Learning from What We Know: How to Perform Vulnerability Prediction
using Noisy Historical Data

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Learning from What We Know: How to Perform Vulnerability Prediction using Noisy Historical Data

21 December 2020

Renzo Degiovanni

Matthieu Jimenez

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Papers citing "Learning from What We Know: How to Perform Vulnerability Prediction using Noisy Historical Data"

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Title
Devign: Effective Vulnerability Identification by Learning Comprehensive Program Semantics via Graph Neural Networks Yaqin Zhou Shangqing Liu J. Siow Xiaoning Du Yang Liu GNN 68 778 0 08 Sep 2019
Massive Exploration of Neural Machine Translation Architectures D. Britz Anna Goldie Minh-Thang Luong Quoc V. Le 63 519 0 11 Mar 2017
Deep API Learning Xiaodong Gu Hongyu Zhang Dongmei Zhang Sunghun Kim AIMat HAI 79 558 0 27 May 2016
Sequence to Sequence Learning with Neural Networks Ilya Sutskever Oriol Vinyals Quoc V. Le AIMat 440 20,584 0 10 Sep 2014
Neural Machine Translation by Jointly Learning to Align and Translate Dzmitry Bahdanau Kyunghyun Cho Yoshua Bengio AIMat 575 27,325 0 01 Sep 2014