1

『高效采样』

• Dynamic Scheduled Sampling with Imitation Loss for Neural Text Generation
• Truncated Diffusion Probabilistic Models and Diffusion-based Adversarial Auto-Encoders
• Denoising Diffusion Samplers
• Denoising MCMC for Accelerating Diffusion-Based Generative Models
• DPM-Solver++: Fast Solver for Guided Sampling of Diffusion Probabilistic Models
• Quasi-Taylor Samplers for Diffusion Generative Models based on Ideal Derivatives
• Fast Sampling of Diffusion Models with Exponential Integrator
• Accelerating Guided Diffusion Sampling with Splitting Numerical Methods
• Boomerang: Local sampling on image manifolds using diffusion models
• Markup-to-Image Diffusion Models with Scheduled Sampling

2

『和其他生成模型结合』

• Diffusion-GAN: Training GANs with Diffusion
• in Conversation based on offline reinforcement learning
• FastDiff 2: Dually Incorporating GANs into Diffusion Models for High-Quality Speech Synthesis
• Reduce, Reuse, Recycle: Compositional Generation with Energy-Based Diffusion Models and MCMC
• Geometric Networks Induced by Energy Constrained Diffusion
• Progressive Image Synthesis from Semantics to Details with Denoising Diffusion GAN
• Flow Matching for Generative Modeling
• SPI-GAN: Denoising Diffusion GANs with Straight-Path Interpolations
• Building Normalizing Flows with Stochastic Interpolants
• Guiding Energy-based Models via Contrastive Latent Variables
• Your Denoising Implicit Model is a Sub-optimal Ensemble of Denoising Predictions
• Thinking fourth dimensionally: Treating Time as a Random Variable in EBMs

3

『在CV、NLP领域的应用』

• Novel View Synthesis with Diffusion Models
• Pyramidal Denoising Diffusion Probabilistic Models
• Compositional Image Generation and Manipulation with Latent Diffusion Models
• Towards the Detection of Diffusion Model Deepfakes
• DifFace: Blind Face Restoration with Diffused Error Contraction
• Restoration based Generative Models
• Generative Modelling with Inverse Heat Dissipation
• Deep Watermarks for Attributing Generative Models
• Learning multi-scale local conditional probability models of images
• Images as Weight Matrices: Sequential Image Generation Through Synaptic Learning Rules
• Self-conditioned Embedding Diffusion for Text Generation
• Sequence to sequence text generation with diffusion models
• DiffusER: Diffusion via Edit-based Reconstruction
• SDMuse: Stochastic Differential Music Editing and Generation via Hybrid Representation
• Universal Speech Enhancement with Score-based Diffusion
• Score-based Generative 3D Mesh Modeling
• CAN: A simple, efficient and scalable contrastive masked autoencoder framework for learning visual representations
• Neural Volumetric Mesh Generator
• SketchKnitter: Vectorized Sketch Generation with Diffusion Models
• $DDM^2$: Self-Supervised Diffusion MRI Denoising with Generative Diffusion Models
• Neural Image Compression with a Diffusion-based Decoder
• Lossy Compression with Gaussian Diffusion
• Distilling Model Failures as Directions in Latent Space
• Lossy Image Compression with Conditional Diffusion Models
• Quantized Compressed Sensing with Score-Based Generative Models
• Out-of-distribution Detection with Diffusion-based Neighborhood

4

『在多模态领域的应用』

• DreamFusion: Text-to-3D using 2D Diffusion
• Diffusion-based Image Translation using disentangled style and content representation
• CUSTOMIZING PRE-TRAINED DIFFUSION MODELS FOR YOUR OWN DATA
• Human Motion Diffusion Model
• Prosody-TTS: Self-Supervised Prosody Pretraining with Latent Diffusion For Text-to-Speech
• Text-Guided Diffusion Image Style Transfer with Contrastive Loss Fine-tuning
• Meta-Learning via Classifier(-free) Guidance
• KNN-Diffusion: Image Generation via Large-Scale Retrieval
• DiffEdit: Diffusion-based semantic image editing with mask guidance
• Training-Free Structured Diffusion Guidance for Compositional Text-to-Image Synthesis
• Discrete Contrastive Diffusion for Cross-Modal Music and Image Generation
• Unified Discrete Diffusion for Simultaneous Vision-Language Generation
• ResGrad: Residual Denoising Diffusion Probabilistic Models for Text to Speech
• Re-Imagen: Retrieval-Augmented Text-to-Image Generator
• Prompt-to-Prompt Image Editing with Cross-Attention Control

5

『与强化学习结合』

• Diffusion Policies as an Expressive Policy Class for Offline Reinforcement Learning
• Offline Reinforcement Learning via High-Fidelity Generative Behavior Modeling
• Provably Efficient Reinforcement Learning for Online Adaptive Influence Maximization
• Variational Reparametrized Policy Learning with Differentiable Physics
• Is Conditional Generative Modeling all you need for Decision Making?

