標(biāo)題: Titlebook: Neural Networks and Deep Learning; A Textbook Charu C. Aggarwal Textbook 2023Latest edition Springer Nature Switzerland AG 2023 Neural netw [打印本頁] 作者: Johnson 時間: 2025-3-21 18:50
書目名稱Neural Networks and Deep Learning影響因子(影響力)
書目名稱Neural Networks and Deep Learning影響因子(影響力)學(xué)科排名
書目名稱Neural Networks and Deep Learning網(wǎng)絡(luò)公開度
書目名稱Neural Networks and Deep Learning網(wǎng)絡(luò)公開度學(xué)科排名
書目名稱Neural Networks and Deep Learning被引頻次
書目名稱Neural Networks and Deep Learning被引頻次學(xué)科排名
書目名稱Neural Networks and Deep Learning年度引用
書目名稱Neural Networks and Deep Learning年度引用學(xué)科排名
書目名稱Neural Networks and Deep Learning讀者反饋
書目名稱Neural Networks and Deep Learning讀者反饋學(xué)科排名
作者: FUME 時間: 2025-3-21 23:29
Restricted Boltzmann Machines, mapping networks where a set of inputs is mapped to a set of outputs. On the other hand, RBMs are networks in which the probabilistic states of a network are learned for a set of inputs, which is useful for . modeling.作者: jabber 時間: 2025-3-22 02:34 作者: 異常 時間: 2025-3-22 05:37 作者: 開頭 時間: 2025-3-22 12:06
http://image.papertrans.cn/n/image/663703.jpg作者: 對手 時間: 2025-3-22 16:37 作者: Grating 時間: 2025-3-22 17:27
The Backpropagation Algorithm,This chapter will introduce the backpropagation algorithm, which is the key to learning in multilayer neural networks. In the early years, methods for training multilayer networks were not known, primarily because of the unfamiliarity of the computer science community with ideas that were used quite frequently in control theory [., .].作者: 頂點 時間: 2025-3-22 21:57 作者: 幻影 時間: 2025-3-23 03:17 作者: 推遲 時間: 2025-3-23 09:13
Radial Basis Function Networks,Radial basis function (RBF) networks represent a fundamentally different architecture from what we have seen in ?the previous chapters. All the previous chapters use a feed-forward network in which the inputs are transmitted forward from layer to layer in a similar fashion in order to create the final outputs.作者: outrage 時間: 2025-3-23 10:19
Recurrent Neural Networks,All the neural architectures discussed in earlier chapters are inherently designed for multidimensional data in which there is no inherent ordering among attributes and the number of dimensions (input data items) are fixed.作者: committed 時間: 2025-3-23 15:43 作者: arrhythmic 時間: 2025-3-23 21:48
Graph Neural Networks,Graphs are used in a wide variety of application-centric settings, such as the Web, social networks, communication networks, and chemical compounds. Graphs can be either . or undirected.作者: Badger 時間: 2025-3-24 00:56
Deep Reinforcement Learning,Human beings do not learn from a concrete notion of training data. Learning in humans is a continuous experience-driven process in which decisions are made, and the reward/punishment received from the . are used to guide the learning process for future decisions. In other words, learning in intelligent beings is by reward-guided ..作者: 減震 時間: 2025-3-24 02:40 作者: 蟄伏 時間: 2025-3-24 06:35 作者: Sleep-Paralysis 時間: 2025-3-24 11:03 作者: 開始從未 時間: 2025-3-24 15:46 作者: exophthalmos 時間: 2025-3-24 21:21 作者: infinite 時間: 2025-3-25 00:32
Charu Aggarwald in the study of elastic structures not seen in other texts currently on the market. This work offers a clear and carefully prepared exposition of variational techniques as they are applied to solid mechanics. Unlike other books in this field,?Dym and Shames treat all the necessary theory needed fo作者: 議程 時間: 2025-3-25 04:53
Charu Aggarwalrred during the material technological processing into a product on the deformation behavior and dissipative properties thin-walled glass-plastic tubular elements subjected to repeated-static internal hydrostatic pressure are discussed. It is stated that under the conditions of repeated-static inter作者: Estimable 時間: 2025-3-25 09:47
Charu Aggarwal no coding experience.Maximizes students’ insight into conceThe lessons in this fundamental text equip students with the theory of Computer Assisted Design (CAD), Computer Assisted Engineering (CAE), the essentials of Rapid Prototyping, as well as practical?skills needed to apply this understanding 作者: Anterior 時間: 2025-3-25 12:24 作者: 管理員 時間: 2025-3-25 19:23
Charu Aggarwalalysis.Introduces the theory and application of CAD, CAE, anThis updated, second edition provides readers with an expanded treatment of the FEM as well as new information on recent trends in rapid prototyping technology. The new edition features more descriptions, exercises, and questions within eac作者: Macronutrients 時間: 2025-3-25 23:36 作者: Merited 時間: 2025-3-26 00:08
Charu Aggarwalalysis.Introduces the theory and application of CAD, CAE, anThis updated, second edition provides readers with an expanded treatment of the FEM as well as new information on recent trends in rapid prototyping technology. The new edition features more descriptions, exercises, and questions within eac作者: impaction 時間: 2025-3-26 05:35 作者: Hyperlipidemia 時間: 2025-3-26 09:12 作者: trigger 時間: 2025-3-26 14:58
