Most relevant research papers
This page gathers the most relevant papers dealing about artificial neural networks. You can suggest more papers by contacting us.
HE, Kaiming, GKIOXARI, Georgia, DOLLÁR, Piotr, et al. Mask r-cnn. arXiv preprint arXiv:1703.06870, 2017.
SCHMIDHUBER, Jürgen. Deep learning in neural networks: An overview. Neural networks, 2015, vol. 61, p. 85-117.
MIKOLOV, Tomas, SUTSKEVER, Ilya, CHEN, Kai, et al. Distributed representations of words and phrases and their compositionality. In : Advances in neural information processing systems. 2013. p. 3111-3119.
HINTON, Geoffrey E., SRIVASTAVA, Nitish, KRIZHEVSKY, Alex, et al. Improving neural networks by preventing co-adaptation of feature detectors. arXiv preprint arXiv:1207.0580, 2012.
LECUN, Yann, BOTTOU, Léon, ORR, Genevieve B., et al. Efficient backprop. In : Neural networks: Tricks of the trade. Springer, Berlin, Heidelberg, 1998. p. 9-50.
KOHONEN, Teuvo. Correlation matrix memories. IEEE transactions on computers, 1972, vol. 100, no 4, p. 353-359.
ROSENBLATT, Frank. Principles of neurodynamics. perceptrons and the theory of brain mechanisms. CORNELL AERONAUTICAL LAB INC BUFFALO NY, 1961.
WIDROW, Bernard et HOFF, Marcian E. Adaptive switching circuits. STANFORD UNIV CA STANFORD ELECTRONICS LABS, 1960.
ROSENBLATT, Frank. The perceptron: A probabilistic model for information storage and organization in the brain. Psychological review, 1958, vol. 65, no 6, p. 386.
HEBB, Donald O., et al. The organization of behavior: A neuropsychological theory. 1949.
MCCULLOCH, Warren S. et PITTS, Walter. A logical calculus of the ideas immanent in nervous activity. The bulletin of mathematical biophysics, 1943, vol. 5, no 4, p. 115-133.