ResearchTrend.AI
  • Papers
  • Communities
  • Events
  • Blog
  • Pricing
Papers
Communities
Social Events
Terms and Conditions
Pricing
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2025 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 1611.02639
  4. Cited By
Gradients of Counterfactuals

Gradients of Counterfactuals

8 November 2016
Mukund Sundararajan
Ankur Taly
Qiqi Yan
    FAtt
ArXivPDFHTML

Papers citing "Gradients of Counterfactuals"

18 / 18 papers shown
Title
Unlearning-based Neural Interpretations
Unlearning-based Neural Interpretations
Ching Lam Choi
Alexandre Duplessis
Serge Belongie
FAtt
217
0
0
10 Oct 2024
Model-Agnostic Interpretability of Machine Learning
Model-Agnostic Interpretability of Machine Learning
Marco Tulio Ribeiro
Sameer Singh
Carlos Guestrin
FAtt
FaML
84
838
0
16 Jun 2016
Not Just a Black Box: Learning Important Features Through Propagating
  Activation Differences
Not Just a Black Box: Learning Important Features Through Propagating Activation Differences
Avanti Shrikumar
Peyton Greenside
A. Shcherbina
A. Kundaje
FAtt
80
788
0
05 May 2016
Layer-wise Relevance Propagation for Neural Networks with Local
  Renormalization Layers
Layer-wise Relevance Propagation for Neural Networks with Local Renormalization Layers
Alexander Binder
G. Montavon
Sebastian Lapuschkin
K. Müller
Wojciech Samek
FAtt
72
461
0
04 Apr 2016
Molecular Graph Convolutions: Moving Beyond Fingerprints
Molecular Graph Convolutions: Moving Beyond Fingerprints
S. Kearnes
Kevin McCloskey
Marc Berndl
Vijay S. Pande
Patrick F. Riley
GNN
137
1,449
0
02 Mar 2016
"Why Should I Trust You?": Explaining the Predictions of Any Classifier
"Why Should I Trust You?": Explaining the Predictions of Any Classifier
Marco Tulio Ribeiro
Sameer Singh
Carlos Guestrin
FAtt
FaML
1.2K
16,954
0
16 Feb 2016
Evaluating the visualization of what a Deep Neural Network has learned
Evaluating the visualization of what a Deep Neural Network has learned
Wojciech Samek
Alexander Binder
G. Montavon
Sebastian Lapuschkin
K. Müller
XAI
134
1,192
0
21 Sep 2015
Understanding Neural Networks Through Deep Visualization
Understanding Neural Networks Through Deep Visualization
J. Yosinski
Jeff Clune
Anh Totti Nguyen
Thomas J. Fuchs
Hod Lipson
FAtt
AI4CE
122
1,871
0
22 Jun 2015
Inverting Visual Representations with Convolutional Networks
Inverting Visual Representations with Convolutional Networks
Alexey Dosovitskiy
Thomas Brox
SSL
FAtt
61
665
0
09 Jun 2015
Striving for Simplicity: The All Convolutional Net
Striving for Simplicity: The All Convolutional Net
Jost Tobias Springenberg
Alexey Dosovitskiy
Thomas Brox
Martin Riedmiller
FAtt
246
4,667
0
21 Dec 2014
Understanding Deep Image Representations by Inverting Them
Understanding Deep Image Representations by Inverting Them
Aravindh Mahendran
Andrea Vedaldi
FAtt
111
1,963
0
26 Nov 2014
Going Deeper with Convolutions
Going Deeper with Convolutions
Christian Szegedy
Wei Liu
Yangqing Jia
P. Sermanet
Scott E. Reed
Dragomir Anguelov
D. Erhan
Vincent Vanhoucke
Andrew Rabinovich
447
43,635
0
17 Sep 2014
Recurrent Neural Network Regularization
Recurrent Neural Network Regularization
Wojciech Zaremba
Ilya Sutskever
Oriol Vinyals
ODL
134
2,776
0
08 Sep 2014
ImageNet Large Scale Visual Recognition Challenge
ImageNet Large Scale Visual Recognition Challenge
Olga Russakovsky
Jia Deng
Hao Su
J. Krause
S. Satheesh
...
A. Karpathy
A. Khosla
Michael S. Bernstein
Alexander C. Berg
Li Fei-Fei
VLM
ObjD
1.7K
39,509
0
01 Sep 2014
Deep Inside Convolutional Networks: Visualising Image Classification
  Models and Saliency Maps
Deep Inside Convolutional Networks: Visualising Image Classification Models and Saliency Maps
Karen Simonyan
Andrea Vedaldi
Andrew Zisserman
FAtt
307
7,292
0
20 Dec 2013
Visualizing and Understanding Convolutional Networks
Visualizing and Understanding Convolutional Networks
Matthew D. Zeiler
Rob Fergus
FAtt
SSL
589
15,876
0
12 Nov 2013
Building high-level features using large scale unsupervised learning
Building high-level features using large scale unsupervised learning
Quoc V. Le
MarcÁurelio Ranzato
R. Monga
M. Devin
Kai Chen
G. Corrado
J. Dean
A. Ng
SSL
OffRL
CVBM
116
2,269
0
29 Dec 2011
How to Explain Individual Classification Decisions
How to Explain Individual Classification Decisions
D. Baehrens
T. Schroeter
Stefan Harmeling
M. Kawanabe
K. Hansen
K. Müller
FAtt
128
1,103
0
06 Dec 2009
1