منابع مشابه
Structured Generative Adversarial Networks
We study the problem of conditional generative modeling based on designated semantics or structures. Existing models that build conditional generators either require massive labeled instances as supervision or are unable to accurately control the semantics of generated samples. We propose structured generative adversarial networks (SGANs) for semi-supervised conditional generative modeling. SGA...
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Probabilistic inference networks capture the stochastic relation between variables by ‘directed’ probabilistic rules corresponding to conditional probabilities, e.g. p(Ak|Ai∧Aj). Associative neural networks – like Boltzmann machine networks – yield a joint distribution, which is a special case of the distribution generated by inference networks. In this paper conventional associative neural net...
متن کاملGenerative Adversarial Structured Networks
We propose a technique that combines generative adversarial networks with probabilistic graphical models to explicitly model dependencies in structured distributions. Generative adversarial structured networks (GASNs) produce samples by passing random inputs through a neural network to construct the potentials of a graphical model; maximum a-posteriori inference in this graphical model then yie...
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A number of Distributed Hash Table(DHT)based publish/subscribe(Pub/Sub) protocols have been proposed to address the issue of scalability in P2P networks. However, their routing state and control message overhead are enormous, the routing depth for notifications is unnecessarily long. We propose SGH, a large-scale partition-based overlay for P2P network, to provide the architecture of Pub/Sub ro...
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Attention networks have proven to be an effective approach for embedding categorical inference within a deep neural network. However, for many tasks we may want to model richer structural dependencies without abandoning end-to-end training. In this work, we experiment with incorporating richer structural distributions, encoded using graphical models, within deep networks. We show that these str...
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ژورنال
عنوان ژورنال: Mathematical and Computer Modelling
سال: 1993
ISSN: 0895-7177
DOI: 10.1016/0895-7177(93)90069-b