You can use MATLAB® Coder™ with Deep Learning Toolbox to generate C++ code from a trained deep learning network. You can then deploy the generated code to an embedded platform that uses an Intel® or ARM® processor. You can also generate generic C or C++ code from a trained deep...
We then show how the game can be extended to general acyclic neural networks with differentiable convex gates, establishing a bijection between the Nash equilibria and critical (or KKT) points of the deep learning problem. Based on these connections we investigate alternative learning methods, and ...
These dynamically typed deep learning frameworks treat neural networks as differentiable expressions that contain many trainable variable, and perform automatic differentiation on those expressions when training them. Until 2019, none of the learning frameworks in statically typed languages provided the ...
How to Do Things with Deep Learning CodeHua, MinhRaley, RitaDHQ: Digital Humanities Quarterly
Code:论文中提到的tensorflow的代码,需要安装tensorflow_privacy这个工具包,DP-SGD方法为: from tensorflow_privacy.privacy.optimizers import dp_optimizer optimizer = dp_optimizer.DPGradientDescentGaussianOptimizer( l2_norm_clip=__, noise_multiplier=__, num_microbatches=__, learning_rate=__) Pytorch实现的...
Deep Learning with MATLAB: Transfer Learning in 10 Lines of MATLAB Code Learnhow to use transferlearningin MATLAB to re-traindeeplearningnetworks created by experts for your own data or task.
论文标题：SRPO: A Cross-Domain Implementation of Large-Scale Reinforcement Learning on LLM 论文链接：https://arxiv.org/abs/2504.14286 模型开源地址：https://huggingface.co/Kwaipilot/SRPO-Qwen-32B 这是业界首个同时在数学和代码两个领域复现 DeepSeek-R1-Zero 性能的方法。通过使用与 DeepSeek 相同的...
With GPU Coder™, you can generate optimized code for prediction of a variety of trained deep learning networks from Deep Learning Toolbox™. The generated code implements the deep convolutional neural network (CNN) by using the architecture, the layers, and parameters that you specify in the...
(x, y, output)#The gradient descent step, the error times the gradient times the inputsdel_w += error_term *x#Update the weights here. The learning rate times the#change in weights, divided by the number of records to averageweights += learnrate * del_w /n_records#Printing out the...
前面的博客中有提到过要开源最近写的code,seq2seq-attention,今天正式开源了,欢迎各路大神来fork和star。这是我从5月中旬开始决定用torch框架来写deep learning code以来写的第一个完整的program,在写的过程中走过不少弯路,尤其是在选择demo进行学习的过程中,被HarvardNLP组的seq2seq-attn难以阅读的代码搞得非常崩溃...