This book covers both classical and modern models in deep learning. The primary focus is on the theory and algorithms of deep learning. The theory and algorithms of neural networks are particularly important for understanding important concepts, so that one can understand the important design concepts...
Artificial Neural Networks and Machine Learning – ICANN 2016, Part II, Lecture Notes in Computer Science, Springer-Verlag, 9887:63-71, 2016 [preprint,bibtex] PJ Kindermans, KT Schütt, M Alber, KR Müller, D Erhan, B Kim, S Dähne.Learning how to explain neural networks: PatternNet and...
出版者:Springer作者:Charu C. Aggarwal出品人:页数:512译者:出版时间:2018-9-13价格:USD 69.99装帧:ebookisbn号码:9783319944623丛书系列:图书标签: Neural Networks and Deep Learning 2024 pdf epub mobi 电子书 图书描述 This book covers both classical and modern models in deep learning. The primary focus ...
摘要: This chapter contains sections titled: Artificial Neural Networks, Neural Network Learning Algorithms, What a Perceptron Can and Cannot Do, Connectionist Models in Cognitive Science, Neural Networks as a Paradigm for Parallel Processing, Hierarchical Representations in Multiple Layers, Deep Learning...
Learning hierarchical features for scene labeling. IEEE Trans. Pattern Anal. Mach. Intell. 35, 1915–1929 (2013). PubMed Google Scholar Hopfield, J. J. Neural networks and physical systems with emergent collective computational abilities. Proc. Natl Acad. Sci. USA 79, 2554–2558 (1982). ...
et al. ImageNet-trained CNNs are biased towards texture; increasing shape bias improves accuracy and robustness. In Proc. 7th International Conference on Learning Representations (OpenReview.net, 2019). Kansky, K. et al. Schema networks: zero-shot transfer with a generative causal model of ...
Adversarial Learning, Transfer Learning, and Deep Learning; Signal, Image, and Video Processing; Modeling, Analysis, and Implementation of Neural Networks; Control Systems, Robotics, and Autonomous Driving; Fault Diagnosis and Intelligent Industry & Bio-signal, Bioinformatics, and Biomedical Engineering. ...
理解训练深层前馈神经网络的难度(Undetanding the difficulty of training deep feedforward neural networks ) 译者按:大神bengio 的经典论文之一,不多说 作者:Xavier Glorot Yoshua Bengio 加拿大魁北克 蒙特利尔大学 摘要:在2006年以前,似乎深度多层的神经网络没有被成功训练过。自那以后少数几种算法显示成功地训练了...
Recently, neural networks empowered with deep learning algorithms have shown the capability of playing games2,3, providing accurate translation of sentences4, and passing visual Turing tests5. These achievements were all demonstrated via software implementations in high-performance digital computers with ...