[arxiv 2023.02]Diffusion Model for Generative Image Denoising [PDF]
[AAAI 2023.02]ShiftDDPMs: Exploring Conditional Diffusion Models by Shifting Diffusion Trajectories [PDF]
[arxiv 2023.02]ReDi: Efficient Learning-Free Diffusion Inference via Trajectory Retrieval [PDF ]
[arxiv 2023.02]Q-Diffusion: Quantizing Diffusion Models [PDF]
[arxiv 2023.02]Boundary Guided Mixing Trajectory for Semantic Control with Diffusion Models [PDF]
[arxiv 2023.02]On Calibrating Diffusion Probabilistic Models [PDF]
[arxiv 2023.03]DIFFUSION PROBABILISTIC FIELDS [PDF]
[arxiv 2023.03]Multilevel Diffusion: Infinite Dimensional Score-Based Diffusion Models for Image Generation [PDF]
[arxiv 2023.03]End-to-End Diffusion Latent Optimization Improves Classifier Guidance [PDF]
[arxiv 2023.03]Exploring Continual Learning of Diffusion Models [PDF]
[arxiv 2023.03]Diffusion Models as Masked Autoencoders [PDF]
[arxiv 2023.04]Memory Efficient Diffusion Probabilistic Models via Patch-based Generation [PDF]
[arxiv 2023.05]Class-Balancing Diffusion Models [PDF]
[arxiv 2023.06]Multi-Architecture Multi-Expert Diffusion Models [PDF]
[arxiv 2023.06]Semi-Implicit Denoising Diffusion Models [PDF]
[arxiv 2023.06]Decoupled Diffusion Models with Explicit Transition Probability [PDF]
[arxiv 2023.07]DiffFlow: A Unified SDE Framework for Score-Based Diffusion Models and Generative Adversarial Networks [PDF]
[arxiv 2023.07]AdjointDPM: Adjoint Sensitivity Method for Gradient Backpropagation of Diffusion Probabilistic Models [PDF]
[arxiv 2023.07]Spatial-Frequency U-Net for Denoising Diffusion Probabilistic Models[PDF]
[arxiv 2023.12]Diffusion Models Without Attention [PDF]
[arxiv 2023.12]Analyzing and Improving the Training Dynamics of Diffusion Models[PDF]
[arxiv 2023.12]On Inference Stability for Diffusion Models [PDF]
[arxiv 2023.12]Diffusion Models With Learned Adaptive Noise [PDF]
[arxiv 2024.04]Denoising Monte Carlo Renders With Diffusion Models [PDF]
[arxiv 2024.04]Diffusion-RWKV: Scaling RWKV-Like Architectures for Diffusion Models [PDF]
[arxiv 2024.06] Dimba: Transformer-Mamba Diffusion Models [PDF]
[arxiv 2023.03]Masked Diffusion Transformer is a Strong Image Synthesizer [PDF]
[arxiv 2022]Accelerating Diffusion Sampling with Classifier-based Feature Distillation [PDF]
[arxiv 2022.12; NUS, ByteDance]Diffusion Probabilistic Model Made Slim [PDF, code]
[arxiv 2023.02]Example-Based Sampling with Diffusion Models [PDF]
[arxiv 2023.03]Efficient Diffusion Training via Min-SNR Weighting Strategy [PDF]
[arxiv 2023.03]SVDiff: Compact Parameter Space for Diffusion Fine-Tuning[PDF]
[arxiv 2023.03]Token Merging for Fast Stable Diffusion [PDF, code]
[arxiv 2023.04]A Closer Look at Parameter-Efficient Tuning in Diffusion Models [PDF]
[arxiv 2023.04]Binary Latent Diffusion[PDF]
[arxiv 2023.04]Patch Diffusion: Faster and More Data-Efficient Training of Diffusion Models [PDF]
[arxiv 2023.06]SnapFusion: Text-to-Image Diffusion Model on Mobile Devices within Two Seconds [PDF, Page]
[arxiv 2023.10]LATENT CONSISTENCY MODELS: SYNTHESIZING HIGH-RESOLUTION IMAGES WITH FEW-STEP INFERENCE [PDF,Page]
[arxiv 2024.04]Efficient Denoising using Score Embedding in Score-based Diffusion Models [PDF]
[arxiv 2024.03]DiffusionMTL: Learning Multi-Task Denoising Diffusion Model from Partially Annotated Data [PDF,Page]