see the link.
diffusion-modeling
diffusion-gan
generative-models
energy-modeling
Wikipedia
Miscellaneous
-
/doc/ai/nn/diffusion/2023-podell-figure2-datalossduetononsquareimageaspectratios.png -
/doc/ai/nn/diffusion/2022-09-21-gwern-stablediffusionv14-circulardropcapinitialsamples.png -
/doc/ai/nn/diffusion/2022-09-20-novelai-kurumuz-animestablediffusion-asukasamples.png -
/doc/ai/nn/diffusion/2022-balaji-figure1-samplesoftexttoimagefromediffi.png -
/doc/ai/nn/diffusion/2022-ashual-figure5-knnretrievalimageediting.png -
/doc/ai/nn/diffusion/2021-nichol-figure10-scalinglawsforddpmincomputevsnllfid.png -
https://blog.metaphysic.ai/the-road-to-realistic-full-body-deepfakes/ -
https://blog.novelai.net/novelai-improvements-on-stable-diffusion-e10d38db82ac -
https://blog.research.google/2023/01/google-research-2022-beyond-language.html -
https://bonfx.com/how-to-use-dreamstudio-stablediffusion-to-create-a-traditional-illustration/ -
https://colab.research.google.com/drive/1dlgggNa5Mz8sEAGU0wFCHhGLFooW_pf1 -
https://discuss.huggingface.co/t/decoding-latents-to-rgb-without-upscaling/23204/4 -
https://docs.google.com/spreadsheets/d/14xTqtuV3BuKDNhLotB_d1aFlBGnDJOY0BRXJ8-86GpA/edit -
https://drive.google.com/drive/folders/1wXvivH2azyK0J-5kjxiq5_4BlMw0ztmx -
https://generalrobots.substack.com/p/dimension-hopper-part-1 -
https://github.com/marqo-ai/marqo/blob/mainline/examples/StableDiffusion/hot-dog-100k.md -
https://github.com/openai/guided-diffusion#download-pre-trained-models -
https://globalcomix.com/c/paintings-photographs/chapters/en/1/1 -
https://huggingface.co/Gustavosta/MagicPrompt-Stable-Diffusion -
https://huggingface.co/Onodofthenorth/SD_PixelArt_SpriteSheet_Generator -
https://huggingface.co/Ryukijano/CatCon-Controlnet-WD-1-5-b2R -
https://jxmo.notion.site/The-Weird-and-Wonderful-World-of-AI-Art-b9615a2e7278435b98380ff81ae1cf09 -
https://keras.io/examples/generative/random_walks_with_stable_diffusion/ -
https://lambdalabs.com/blog/inference-benchmark-stable-diffusion -
https://lxj616.github.io/jekyll/update/2022/05/14/rethinking-the-danbooru-2021-dataset.html -
https://medium.com/@enryu9000/anifusion-diffusion-models-for-anime-pictures-138cf1af2cbe -
https://nostalgebraist.tumblr.com/post/672300992964050944/franks-image-generation-model-explained -
https://paperswithcode.com/sota/text-to-image-generation-on-coco -
https://plai.cs.ubc.ca/2022/05/20/flexible-diffusion-modeling-of-long-videos/ -
https://pub.towardsai.net/stable-diffusion-based-image-compresssion-6f1f0a399202 -
https://restofworld.org/2023/ai-revolution-outsourced-workers/ -
https://saltacc.notion.site/saltacc/WD-1-5-Beta-3-Release-Notes-1e35a0ed1bb24c5b93ec79c45c217f63 -
https://talesofsyn.com/posts/creating-isometric-rpg-game-backgrounds -
https://twitter.com/BjoernKarmann/status/1663496103998750721 -
https://twitter.com/Omorfiamorphism/status/1564633854119477257 -
https://twitter.com/jasonbaldridge/status/1588017062802329604 -
https://twitter.com/pascalblanche/status/1552698745485246471 -
https://twitter.com/pharmapsychotic/status/1577465085575909376 -
https://www.hollywoodreporter.com/tv/tv-news/secret-invasion-ai-opening-1235521299/ -
https://www.reddit.com/r/StableDiffusion/comments/11f4zgt/remixing_memes_with_multi_controlnet_is/ -
https://www.reddit.com/r/StableDiffusion/comments/15aapcb/sdxl_10_is_out/ -
https://www.reddit.com/r/StableDiffusion/comments/ys434h/animating_generated_face_test/ -
https://www.reddit.com/r/StableDiffusion/comments/z0xyk2/dreambooth_model_for_cutting_machines/ -
https://www.reddit.com/r/aigamedev/comments/142j3yt/valve_is_not_willing_to_publish_games_with_ai/ -
https://www.reddit.com/r/midjourney/comments/15mkgho/realistic_retro_ghibli_pok%C3%A9mon/ -
https://www.reddit.com/r/sdnsfw/comments/ylo4eh/huge_list_of_sexy_tested_photorealism_keywords/ -
https://www.samdickie.me/writing/experiment-1-creating-a-landing-page-using-ai-tools-no-code -
https://www.stavros.io/posts/compressing-images-with-stable-diffusion/
Link Bibliography
-
https://arxiv.org/abs/2309.06380: “InstaFlow: One Step Is Enough for High-Quality Diffusion-Based Text-to-Image Generation”, Xingchao Liu, Xiwen Zhang, Jianzhu Ma, Jian Peng, Qiang Liu -
https://arxiv.org/pdf/2307.01952.pdf#page=3&org=stability: “SDXL § Micro-Conditioning: Conditioning the Model on Image Size”, Dustin Podell, Zion English, Kyle Lacey, Andreas Blattmann, Tim Dockhorn, Jonas Müller, Joe Penna, Robin Rombach -
