Explaining Deep Neural Networks

4 October 2020

Papers citing "Explaining Deep Neural Networks"

10 / 10 papers shown

Title
Simfluence: Modeling the Influence of Individual Training Examples by Simulating Training Runs Kelvin Guu Albert Webson Ellie Pavlick Lucas Dixon Ian Tenney Tolga Bolukbasi TDI 66 33 0 14 Mar 2023
A Review on Explainability in Multimodal Deep Neural Nets Gargi Joshi Rahee Walambe K. Kotecha 23 137 0 17 May 2021
Towards Rigorous Interpretations: a Formalisation of Feature Attribution Darius Afchar Romain Hennequin Vincent Guigue FAtt 31 20 0 26 Apr 2021
A Survey of Information Cascade Analysis: Models, Predictions, and Recent Advances Fan Zhou Xovee Xu Goce Trajcevski Kunpeng Zhang 6 171 0 22 May 2020
e-SNLI: Natural Language Inference with Natural Language Explanations Oana-Maria Camburu Tim Rocktaschel Thomas Lukasiewicz Phil Blunsom LRM 255 620 0 04 Dec 2018
Generating Natural Language Adversarial Examples M. Alzantot Yash Sharma Ahmed Elgohary Bo-Jhang Ho Mani B. Srivastava Kai-Wei Chang AAML 245 914 0 21 Apr 2018
Adversarial Example Generation with Syntactically Controlled Paraphrase Networks Mohit Iyyer John Wieting Kevin Gimpel Luke Zettlemoyer AAML GAN 187 711 0 17 Apr 2018
A Decomposable Attention Model for Natural Language Inference Ankur P. Parikh Oscar Täckström Dipanjan Das Jakob Uszkoreit 201 1,367 0 06 Jun 2016
Benefits of depth in neural networks Matus Telgarsky 133 602 0 14 Feb 2016
Learning Attitudes and Attributes from Multi-Aspect Reviews Julian McAuley J. Leskovec Dan Jurafsky 197 296 0 15 Oct 2012