Treffer 21 - 40 von 3.550

21

TensorFlow: learning functions at scale
Abadi, Martín
Proceedings of the 21st ACM SIGPLAN International Conference on Functional Programming. :1-1

Konferenz
22

Speed benchmarking of genetic programming frameworks
Baeta, Francisco ; Correia, João ; Martins, Tiago ; et al.
Proceedings of the Genetic and Evolutionary Computation Conference. :768-775

Konferenz
23

TF-Coder: Program Synthesis for Tensor Manipulations
Shi, Kensen ; Bieber, David ; Singh, Rishabh
ACM Transactions on Programming Languages and Systems (TOPLAS). 44(2):1-36

Fachzeitschrift
24

The Geometry of Computation-Graph Abstraction
Muroya, Koko ; Cheung, Steven W. T. ; Ghica, Dan R.
Proceedings of the 33rd Annual ACM/IEEE Symposium on Logic in Computer Science. :749-758

Konferenz
25

A computational model for TensorFlow: an introduction
Abadi, Martín ; Isard, Michael ; Murray, Derek G.
Proceedings of the 1st ACM SIGPLAN International Workshop on Machine Learning and Programming Languages. :1-7

Konferenz
26

TensorFlow Basics
Bhalley, Rahul ; Bhalley, Rahul
Deep Learning with Swift for TensorFlow : Differentiable Programming with Swift. :143-169

E-Book
27

Differentiable Programming
Bhalley, Rahul ; Bhalley, Rahul
Deep Learning with Swift for TensorFlow : Differentiable Programming with Swift. :67-141

E-Book
28

Computer Vision
Bhalley, Rahul ; Bhalley, Rahul
Deep Learning with Swift for TensorFlow : Differentiable Programming with Swift. :231-267

E-Book
29

Machine Learning Basics
Bhalley, Rahul ; Bhalley, Rahul
Deep Learning with Swift for TensorFlow : Differentiable Programming with Swift. :1-35

E-Book
30

Neural Networks
Bhalley, Rahul ; Bhalley, Rahul
Deep Learning with Swift for TensorFlow : Differentiable Programming with Swift. :171-230

E-Book
31

Essential Math
Bhalley, Rahul ; Bhalley, Rahul
Deep Learning with Swift for TensorFlow : Differentiable Programming with Swift. :37-65

E-Book
32

Overview of Programming
Suri, Abhinav ; Suri, Abhinav
Practical AI for Healthcare Professionals : Machine Learning with Numpy, Scikit-learn, and TensorFlow. :41-78

E-Book
33

Python Programming in Jupyter Notebook
Silaparasetty, Nikita ; Silaparasetty, Nikita
Machine Learning Concepts with Python and the Jupyter Notebook Environment : Using Tensorflow 2.0. :119-145

E-Book
34

Meta-programming for cross-domain tensor optimizations
Susungi, Adilla ; Rink, Norman A. ; Cohen, Albert ; et al.
Proceedings of the 17th ACM SIGPLAN International Conference on Generative Programming: Concepts and Experiences. :79-92

Konferenz
35

Machine learning in SQL by translation to TensorFlow
Makrynioti, Nantia ; Ley-Wild, Ruy ; Vassalos, Vasilis
Proceedings of the Fifth Workshop on Data Management for End-To-End Machine Learning. :1-11

Konferenz
36

Deep Learning model based on CNN using Keras and TensorFlow to determine real time melting point of chemical substances
Anurag Shrivastava
ELCVIA Electronic Letters on Computer Vision and Image Analysis, Vol 23, Iss 1 (2024)

TK7885-7895 Computer engineering. Co... Melting Point of Chemica... TensorFlow Single Board Computer Electronic computers. Co...
Fachzeitschrift
37

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38

An Optimal Design Method of Conv2d Operator for TensorFlow Based on FPGA Accelerator
Li, Rengang ; Kan, Hongwei ; Su, Dongdong ; et al.
Proceedings of the 4th International Conference on Computer Science and Application Engineering. :1-6

Konferenz
39

Polyhedral Optimization of TensorFlow Computation Graphs
Pradelle, Benoît ; Meister, Benoît ; Baskaran, Muthu ; et al.
Programming and Performance Visualization Tools : International Workshops, ESPT 2017 and VPA 2017, Denver, CO, USA, November 12 and 17, 2017, and ESPT 2018 and VPA 2018, Dallas, TX, USA, November 16 and 11, 2018, Revised Selected Papers. 11027:74-89

E-Book
40

Efficient Graph Deep Learning in TensorFlow with tf_geometric
Hu, Jun ; Qian, Shengsheng ; Fang, Quan ; et al.
Proceedings of the 29th ACM International Conference on Multimedia. :3775-3778

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