Lecture notes on Bayesian deep learning . Contribute to sjchoi86/bayes-nn development by creating an account on GitHub.
#deep-learning-lecture-notes 1 repository #deep-learning-training 1 repository #deep-learning-math 1 repository #automated-deep-learning 1 repository #deep-learning-system 1 repository #edge-deep-learning 1 repository #deep-learning-book-notes 1 repository #gui-deep-learning-design 1 repository #nlp...
这个项目是从https://github.com/wangshusen/DeepLearning.git引进的,其包含了几乎全部的深度学习及其相关的内容。
Physics-based Deep Learning(2021)N. Thuerey, P. Holl,etc.github resources深度学习与物理学的联系。比如基于物理的损失函数,可微流体模拟,逆问题的求解,Navier-Stokes方程的前向模拟,Controlling Burgers’ Equation和强化学习的关系等。 Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges(Mich...
课程的作业其实是不公开的,但是2018年的版本Youtube有课程视频,Github上也有课程作业分享,所以我推荐看2018年的Lecture Notes和作业。 An introduction to Statistical Learning 大名鼎鼎的ESL(Elements of Statistical Learning, Data mining)的简化版,又称ISL。 选择这本书主要是因为CS229 18 年的课没有讲Tree相关的...
U-Net, a deep-learning convolutional neural network, is used to downscale coarse meteorological data. Based on 19 models from the Coupled Model Intercomparison Project Phase 6 and the Multi-Source Weather (MSWX) dataset, bias correction and UNet downscal
Notes 1. https://github.com/BVLC/caffe/tree/master/models/bvlcalexnet 2. http://deeplearning.net/tutorial/lenet.html 3. https://github.com/ShaoqingRen/fasterrcnn 4. https://github.com/BVLC/caffe/tree/master/models/bvlcgooglenet 5. ...
Part of the book series:Lecture Notes in Computer Science((LNAI,volume 12500)) 8892Accesses Abstract Exchanging model updates is a widely used method in the modern federated learning system. For a long time, people believed that gradients are safe to share:i.e., the gradients are less informa...
Deep Reinforcement Learning Textbook A collection of comprehensive notes on Deep Reinforcement Learning, based on UC Berkeley's CS 285 (prev. CS 294-112) taught by Professor Sergey Levine. Compile the latex source code into PDF locally. Alternatively, you could download this repo as a zip file...
CS583: Deep Learning Machine learning basics.This part briefly introduces the fundamental ML problems-- regression, classification, dimensionality reduction, and clustering-- and the traditional ML models and numerical algorithms for solving the problems. ...