Denoising Diffusion Implicit Models
PulseAugur coverage of Denoising Diffusion Implicit Models — every cluster mentioning Denoising Diffusion Implicit Models across labs, papers, and developer communities, ranked by signal.
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Paper Unifies Diffusion Models and Flow Matching via Wasserstein Geometry
This paper explores the underlying geometry of diffusion models and flow matching, revealing that both are governed by the quadratic Wasserstein distance on the space of probability measures. The research posits that di…
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New diffusion inversion techniques improve image reconstruction and seismic analysis · 4 sources tracked
Researchers are developing new methods for diffusion inversion, a process that maps images back into the latent space of diffusion models for reconstruction and editing. One approach, "Posterior Continuation," optimizes…
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Diffusion model theory reveals DDIM's hallucination weakness
A new theoretical analysis examines hallucination phenomena in diffusion models, specifically comparing the Denoising Diffusion Probabilistic Model (DDPM) and the Denoising Diffusion Implicit Model (DDIM). The study pro…
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DDIM Creator Jiaming Song Departs Luma AI
Jiaming Song, a key figure behind the Denoising Diffusion Implicit Models (DDIM) that accelerated image generation, has departed from Luma AI. Song, who joined Luma AI as Chief Scientist in 2023 after a tenure at NVIDIA…
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New Gaussian Mixture Model improves DDIM sampling quality
Researchers have developed a new method to improve the sampling process in Denoising Diffusion Implicit Models (DDIM). Their approach utilizes a Gaussian Mixture Model (GMM) as the reverse transition operator, which mat…
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ExpoCM framework reconstructs HDR images faster
Researchers have developed ExpoCM, a new framework for reconstructing high dynamic range (HDR) images from single low dynamic range inputs. This method addresses the challenges of detail loss in over-exposed and noise i…
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Diffusion Models for Video Generation
Researchers are exploring advanced diffusion models for video generation, addressing challenges like temporal consistency and data scarcity. New methods focus on improving parameterization, such as the v-prediction tech…