Deep Learning深度学习(一)简介 1.what这个技术是什么 官方文档定义 深度学习是指多层神经网络上运用各种机器学习算法解决图像,文本等各种问题的算法集合。 对比同类技术的优缺点,适用场景(to be continue) Deep learning本身算是machine learning的一个分支,简单可以理解为neural network的发展。 二者的相同在于deep lear...
The field of deep learning has witnessed significant progress in recent times, particularly in areas such as computer vision (CV), natural language processing (NLP), and speech. The use of large-scale models trained on vast amounts of data holds immense promise for practical applications, ...
Dr. Elara Nova:问候,尊敬的同事们。今天,我们聚集在这里,讨论OpenAI Five的开创性成就,这是一个AI系统,击败了《Dota 2》世界冠军Team OG。考虑到游戏的复杂性和对AI的挑战,这一成就令人印象深刻。让我们深入探讨这一成就的重要意义。 Prof. Orion Teller:的确,Dr. Nova。从博弈论的角度来看,《Dota 2》是一...
Deep Learning Recommender Systems (DLRSs) need to update models at low latency, thus promptly serving new users and content. Existing DLRSs, however, fail to do so. They train/validate models offline and broadcast entir...
Designing reconfigurable large-scale deep learning systems using stochastic computing Deep Learning, as an important branch of machine learning and neural network, is playing an increasingly important role in a number of fields like computer... R Ao,L Zhe,Y Wang,... - IEEE 被引量: 19发表: ...
Deep Learning for Large-Scale Holographic 3D Particle Localization and Two-Photon Angiography SegmentationEngineering.Physics.Artificial intelligence.Digital inline holography (DIH) is a popular imaging technique, in which an unknown 3D object can be estimated from a single 2D intensity measurement, also ...
Deep learning, a recent artificial intelligence advance with a promising application for big data, has demonstrated potential in the field of single-cell analysis 1 . Deep learning exhibits flexibility in extracting informative features from noisy, high-dimensional, single-cell RNA sequencing (scRNA-...
Beyond Deep Ensembles: A Large-Scale Evaluation of Bayesian Deep Learning under Distribution Shift 群主 nlp算法工程师旨在对贝叶斯深度学习在分布偏移(distribution shift)数据上进行校准预测的能力进行大规模评估。 在这篇论文中,作者们提出了以下几点贡献: 他们系统地评估了一组现代、可扩展的BDL算法在WILDS集合中...
Today, and possibly for a long time to come, the full driving task is too complex an activity to be fully formalized as a sensing-acting robotics system that can be explicitly solved through model-based and learning-based approaches in order to achieve full unconstrained vehicle autonomy. Locali...
Trishul Chilimbi, Partner Research Manager for Microsoft Research, discusses Project Adam, and how deep neural networks have enabled large-scale computer image recognition with astounding accuracy.