Results 11 to 20 of about 486,752 (312)
PharmacoForge: pharmacophore generation with diffusion models [PDF]
Frontiers in BioinformaticsStructure-based drug design (SBDD) is enhanced by machine learning (ML) to improve both virtual screening and de novo design. Despite advances in ML tools for both strategies, screening remains bounded by time and computational cost, while generative ...
Emma L. Flynn +7 more
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Progressive Disease Image Generation with Ordinal-Aware Diffusion Models [PDF]
DiagnosticsBackground/Objectives: Ulcerative Colitis (UC) lacks longitudinal visual data, which limits both disease progression modeling and the effectiveness of computer-aided diagnosis systems.
Meryem Mine Kurt +2 more
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Diffusion Models at the Drug Discovery Frontier: A Review on Generating Small Molecules Versus Therapeutic Peptides [PDF]
BiologyDiffusion models have emerged as a leading framework in generative modeling, poised to transform the traditionally slow and costly process of drug discovery.
Yiquan Wang +6 more
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Exploring the relationship between visual inspection time task and intelligence in young children
Ψυχολογία: το Περιοδικό της Ελληνικής Ψυχολογικής Εταιρείας, 2023 Inspection time task (IT) indexes individual differences in perceptual discrimination speed and it is a reliable predictor of psychometric intelligence However, the reasons underlying the relationship between IT and intelligence are not clear, because ...
Γεώργιος Σπανούδης +1 more
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Generation of Musculoskeletal Ultrasound Images with Diffusion Models
BioMedInformatics, 2023 The recent advances in deep learning have revolutionised computer-aided diagnosis in medical imaging. However, deep learning approaches to unveil their full potential require significant amounts of data, which can be a challenging task in some scientific
Sofoklis Katakis +6 more
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Q-Diffusion: Quantizing Diffusion Models
2023 IEEE/CVF International Conference on Computer Vision (ICCV), 2023 The code is available at https://github.com/Xiuyu-Li/q ...
Xiuyu Li +7 more
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Advances in Neural Information Processing Systems 35, 2022 Diffusion models are recent state-of-the-art methods for image generation and likelihood estimation. In this work, we generalize continuous-time diffusion models to arbitrary Riemannian manifolds and derive a variational framework for likelihood estimation.
Chin-Wei Huang +4 more
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Advances in Neural Information Processing Systems 35, 2022 Generating temporally coherent high fidelity video is an important milestone in generative modeling research. We make progress towards this milestone by proposing a diffusion model for video generation that shows very promising initial results. Our model is a natural extension of the standard image diffusion architecture, and it enables jointly ...
Jonathan Ho +5 more
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CoRR, 2022 Recently, Rissanen et al., (2022) have presented a new type of diffusion process for generative modeling based on heat dissipation, or blurring, as an alternative to isotropic Gaussian diffusion. Here, we show that blurring can equivalently be defined through a Gaussian diffusion process with non-isotropic noise.
Emiel Hoogeboom, Tim Salimans
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A Multi-Scale Deep Back-Projection Backbone for Face Super-Resolution with Diffusion Models
Applied Sciences, 2023 Face verification and recognition are important tasks that have made great progress in recent years. However, recognizing low-resolution faces from small images is still a difficult problem.
Juhao Gao, Ni Tang, Dongxiao Zhang
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