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Formal description of ML models for unambiguous implementation
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Formal description of ML models for unambiguous implementation

Adrien Gauffriau
Iryna De Albuquerque Silva
C. Pagetti
ArXiv (abs)PDFHTML

Papers citing "Formal description of ML models for unambiguous implementation"

3 / 3 papers shown
Title
Compiling ONNX Neural Network Models Using MLIR
Compiling ONNX Neural Network Models Using MLIR
Tian Jin
Gheorghe-Teodor Bercea
Tung D. Le
Tong Chen
Gong Su
...
Yasushi Negishi
Anh Leu
K. O'Brien
K. Kawachiya
A. Eichenberger
28
61
0
19 Aug 2020
Reluplex: An Efficient SMT Solver for Verifying Deep Neural Networks
Reluplex: An Efficient SMT Solver for Verifying Deep Neural Networks
Guy Katz
Clark W. Barrett
D. Dill
Kyle D. Julian
Mykel Kochenderfer
AAML
318
1,873
0
03 Feb 2017
Caffe: Convolutional Architecture for Fast Feature Embedding
Caffe: Convolutional Architecture for Fast Feature Embedding
Yangqing Jia
Evan Shelhamer
Jeff Donahue
Sergey Karayev
Jonathan Long
Ross B. Girshick
S. Guadarrama
Trevor Darrell
VLMBDL3DV
280
14,713
0
20 Jun 2014

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