Teaching Compositionality to CNNs

Teaching Compositionality to CNNs

14 June 2017

Papers citing "Teaching Compositionality to CNNs"

15 / 15 papers shown

Title
AI-based association analysis for medical imaging using latent-space geometric confounder correction Xianjing Liu Bo-wen Li Meike W. Vernooij E. Wolvius Gennady V. Roshchupkin Esther E. Bron MedIm 29 0 0 03 Oct 2023
The Construction of Reality in an AI: A Review J. W. Johnston 3DV 13 1 0 03 Feb 2023
Greybox XAI: a Neural-Symbolic learning framework to produce interpretable predictions for image classification Adrien Bennetot Gianni Franchi Javier Del Ser Raja Chatila Natalia Díaz Rodríguez AAML 32 28 0 26 Sep 2022
EXplainable Neural-Symbolic Learning (X-NeSyL) methodology to fuse deep learning representations with expert knowledge graphs: the MonuMAI cultural heritage use case Natalia Díaz Rodríguez Alberto Lamas Jules Sanchez Gianni Franchi Ivan Donadello Siham Tabik David Filliat P. Cruz Rosana Montes Francisco Herrera 49 77 0 24 Apr 2021
Learning Compositional Representation for 4D Captures with Neural ODE Boyan Jiang Yinda Zhang Xingkui Wei Xiangyang Xue Yanwei Fu 27 28 0 15 Mar 2021
Rule Extraction from Binary Neural Networks with Convolutional Rules for Model Validation Sophie Burkhardt Jannis Brugger Nicolas Wagner Zahra Ahmadi Kristian Kersting Stefan Kramer NAI FAtt 25 8 0 15 Dec 2020
Interpretable and Accurate Fine-grained Recognition via Region Grouping Zixuan Huang Yin Li 12 138 0 21 May 2020
On Interpretability of Artificial Neural Networks: A Survey Fenglei Fan Jinjun Xiong Mengzhou Li Ge Wang AAML AI4CE 38 300 0 08 Jan 2020
Locality and compositionality in zero-shot learning Tristan Sylvain Linda Petrini R. Devon Hjelm 24 56 0 20 Dec 2019
Semantically Interpretable Activation Maps: what-where-how explanations within CNNs Diego Marcos Sylvain Lobry D. Tuia FAtt MILM 22 26 0 18 Sep 2019
X-ToM: Explaining with Theory-of-Mind for Gaining Justified Human Trust Arjun Reddy Akula Changsong Liu Sari Saba-Sadiya Hongjing Lu S. Todorovic J. Chai Song-Chun Zhu 24 18 0 15 Sep 2019
Combining Compositional Models and Deep Networks For Robust Object Classification under Occlusion Adam Kortylewski Qing Liu Huiyu Wang Zhishuai Zhang Alan Yuille 14 62 0 28 May 2019
Robustness of Object Recognition under Extreme Occlusion in Humans and Computational Models Hongru Zhu Peng Tang Jeongho Park Soojin Park Alan Yuille 22 49 0 11 May 2019
Explaining Neural Networks Semantically and Quantitatively Runjin Chen Hao Chen Ge Huang Jie Ren Quanshi Zhang FAtt 23 54 0 18 Dec 2018
Interpretable Neuron Structuring with Graph Spectral Regularization Alexander Tong David van Dijk Jay S. Stanley Matthew Amodio Kristina M. Yim R. Muhle J. Noonan Guy Wolf Smita Krishnaswamy 32 6 0 30 Sep 2018