6

『分子图建模』

• Diffusion Probabilistic Modeling of Protein Backbones in 3D for the motif-scaffolding problem
• Protein structure generation via folding diffusion
• Pre-training Protein Structure Encoder via Siamese Diffusion Trajectory Prediction
• DiffDock: Diffusion Steps, Twists, and Turns for Molecular Docking
• Pocket-specific 3D Molecule Generation by Fragment-based Autoregressive Diffusion Models
• Equivariant 3D-Conditional Diffusion Models for Molecular Linker Design
• Structure-based Drug Design with Equivariant Diffusion Models
• Equivariant Energy-Guided SDE for Inverse Molecular Design
• 3D Equivariant Diffusion for Target-Aware Molecule Generation and Affinity Prediction
• Exploring Chemical Space with Score-based Out-of-distribution Generation
• Protein Sequence and Structure Co-Design with Equivariant Translation

7

『扩散模型理论与理解』

• Information-Theoretic Diffusion
• Analyzing diffusion as serial reproduction
• Sampling is as easy as learning the score: theory for diffusion models with minimal data assumptions
• Diffusion Models Already Have A Semantic Latent Space
• Unifying Diffusion Models' Latent Space, with Applications to CycleDiffusion and Guidance
• Understanding DDPM Latent Codes Through Optimal Transport
• Interpreting Neural Networks Through the Lens of Heat Flow
• gDDIM: Generalized denoising diffusion implicit models

8

『扩散模型泛化与扩展』

• Soft Diffusion: Score Matching For General Corruptions
• Where to Diffuse, How to Diffuse and How to get back: Learning in Multivariate Diffusions
• Blurring Diffusion Models
• Diffusion Probabilistic Fields
• Neural Diffusion Processes
• Pseudoinverse-Guided Diffusion Models for Inverse Problems
• Removing Structured Noise with Diffusion Models
• f-DM: A Multi-stage Diffusion Model via Progressive Signal Transformation
• Iterative α-(de)Blending: Learning a Deterministic Mapping Between Arbitrary Densities
• Score-Based Graph Generative Modeling with Self-Guided Latent Diffusion
• Self-Guided Diffusion Models
• From Points to Functions: Infinite-dimensional Representations in Diffusion Models
• Score Matching via Differentiable Physics
• Approximated Anomalous Diffusion: Gaussian Mixture Score-based Generative Models
• Action Matching: A Variational Method for Learning Stochastic Dynamics from Samples
• Autoregressive Generative Modeling with Noise Conditional Maximum Likelihood Estimation
• DIFFUSION GENERATIVE MODELS ON SO(3)
• Diffusion Posterior Sampling for General Noisy Inverse Problems

9

『扩散模型迁移』

• Transferring Pretrained Diffusion Probabilistic Models
• Cold Diffusion: Inverting Arbitrary Image Transforms Without Noise
• Dual-Domain Diffusion Based Progressive Style Rendering towards Semantic Structure Preservation
• Dual Diffusion Implicit Bridges for Image-to-Image Translation
• Learning to Learn with Generative Models of Neural Network Checkpoints
• Zero-Shot Image Restoration Using Denoising Diffusion Null-Space Model

10

『特殊结构数据的建模』

• Autoregressive Diffusion Model for Graph Generation
• Analog Bits: Generating Discrete Data using Diffusion Models with Self-Conditioning
• TabDDPM: Modelling Tabular Data with Diffusion Models
• ChiroDiff: Modelling chirographic data with Diffusion Models
• Modeling Temporal Data as Continuous Functions with Process Diffusion
• Domain Specific Denoising Diffusion Probabilistic Models for Brain Dynamics
• Discrete Predictor-Corrector Diffusion Models for Image Synthesis
• Diffusion-based point cloud generation with smoothness constraints
• Computational Doob h-transforms for Online Filtering of Discretely Observed Diffusions
• Imitating Human Behaviour with Diffusion Models
• Learning Diffusion Bridges on Constrained Domains
• DiGress: Discrete Denoising diffusion for graph generation
• Score-based Continuous-time Discrete Diffusion Models
• Brain Signal Generation and Data Augmentation with a Single-Step Diffusion Probabilistic Model

11

『鲁棒性与稳定性』

• DensePure: Understanding Diffusion Models towards Adversarial Robustness
• Defending against Adversarial Audio via Diffusion Model
• PointDP: Diffusion-driven Purification against 3D Adversarial Point Clouds
• Diffusion Adversarial Representation Learning for Self-supervised Vessel Segmentation
• Improving Adversarial Robustness by Contrastive Guided Diffusion Process
• Robustness for Free: Adversarially Robust Anomaly Detection Through Diffusion Model
• (Certified!!) Adversarial Robustness for Free!
• The Biased Artist: Exploiting Cultural Biases via Homoglyphs in Text-Guided Image Generation Models
• Expected Perturbation Scores for Adversarial Detection
• Input Perturbation Reduces Exposure Bias in Diffusion Models
• Stable Target Field for Reduced Variance Score Estimation

12

『扩散模型的隐私保护』

• Membership Inference Attacks Against Text-to-image Generation Models
• Differentially Private Diffusion Models

13

『其他方向』

• OCD: Learning to Overfit with Conditional Diffusion Models
• Denoising Diffusion Error Correction Codes
• Neural Lagrangian Schrodinger Bridge: Diffusion Modeling for Population Dynamics
• Diffusion Models for Causal Discovery via Topological Ordering
• Transport with Support: Data-Conditional Diffusion Bridges
• A Score-Based Model for Learning Neural Wavefunctions

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