Charu Aggarwalalysis.Introduces the theory and application of CAD, CAE, anThis updated, second edition provides readers with an expanded treatment of the FEM as well as new information on recent trends in rapid prototyping technology. The new edition features more descriptions, exercises, and questions within eac作者: 可用 時間: 2025-3-26 20:04
alysis.Introduces the theory and application of CAD, CAE, anThis updated, second edition provides readers with an expanded treatment of the FEM as well as new information on recent trends in rapid prototyping technology. The new edition features more descriptions, exercises, and questions within eac作者: Nomadic 時間: 2025-3-27 00:04
An Introduction to Neural Networks,system contains cells, which are referred to as neurons. The neurons are connected to one another with the use of . and ., and the connecting regions between axons and dendrites are referred to as .. These connections are illustrated in Figure 1.1(a). The strengths of synaptic connections often chan作者: –DOX 時間: 2025-3-27 04:11 作者: COKE 時間: 2025-3-27 07:45
Restricted Boltzmann Machines, mapping networks where a set of inputs is mapped to a set of outputs. On the other hand, RBMs are networks in which the probabilistic states of a network are learned for a set of inputs, which is useful for . modeling.作者: acrobat 時間: 2025-3-27 13:14
Charu Aggarwals (one- and two-dimensional) as developed from the three-dimensional theory of elasticity; and second, to introduce the student to the strength and utility of variational principles and methods, including brief978-1-4899-9248-2978-1-4614-6034-3作者: heterodox 時間: 2025-3-27 14:27
ning models can be understood as special cases of neural networks. Chapter 3 explores the connections between traditional machine learning and neural networks. Support vector machines, linear/logistic regressio978-3-031-29644-4978-3-031-29642-0作者: 圖表證明 時間: 2025-3-27 20:02
Textbook 2023Latest editions:.?The backpropagation algorithm is discussed in Chapter 2..Many traditional machine learning models can be understood as special cases of neural networks. Chapter 3 explores the connections between traditional machine learning and neural networks. Support vector machines, linear/logistic regressio作者: installment 時間: 2025-3-28 01:09
Charu Aggarwald Modeling and Applications: Rapid Prototyping, CAD and CAE Theory is ideal for university students in various engineering disciplines as well as design engineers involved in product design, analysis, and validation.978-3-319-35511-5978-3-319-21822-9作者: 附錄 時間: 2025-3-28 03:43 作者: 招惹 時間: 2025-3-28 07:04
Charu Aggarwaldesign engineers involved in product design, analysis, and validation. It equips them with an understanding of the theoryand essentials and also with?practical?skills needed to apply this understanding in real world design and manufacturing settings.?.978-3-030-09031-9978-3-319-74594-7作者: glomeruli 時間: 2025-3-28 12:08
Charu Aggarwaldesign engineers involved in product design, analysis, and validation. It equips them with an understanding of the theoryand essentials and also with?practical?skills needed to apply this understanding in real world design and manufacturing settings.?.978-3-030-09031-9978-3-319-74594-7作者: Patrimony 時間: 2025-3-28 15:16 作者: osteoclasts 時間: 2025-3-28 19:34 作者: 彎腰 時間: 2025-3-29 02:10 作者: SPECT 時間: 2025-3-29 06:14 作者: regale 時間: 2025-3-29 08:04 作者: 轉(zhuǎn)折點 時間: 2025-3-29 12:54 作者: 雪崩 時間: 2025-3-29 15:43 作者: exacerbate 時間: 2025-3-29 19:52
Charu Aggarwalauthors’ objective is two-fold: first, to introduce the student to the theory of structures (one- and two-dimensional) as developed from the three-dimensional theory of elasticity; and second, to introduce the student to the strength and utility of variational principles and methods, including brief作者: legitimate 時間: 2025-3-30 03:49 作者: Herd-Immunity 時間: 2025-3-30 07:32
Charu Aggarwalhe value of energy dissipation coefficient ψ for glass-plastic pipes with φ?=?6–8° turns out to be 20% (and more) greater than the value of energy dissipation coefficient ψ defined for glass-plastic pipes with φ?=?0°. The shares of each from the main and accompanying the main deformations into the t作者: 墊子 時間: 2025-3-30 10:34 作者: 溫室 時間: 2025-3-30 15:35 作者: 難解 時間: 2025-3-30 17:07
Includes exercises and examples.Discusses both traditional n.This book covers both classical and modern models in deep learning. The primary focus is on the theory and algorithms of deep learning. The theory and algorithms of neural networks are particularly important for understanding important con作者: 討厭 時間: 2025-3-30 21:16
10樓作者: bizarre 時間: 2025-3-31 04:40
10樓作者: 虛假 時間: 2025-3-31 06:51
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