https://arxiv.org/abs/2307.01952#stability: “SDXL: Improving Latent Diffusion Models for High-Resolution Image Synthesis”, Dustin Podell, Zion English, Kyle Lacey, Andreas Blattmann, Tim Dockhorn, Jonas Müller, Joe Penna, Robin Rombach -
https://arxiv.org/abs/2303.14389: “Masked Diffusion Transformer Is a Strong Image Synthesizer”, Shanghua Gao, Pan Zhou, Ming-Ming Cheng, Shuicheng Yan -
https://arxiv.org/abs/2303.01469#openai: “Consistency Models”, Yang Song, Prafulla Dhariwal, Mark Chen, Ilya Sutskever -
https://arxiv.org/abs/2302.01329#google: “Dreamix: Video Diffusion Models Are General Video Editors”, -
https://raw.githubusercontent.com/flavioschneider/master-thesis/main/audio_diffusion_thesis.pdf: “Archisound: Audio Generation With Diffusion”, Flavio Schneider -
2023-samo.pdf: “Artificial Intelligence and Art: Identifying the Esthetic Judgment Factors That Distinguish Human & Machine-generated Artwork”, Andrew Samo, Scott Highhouse -
https://arxiv.org/abs/2212.08751#openai: “Point·E: A System for Generating 3D Point Clouds from Complex Prompts”, Alex Nichol, Heewoo Jun, Prafulla Dhariwal, Pamela Mishkin, Mark Chen -
https://arxiv.org/abs/2211.09800: “InstructPix2Pix: Learning to Follow Image Editing Instructions”, Tim Brooks, Aleksander Holynski, Alexei A. Efros -
https://arxiv.org/abs/2211.09788: “DiffusionDet: Diffusion Model for Object Detection”, Shoufa Chen, Peize Sun, Yibing Song, Ping Luo -
https://arxiv.org/abs/2211.01324#nvidia: “EDiff-I: Text-to-Image Diffusion Models With an Ensemble of Expert Denoisers”, -
https://arxiv.org/abs/2210.07508#sony: “Hierarchical Diffusion Models for Singing Voice Neural Vocoder”, Naoya Takahashi, Mayank Kumar, Singh, Yuki Mitsufuji -
https://arxiv.org/abs/2210.03142#google: “On Distillation of Guided Diffusion Models”, Chenlin Meng, Ruiqi Gao, Diederik P. Kingma, Stefano Ermon, Jonathan Ho, Tim Salimans -
https://arxiv.org/abs/2208.12242#google: “DreamBooth: Fine Tuning Text-to-Image Diffusion Models for Subject-Driven Generation”, Nataniel Ruiz, Yuanzhen Li, Varun Jampani, Yael Pritch, Michael Rubinstein, Kfir Aberman -
https://arxiv.org/abs/2208.01618: “An Image Is Worth One Word: Personalizing Text-to-Image Generation Using Textual Inversion”, Rinon Gal, Yuval Alaluf, Yuval Atzmon, Or Patashnik, Amit H. Bermano, Gal Chechik, Daniel Cohen-Or -
https://arxiv.org/abs/2207.09814#microsoft: “NUWA-∞: Autoregressive over Autoregressive Generation for Infinite Visual Synthesis”, Chenfei Wu, Jian Liang, Xiaowei Hu, Zhe Gan, Jianfeng Wang, Lijuan Wang, Zicheng Liu, Yuejian Fang, Nan Duan -
https://arxiv.org/abs/2205.16007#microsoft: “Improved Vector Quantized Diffusion Models”, Zhicong Tang, Shuyang Gu, Jianmin Bao, Dong Chen, Fang Wen -
https://arxiv.org/abs/2205.11487#google: “Imagen: Photorealistic Text-to-Image Diffusion Models With Deep Language Understanding”, -
https://arxiv.org/abs/2205.07460: “Diffusion Models for Adversarial Purification”, Weili Nie, Brandon Guo, Yujia Huang, Chaowei Xiao, Arash Vahdat, Anima Anandkumar -
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/2112.05744: “More Control for Free! Image Synthesis With Semantic Diffusion Guidance”, -
https://arxiv.org/abs/2106.09685: “LoRA: Low-Rank Adaptation of Large Language Models”, Edward J. Hu, Yelong Shen, Phillip Wallis, Zeyuan Allen-Zhu, Yuanzhi Li, Shean Wang, Lu Wang, Weizhu Chen -
https://cascaded-diffusion.github.io/: “CDM: Cascaded Diffusion Models for High Fidelity Image Generation”, Jonathan Ho, Chitwan Saharia, William Chan, David J. Fleet, Mohammad Norouzi, Tim Salimans -
https://arxiv.org/abs/2105.05233#openai: “Diffusion Models Beat GANs on Image Synthesis”, Prafulla Dhariwal, Alex Nichol -
https://arxiv.org/abs/2104.07636#google: “Image Super-Resolution via Iterative Refinement”, Chitwan Saharia, Jonathan Ho, William Chan, Tim Salimans, David J. Fleet, Mohammad Norouzi -
https://arxiv.org/abs/2102.09672#openai: “Improved Denoising Diffusion Probabilistic Models”, Alex Nichol, Prafulla Dhariwal -
2018-sharma.pdf#google: “Conceptual Captions: A Cleaned, Hypernymed, Image Alt-text Dataset For Automatic Image Captioning”, Piyush Sharma, Nan Ding, Sebastian Goodman, Radu Soricut -
idea: “Research Ideas”, Gwern -
2011-vincent.pdf: “A Connection Between Score Matching and Denoising Autoencoders”, Pascal Vincent -
https://www.jmlr.org/papers/volume6/hyvarinen05a/hyvarinen05a.pdf: “Estimation of Non-Normalized Statistical Models by Score Matching”, Aapo Hyvärinen