Neural NILM: Deep Neural Networks Applied to Energy Disaggregation
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[1] Gerhard P. Hancke,et al. Using neural networks for non-intrusive monitoring of industrial electrical loads , 1994, Conference Proceedings. 10th Anniversary. IMTC/94. Advanced Technologies in I & M. 1994 IEEE Instrumentation and Measurement Technolgy Conference (Cat. No.94CH3424-9).
[2] S. R. Shaw,et al. Transient event detection in spectral envelope estimates for nonintrusive load monitoring , 1995 .
[3] A. Schoofs,et al. Real-Time Recognition and Profiling of Appliances through a Single Electricity Sensor , 2010, 2010 7th Annual IEEE Communications Society Conference on Sensor, Mesh and Ad Hoc Communications and Networks (SECON).
[4] Hong-Tzer Yang,et al. Design a Neural Network for Features Selection in Non-intrusive Monitoring of Industrial Electrical Loads , 2007, 2007 11th International Conference on Computer Supported Cooperative Work in Design.
[5] Geoffrey E. Hinton,et al. ImageNet classification with deep convolutional neural networks , 2012, Commun. ACM.
[6] 森谷 祐一,et al. Advanced Technologies , 2005, Contemporary Endoscopic Spine Surgery.
[7] Ronald J. Williams,et al. Gradient-based learning algorithms for recurrent networks and their computational complexity , 1995 .
[8] Yoshua Bengio,et al. Gradient-based learning applied to document recognition , 1998, Proc. IEEE.
[9] Quoc V. Le,et al. Sequence to Sequence Learning with Neural Networks , 2014, NIPS.
[10] Kunihiko Fukushima,et al. Neocognitron: A self-organizing neural network model for a mechanism of pattern recognition unaffected by shift in position , 1980, Biological Cybernetics.
[11] G. W. Hart,et al. Nonintrusive appliance load monitoring , 1992, Proc. IEEE.
[12] Jack Kelly,et al. The UK-DALE dataset, domestic appliance-level electricity demand and whole-house demand from five UK homes , 2014, Scientific Data.
[13] Haimonti Dutta,et al. NILMTK: an open source toolkit for non-intrusive load monitoring , 2014, e-Energy.
[14] David G. Lowe,et al. Object recognition from local scale-invariant features , 1999, Proceedings of the Seventh IEEE International Conference on Computer Vision.
[15] Yoshua Bengio,et al. End-to-end Continuous Speech Recognition using Attention-based Recurrent NN: First Results , 2014, ArXiv.
[16] Yee Whye Teh,et al. A Fast Learning Algorithm for Deep Belief Nets , 2006, Neural Computation.
[17] Yoshua Bengio,et al. Scaling learning algorithms towards AI , 2007 .
[18] Jürgen Schmidhuber,et al. Long Short-Term Memory , 1997, Neural Computation.
[19] Alex Graves,et al. Supervised Sequence Labelling with Recurrent Neural Networks , 2012, Studies in Computational Intelligence.
[20] Geoffrey E. Hinton,et al. Learning internal representations by error propagation , 1986 .
[21] J. Zico Kolter,et al. REDD : A Public Data Set for Energy Disaggregation Research , 2011 .
[22] Navdeep Jaitly,et al. Towards End-To-End Speech Recognition with Recurrent Neural Networks , 2014, ICML.
[23] Robert J. Marks,et al. An Artificial Neural Network for Spatio-Temporal Bipolar Patterns: Application to Phoneme Classification , 1987, NIPS.
[24] Alex Graves,et al. Generating Sequences With Recurrent Neural Networks , 2013, ArXiv.
[25] Razvan Pascanu,et al. Theano: new features and speed improvements , 2012, ArXiv.
[26] Hsueh-Hsien Chang,et al. Feature Extraction of Non-intrusive Load-Monitoring System Using Genetic Algorithm in Smart Meters , 2011, 2011 IEEE 8th International Conference on e-Business Engineering.
[27] Claude Jauffret,et al. A new approach for event detection and feature extraction for NILM , 2014, 2014 21st IEEE International Conference on Electronics, Circuits and Systems (ICECS).
[28] Yu-Hsiu Lin,et al. A novel feature extraction method for the development of nonintrusive load monitoring system based on BP-ANN , 2010, 2010 International Symposium on Computer, Communication, Control and Automation (3CA).
[29] PAUL J. WERBOS,et al. Generalization of backpropagation with application to a recurrent gas market model , 1988, Neural Networks.
[30] Razvan Pascanu,et al. Theano: A CPU and GPU Math Compiler in Python , 2010, SciPy.
[31] Paul J. Werbos,et al. Backpropagation Through Time: What It Does and How to Do It , 1990, Proc. IEEE.
[32] Yoshua Bengio,et al. Extracting and composing robust features with denoising autoencoders , 2008, ICML '08.
[33] Shane Legg,et al. Human-level control through deep reinforcement learning , 2015, Nature.