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Генеративни модел заснован на скору×Капсулска мрежа×
OblastDuboko učenjeDuboko učenje
PorodicaMachine learningMachine learning
Godina nastanka20192017
TvoracSong, Y. & Ermon, S.Sabour, S., Frosst, N. & Hinton, G. E.
TipScore-based generative model (SDE framework)Deep learning architecture (vector capsules with dynamic routing)
Temeljni izvorSong, Y. & Ermon, S. (2019). Generative Modeling by Estimating Gradients of the Data Distribution. NeurIPS 32, 11895–11907. link ↗Sabour, S., Frosst, N. & Hinton, G. E. (2017). Dynamic Routing Between Capsules. Advances in Neural Information Processing Systems (NeurIPS). link ↗
Drugi naziviSkor Tabanlı Üretici Model (Score-Based / SDE), score-based diffusion, SDE-based generative model, score SDEKapsül Ağı (CapsNet), CapsNet, capsule net, dynamic routing network
Srodne54
SažetakA score-based generative model, introduced by Yang Song and Stefano Ermon in 2019 and generalized to the stochastic differential equation (SDE) framework in 2021, learns the gradient of the data density — the score — rather than predicting noise directly, and uses it to generate new samples. It is the mathematical generalization that unifies diffusion models under a continuous-time formulation.A Capsule Network (CapsNet) is a deep learning architecture introduced by Sara Sabour, Nicholas Frosst and Geoffrey Hinton in 2017 that organises neurons as vectors (capsules) rather than scalar activations, so that spatial hierarchy and pose (orientation) information are encoded directly. It was proposed to overcome the fragility of convolutional networks to changes in viewpoint.
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ScholarGateUporedite metode: Score-Based Generative Model · Capsule Network. Preuzeto 2026-06-15 sa https://scholargate.app/sr/compare