Attribution in Scale and Space

Attribution in Scale and Space

3 April 2020

Subhashini Venugopalan

Mukund Sundararajan

Papers citing "Attribution in Scale and Space"

18 / 18 papers shown

Title
Attention Mechanisms Don't Learn Additive Models: Rethinking Feature Importance for Transformers Tobias Leemann Alina Fastowski Felix Pfeiffer Gjergji Kasneci 62 5 0 10 Jan 2025
Unlearning-based Neural Interpretations Ching Lam Choi Alexandre Duplessis Serge Belongie FAtt 49 0 0 10 Oct 2024
Riemann Sum Optimization for Accurate Integrated Gradients Computation Swadesh Swain Shree Singhi 28 0 0 05 Oct 2024
Scale generalisation properties of extended scale-covariant and scale-invariant Gaussian derivative networks on image datasets with spatial scaling variations Andrzej Perzanowski Tony Lindeberg 53 1 0 17 Sep 2024
DiffExplainer: Unveiling Black Box Models Via Counterfactual Generation Yingying Fang Shuang Wu Zihao Jin Caiwen Xu Shiyi Wang Simon Walsh Guang Yang MedIm 42 4 0 21 Jun 2024
Manifold Integrated Gradients: Riemannian Geometry for Feature Attribution Eslam Zaher Maciej Trzaskowski Quan Nguyen Fred Roosta AAML 29 4 0 16 May 2024
MAEA: Multimodal Attribution for Embodied AI Vidhi Jain Jayant Sravan Tamarapalli Sahiti Yerramilli Yonatan Bisk 39 0 0 25 Jul 2023
TAX: Tendency-and-Assignment Explainer for Semantic Segmentation with Multi-Annotators Yuan Cheng Zu-Yun Shiau Fu-En Yang Yu-Chiang Frank Wang 39 2 0 19 Feb 2023
On the Relationship Between Explanation and Prediction: A Causal View Amir-Hossein Karimi Krikamol Muandet Simon Kornblith Bernhard Schölkopf Been Kim FAtt CML 37 14 0 13 Dec 2022
Quantitative Metrics for Evaluating Explanations of Video DeepFake Detectors Federico Baldassarre Quentin Debard Gonzalo Fiz Pontiveros Tri Kurniawan Wijaya 44 4 0 07 Oct 2022
A Rigorous Study of Integrated Gradients Method and Extensions to Internal Neuron Attributions Daniel Lundstrom Tianjian Huang Meisam Razaviyayn FAtt 24 64 0 24 Feb 2022
WaveFake: A Data Set to Facilitate Audio Deepfake Detection Joel Frank Lea Schonherr DiffM 129 123 0 04 Nov 2021
Attribution of Predictive Uncertainties in Classification Models Iker Perez Piotr Skalski Alec E. Barns-Graham Jason Wong David Sutton UQCV 32 6 0 19 Jul 2021
Explaining in Style: Training a GAN to explain a classifier in StyleSpace Oran Lang Yossi Gandelsman Michal Yarom Yoav Wald G. Elidan ... William T. Freeman Phillip Isola Amir Globerson Michal Irani Inbar Mosseri GAN 45 152 0 27 Apr 2021
Group-CAM: Group Score-Weighted Visual Explanations for Deep Convolutional Networks Qing-Long Zhang Lu Rao Yubin Yang 16 58 0 25 Mar 2021
Explainable Person Re-Identification with Attribute-guided Metric Distillation Xiaodong Chen Xinchen Liu Wu Liu Xiaoping Zhang Yongdong Zhang Tao Mei 53 44 0 02 Mar 2021
Explaining by Removing: A Unified Framework for Model Explanation Ian Covert Scott M. Lundberg Su-In Lee FAtt 48 242 0 21 Nov 2020
Feature Removal Is a Unifying Principle for Model Explanation Methods Ian Covert Scott M. Lundberg Su-In Lee FAtt 33 33 0 06 Nov 2020