which can be propagated through time to infer knowledge about reality based on previous data. We can generalise the sparse learning information over real world.
Accurate state of charge (SOC) estimation of lithium-ion (Li-ion) batteries is crucial in prolonging cell lifespan and ensuring its safe operation for electric vehicle applications. In this article, we propose the deep learning-based transformer model tr
Deep Reinforcement Learning, Spring 2017, by UC Berkeley:http://rll.berkeley.edu/deeprlcours... Reinforcement Learning, 2015, by UCL (David Siver):http://www0.cs.ucl.ac.uk/staff/d.si... https://github.com/yandexdataschool... Lecture notes by Andrew Ng:http://cs229.stanford.edu/note...
Fastai: a layered API for deep learning. Information 11, 108 (2020). Google Scholar Ronneberger, O., Fischer, P. & Brox, T. in Medical Image Computing and Computer-Assisted Intervention – MICCAI 2015. MICCAI 2015 (eds Navab, N. et al.) (Lecture Notes in Computer Science, Vol. ...
* [《MIT Machine Learning for Big Data and Text Processing Class Notes - Day 1》](http://blog.adnanmasood.com/2015/06/08/mit-machine-learning-for-big-data-and-text-processing-class-notes-day-1/) 介绍: [Day 1](http://blog.adnanmasood.com/2015/06/08/mit-machine-learning-for-big-dat...
Backpropagation and Introduction to neural networks [notes] [video] Neural Networks Part 1 [notes] [Extra] Backpropagation MIT lecture [video]05Neural network part-II -- setting up the data and the model [notes] [video] Neural network part-III -- learning the network [notes] [video]...
In recent years, deep learning has been widely used in diverse fields of research, such as speech recognition, image classification, autonomous driving and natural language processing. Deep learning has showcased dramatically improved performance in complex classification and regression problems, where the...
The Principles of Deep Learning Theory(2021)Daniel A. Roberts and Sho Yaida(mit),Beginning from a first-principles component-level picture of networks,本书解释了如何通过求解层到层迭代方程和非线性学习动力学来确定训练网络输出的准确描述。一个主要的结果是网络的预测是由近高斯分布描述的,网络的深度与宽...
《MIT Machine Learning for Big Data and Text Processing Class Notes - Day 1》 介绍:Day 1、Day 2、Day 3、Day 4、Day 5. 《Getting “deep” about “deep learning”》 介绍:深度学习之“深”——DNN的隐喻分析. 《Mixture Density Networks》 ...
The HSIC Bottleneck: Deep Learning without Back-Propagation: Another experiemnt using alternative methods Codebase (HSIC trainning with PyTorch) HSIC-bottleneck Some supplementary materials: Lecture notes for information theory: Related notes: Lec. 1, 4 Information theory and machine learning: Related ...