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"

15 / 15 papers shown
Title
Unlearning-based Neural Interpretations
Unlearning-based Neural Interpretations
Ching Lam Choi
Alexandre Duplessis
Serge Belongie
FAtt
47
0
0
10 Oct 2024
The Generalizability of Explanations
The Generalizability of Explanations
Hanxiao Tan
FAtt
18
1
0
23 Feb 2023
End-to-end Ensemble-based Feature Selection for Paralinguistics Tasks
End-to-end Ensemble-based Feature Selection for Paralinguistics Tasks
Tamás Grósz
Mittul Singh
Sudarsana Reddy Kadiri
H. Kathania
M. Kurimo
23
0
0
28 Oct 2022
Generalizability Analysis of Graph-based Trajectory Predictor with
  Vectorized Representation
Generalizability Analysis of Graph-based Trajectory Predictor with Vectorized Representation
Juanwu Lu
Wei Zhan
Masayoshi Tomizuka
Yeping Hu
22
6
0
06 Aug 2022
Maximum Entropy Baseline for Integrated Gradients
Maximum Entropy Baseline for Integrated Gradients
Hanxiao Tan
FAtt
21
4
0
12 Apr 2022
Projective Ranking-based GNN Evasion Attacks
Projective Ranking-based GNN Evasion Attacks
He Zhang
Xingliang Yuan
Chuan Zhou
Shirui Pan
AAML
42
23
0
25 Feb 2022
Brain Structural Saliency Over The Ages
Brain Structural Saliency Over The Ages
Daniel Taylor
Jonathan Shock
Deshendran Moodley
J. Ipser
M. Treder
FAtt
16
1
0
12 Jan 2022
Clustering-Based Interpretation of Deep ReLU Network
Clustering-Based Interpretation of Deep ReLU Network
Nicola Picchiotti
Marco Gori
FAtt
17
0
0
13 Oct 2021
Do Input Gradients Highlight Discriminative Features?
Do Input Gradients Highlight Discriminative Features?
Harshay Shah
Prateek Jain
Praneeth Netrapalli
AAML
FAtt
23
57
0
25 Feb 2021
PGM-Explainer: Probabilistic Graphical Model Explanations for Graph
  Neural Networks
PGM-Explainer: Probabilistic Graphical Model Explanations for Graph Neural Networks
Minh Nhat Vu
My T. Thai
BDL
16
328
0
12 Oct 2020
Explainable Deep Learning: A Field Guide for the Uninitiated
Explainable Deep Learning: A Field Guide for the Uninitiated
Gabrielle Ras
Ning Xie
Marcel van Gerven
Derek Doran
AAML
XAI
41
371
0
30 Apr 2020
Explaining Regression Based Neural Network Model
Explaining Regression Based Neural Network Model
Mégane Millan
Catherine Achard
FAtt
21
3
0
15 Apr 2020
Explaining Visual Models by Causal Attribution
Explaining Visual Models by Causal Attribution
Álvaro Parafita
Jordi Vitrià
CML
FAtt
62
35
0
19 Sep 2019
Improving the Adversarial Robustness and Interpretability of Deep Neural
  Networks by Regularizing their Input Gradients
Improving the Adversarial Robustness and Interpretability of Deep Neural Networks by Regularizing their Input Gradients
A. Ross
Finale Doshi-Velez
AAML
37
675
0
26 Nov 2017
Right for the Right Reasons: Training Differentiable Models by
  Constraining their Explanations
Right for the Right Reasons: Training Differentiable Models by Constraining their Explanations
A. Ross
M. C. Hughes
Finale Doshi-Velez
FAtt
41
582
0
10 Mar 2017
1