2018[SIG]DeepMimic: Example-Guided Deep Reinforcement Learning of Physics-Based Character Skills 本文是Xuebin Peng组在2018年比较出圈的工作,也是Physics-based Animation比较重要的工作,里面的许多设定在后续的AMP、ASE等文章中都有沿用。总体来说这篇工作比较有GCRL的感觉,用一个比较复杂的奖励让角色学一个比较难...
然后训练智能体通过模仿参考运动来生成更自然的动作。模仿运动数据的模拟在计算机动画中有很长的历史,近期也出现了一些使用深度强化学习的案例,如《DeepLoco: Dynamic Locomotion Skills Using Hierarchical Deep Reinforcement Learning》。尽管结果看起来更加自然,但是离生动再现大量运动还有很远的距离。 本研究中,我们的策略...
CNTK, or Theano. It acts as high level wrapper and is very easy to use even for people new to Machine Learning. Due to these reasons,Kerasis getting a lot of traction these
The performance measurements in this document were conducted at the time of publication and may not reflect the performance achieved from NVIDIA’s latest software release. For the most up-to-date performance measurements, go toNVIDIA Data Center Deep Learning Product Performance. ...
在这5堂课中,学生将可以学习到深度学习的基础,学会构建神经网络,并用在包括吴恩达本人在内的多位业界顶尖专家指导下创建自己的机器学习项目。Deep Learning Specialization对卷积神经网络 (CNN)、递归神经网络 (RNN)、长短期记忆 (LSTM) 等深度学习常用的网络结构、工具和知识都有涉及。
The latest NVIDIA Deep Learning software libraries, such as cuDNN, NCCL, cuBLAS, etc. which have all been through a rigorous monthly quality assurance process to ensure that they provide the best possible performance Monthly release notesfor each of the NVIDIA optimized containers ...
读论文 DeepMimic: Example-Guided Deep Reinforcement Learning of Physics-Based Character Skills 笔记,程序员大本营,技术文章内容聚合第一站。
for example:固定搭配,意为“以……为例”。 2. get into debt:固定搭配,意为“负债”。 3. see sb. doing sth.:固定搭配,意为“看见某人正在做某事”。 4. guarantee to do sth.:固定搭配,意为“保证做某事”。 5. get sth. done:固定搭配,意为“使某事被做”。 6. be upset about sth.:固定...
具体显示第一层特征的可视化函数display_network.m的详细注释可见:Deep Learning八:Stacked Autocoders and Implement deep networks for digit classification_Exercise(斯坦福大学深度学习教程UFLDL) 运行结果为: 训练集为: 特征可视化结果为: 可以看出,稀疏自动编码器学习到的特征实际上是图像的边缘 ...
The ability to train deep learning networks with lower precision was introduced in the Pascal architecture and first supported in CUDA 8 in the NVIDIA Deep Learning SDK. For information about: How to train using mixed precision, see theMixed Precision Training paper and Training With Mixed Precisio...