在第一章中,本文将介绍机器学习的可信性(Trustworthiness),包含可解释性(Explainability)、公平性(Fairness)、隐私性(Privacy)和鲁棒性(Robustness)。其中可解释性是最重要的,因为它在一定程度上可以促进后三者。因此,本文重点关注机器学习的可解释性。 在第二章中,本文将详细阐述什么是可解释性(what),为什么需要可解...
These networks were preferred, since one of the main advantages of the biological neural networks -- which motivated the use of neural networks in computing -- is their parallelism, and 3-layer networks provide the largest degree of parallelism. Recently, however, it was empirically shown that,...
There are different kinds of deep neural networks – and each has advantages and disadvantages, depending upon the use. Examples include: Convolutional neural networks (CNNs)contain five types of layers: input, convolution, pooling, fully connected and output. Each layer has a specific purpose, li...
Such networks could use the intermediate layers to build up multiple layers of abstraction, just as we do in Boolean circuits. For instance, if we're doing visual pattern recognition, then the neurons in the first layer might learn to recognize edges, the neurons in the second layer could le...
The first scientific paper on neural networks – the architecture of the AI we have today – was 于1943 年published in 1943。在过去的 80 年里,整整几代人工智能科学家出生、上学、工作,在许多情况下都没有看到我们现在得到的回报就去世了。他们都是传奇,每一个人。. Entire generations of AI ...
GPNPUs can be confused as a hybrid variant of GPUs and NPUs. However, the abbreviation stands for “General Purpose Neural Processing Units“. A GPNPU makes use of a single execution pipeline for unified processor architecture, which can perform vector and matrix operations as well as scalar ...
I fail to see the big difference, when to use one over the other, and why it is claimed in the video that triplet loss allows to learn a ranking, whereas contrastive loss only allows for similarity. Would love a clarification on that neural-networks loss-functions triplet-loss siamese Share...
Artificial intelligence, machine learning and neural networks are terms that are increasingly being used in daily life. Face recognition, object detection, and person classification and segmentation are common tasks for machine learning algorithms which are now in widespread use. Underlying all these proc...
We should now have a good understand about why we use GPUs for neural network programming. For the first part of this series, we will be using a CPU. We are ready now to start working with torch.Tensors and building our first neural networks. I'll see you in the next one!quiz ...
“I don’t know if Waymo and Tesla have images of traffic lights on fire in the datasets they use to train their neural networks, but I’m willing to bet … if they have any, they’ll only have a very few.”It’s one thing for a corner case to be something that’s insignificant...