[PDF] Top 20 Deep Latent Generative Models for Energy Disaggregation
Has 10000 "Deep Latent Generative Models for Energy Disaggregation" found on our website. Below are the top 20 most common "Deep Latent Generative Models for Energy Disaggregation".
Deep Latent Generative Models for Energy Disaggregation
... learning models for smart energy con- sumption is an important research problem, having a tremen- dous impact on ...smart energy consumption is being able to accu- rately disaggregate energy ... See full document
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Multi-Label Latent Spaces with Semi-Supervised Deep Generative Models
... [44,58,59,63,73]. Deep Generative Models (DGMs) are among the state-of-the-art for unsupervised and semi-supervised learning [44, 45,58, 59] capable of attaining 98% using 100 labels, close to the ... See full document
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ClusterGAN: Latent Space Clustering in Generative Adversarial Networks
... by deep generative approaches, the two most prominent be- ing Variational Autoencoder (VAE) (Kingma and Welling 2013) and Generative Adversarial Network (GAN) (Good- fellow et ...of generative ... See full document
8
Language as a Latent Variable: Discrete Generative Models for Sentence Compression
... as deep generative mod- ...employs generative models for supervised learning ...a generative model that explicitly extracts syntactic relationships among words and phrases which further ... See full document
10
Probabilistic Typology: Deep Generative Models of Vowel Inventories
... There is a long history in cognitive psychology of mapping stimuli into some psychological space. The distances in this psychological space may be predictive of generalization (Shepard, 1987) or of perception. Due to the ... See full document
11
Deep Recurrent Generative Decoder for Abstractive Text Summarization
... topic models to capture the latent information from source docu- ments or ...their latent characteristics using a hierarchical topic model, and trained a regression model to ex- tract ...the ... See full document
10
NeVAE: A Deep Generative Model for Molecular Graphs
... Deep generative models have been praised for their ability to learn smooth latent representation of images, text, and au- dio, which can then be used to generate new, plausible ...current ... See full document
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A Stochastic Decoder for Neural Machine Translation
... current models of machine translation do not account for this variation, instead treating the prob- lem as a deterministic ...a deep generative model of machine translation which incorporates a chain ... See full document
10
An Extreme Learning Machine Approach to Effective Energy Disaggregation
... Although deep neural architectures can achieve excellent results, those models have two main weaknesses: (1) deep models considers the multilayer architectures as a whole that is fine-tuned by ... See full document
18
Modelling urban networks using Variational Autoencoders
... of deep learning models that lack com- prehensive human ...the deep learning literature (Ribeiro et ...how latent space representations of urban networks relate to established network met- ... See full document
11
auDeep: Unsupervised Learning of Representations from Audio with Deep Recurrent Neural Networks
... for deep unsupervised representation learning from audio with competitive performance on various audio classification ...general-purpose deep audio toolkit, by integrating other deep representation ... See full document
5
Kernels for Vector-Valued Functions: a Review
... In sensor networks, for example, missing signals from certain sensors may be predicted by exploiting their cor- relation with observed signals acquired from other sensors [72]. In geostatistics, predicting the ... See full document
38
Energy feedback enabled by load disaggregation
... with energy feedback (see (Murray et ...in energy consumption incurred by replacing their standard kettle with an ‘eco’ vacuum ...reducing energy, they believed that they had changed their habits ... See full document
7
Energy feedback enabled by load disaggregation
... NILM-facilitated Energy Feedback Using disaggregated information about the when, duration and energy consumption of each appliance use: Time use statistics to quantify, predict and i[r] ... See full document
16
Article Taking the Models back to Music Practice: Evaluating Generative Transcription Models built using Deep Learning
... We emphasise that folk-rnn is not modelling music, but instead a highly reductive abstraction removed from what one perceives as music. We thus limit our interrogation of the model to how well it understands the use of ... See full document
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A Deep Generative Model of Vowel Formant Typology
... a generative proba- bility model of which vowels a language con- ...novel generative probability model and report results based on a corpus of 233 lan- ... See full document
10
RETRACTED: Realization of Virtual Human Face Based on Deep Convolutional Generative Adversarial Networks
... Processing generative adversarial networks and used them for LSUN scene recognition challenges, Mnist handwritten numbers, and SVNH data sets ...the deep convolutional generative adversarial ... See full document
12
What Do We Learn from Word Associations? Evaluating Machine Learning Algorithms for the Extraction of Contextual Word Meaning in Natural Language Processing
... Keywords: Machine Learning; Algorithms; Natural Language Processing, Deep Learning, Vector 29.. Space Models, Semantic Similarity, Distributional Semantics, Latent Semantic Analys[r] ... See full document
21
Sentiment Retrieval using Generative Models
... retrieval models in the framework of generative language modeling, not only assuming query terms expressing a certain topic, but also assuming that the polarity of sen- timent interest is specified by the ... See full document
10
Doc2hash: Learning Discrete Latent variables for Documents Retrieval
... We follow the same experimental protocol and setting used in (Shen et al., 2018; Chaidaroon and Fang, 2017). Three standard public datasets of documents are chosen for training and evaluation: Reuters (Lewis, 1997), TMC ... See full document
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