Results 61 to 70 of about 8,073,665 (296)
Decentralized Diffusion Models
2025 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)Large-scale AI model training divides work across thousands of GPUs, then synchronizes gradients across them at each step. This incurs a significant network burden that only centralized, monolithic clusters can support, driving up infrastructure costs and straining power systems.
David McAllister +3 more
openaire +2 more sources
FEBS Letters, EarlyView.We present robust protocols for the preparation of supported lipid bilayers (SLBs) incorporating either Salmonella smooth LPS or outer membrane vesicles (OMVs). We use a combination of quartz crystal microbalance with dissipation (QCM‐D) and fluorescence microscopy to both characterize the SLBs of various compositions and to probe their interactions ...
Hudson P. Pace +6 more
wiley +1 more source
Diffusion Soup: Model Merging for Text-to-Image Diffusion Models
We present Diffusion Soup, a compartmentalization method for Text-to-Image Generation that averages the weights of diffusion models trained on sharded data. By construction, our approach enables training-free continual learning and unlearning with no additional memory or inference costs, since models corresponding to data shards can be added or removed
Benjamin Biggs +8 more
openaire +3 more sources
A Short Note on Non-isothermal Diffusion Models
Acta Polytechnica, 2003 Asymptotic behaviour of the DIAL and DRAL non-isothermal models, derived previously for the diffusion of water vapour through a porous building structure, is studied under the assumption that the initially non-isothermal structure becomes purely ...
T. Ficker
doaj
Modelling stem cell differentiation related processes—A practical overview for biologists
FEBS Letters, EarlyView.Stem cell differentiation is complex and difficult to control experimentally. This review introduces suitable computational modelling approaches that can support stem cell research, from mechanistic ODE and abstract models to multiscale and deep learning methods.
Ricco Zeegelaar +4 more
wiley +1 more source
Investigating transcription factor dynamics in health and disease using FRAP
FEBS Letters, EarlyView.FRAP analysis of GFP‐tagged transcription factors reveals how molecular mobility and target engagement change in response to drug treatment. By combining live‐cell imaging, quantitative model fitting, and statistical analysis, this approach uncovers transcription factor dynamics linked to disease mechanisms, providing a powerful framework for ...
Kannan Govindaraj +3 more
wiley +1 more source
Molecular diffusion under confinement [PDF]
, 2005 With reference to molecular transport in manifold media of porous structure, a survey is given on the ample spectrum of diffusion phenomena under confinement.
Kärger, Jörg
core +1 more source
Latent diffusion models for survival analysis [PDF]
, 2010 We consider Bayesian hierarchical models for survival analysis, where the survival times are modeled through an underlying diffusion process which determines the hazard rate.
Laura M. Sangalli +5 more
core +1 more source
Conserved binding mode but diverse interfaces of MreC‐PBP2 interactions
FEBS Letters, EarlyView.The crystal structure of abMreC reveals a conserved two β‐barrel architecture and provides structural insights into its role within the bacterial elongasome. The abMreC–abPBP2 complex model identifies the molecular basis of MreC‐mediated PBP2 recognition, contributing to the regulation of peptidoglycan synthesis.
Hyunseok Jang +4 more
wiley +1 more source
On the Mathematics of Diffusion Models
CoRR, 2023 This paper gives direct derivations of the differential equations and likelihood formulas of diffusion models assuming only knowledge of Gaussian distributions. A VAE analysis derives both forward and backward stochastic differential equations (SDEs) as well as non-variational integral expressions for likelihood formulas.
openaire +2 more sources