From circuit theory. Certain functions can be represented much more efficiently using a multi-stage architecture. A classic example is the parity function. However parity function is not very relevant to functions that we approximate in practice. Besides, gradient descent is horrible at learning funct...
This tutorial is an introduction to deep learning. We will motivate the excitement in this field with a survey of recent state-of-the-art results, and we will outline some of the theory behind representational learning. We will then discuss a small implementation of a convolutional network ...
《Hinton CSC321课程/Deep Learning/Notes on CNN/Python/Theano/CUDA/OpenCV/...》 介绍:介绍个乐于总结和翻译机器学习和计算机视觉类资料的博客,包含的内容:Hinton的CSC321课程的总结;Deep Learning综述;Notes on CNN的总结;python的原理总结;Theano基础知识和练习总结;CUDA原理和编程;OpenCV一些总结. 《Which Algori...
Javier Robledo Moreno, Giuseppe Carleo, and Antoine Georges, Deep Learning the Hohenberg-Kohn Maps of Density Functional Theory, Phys. Rev. Lett., 125:076402, 2020. pdf Jiequn Han(韩劼群), Linfeng Zhang(张林峰), Roberto Car, and Weinan E(鄂维南), Deep Potential: A General Representation of...
[Lecture Notes in Electrical Engineering] Proceedings of 2013 Chinese Intelligent Automation Conference Volume 255 || Sensor Failure Detection and Diagnosis via Polynomial Chaos Theory—Part II: Digital Realization... Z Sun,Z Deng 被引量: 0发表: 2013年 Intelligentized Methodology for Arc Welding Dyna...
Razzak M.I, Naz, S, Zaib A. Deep Learning for Medical Image Processing: Overview, Challenges and the Future. In: Dey, N., Ashour, A., Borra, S. (eds) Classification in BioApps. Lecture Notes in Computational Vision and Biomechanics, 2017;26:323–350. ...
Some Notes on Applied Mathematics for Machine Learning 100 Best GitHub: Deep Learning 介绍:100 Best GitHub: Deep Learning 《UFLDL-斯坦福大学Andrew Ng教授“Deep Learning”教程》 介绍:本教程将阐述无监督特征学习和深度学习的主要观点。通过学习,你也将实现多个功能学习/深度学习算法,能看到它们为你工作,并学...
In recent times, characterized by the rapid advancement of science and technology, the educational system has continuously evolved. Within this modern educational landscape, Science, Technology, Engineering, Arts, and Mathematics (STEAM) education has em
learning,” in Signal and Information Processing, Networking and Computers, vol. 494 of Lecture Notes in Electrical Engineering, pp. 296–306, Springer, Singapore, 2019. [12] J. Schmidhuber, “Deep learning in neural networks: an overview,” Neural Networks, vol. 61, pp. 85–117, 2015. ...
With the recent achievements of deep learning in various applications such as Natural Language Processing (NLP) and image processing, more efforts have been made by the researchers to exploit deep learning methods for improving the performance of RS. However, despite the several research works on ...