Deep Learning for Case-Based Reasoning through Prototypes: A Neural Network that Explains Its Predictions

13 October 2017

Papers citing "Deep Learning for Case-Based Reasoning through Prototypes: A Neural Network that Explains Its Predictions"

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Title
This part looks alike this: identifying important parts of explained instances and prototypes Jacek Karolczak Jerzy Stefanowski 31 0 0 08 May 2025
If Concept Bottlenecks are the Question, are Foundation Models the Answer? Nicola Debole Pietro Barbiero Francesco Giannini Andrea Passerini Stefano Teso Emanuele Marconato 182 0 0 28 Apr 2025
Interpretable Affordance Detection on 3D Point Clouds with Probabilistic Prototypes M. Li Korbinian Franz Rudolf Nils Blank Rudolf Lioutikov 3DPC 41 0 0 25 Apr 2025
Enhancing Job Salary Prediction with Disentangled Composition Effect Modeling: A Neural Prototyping Approach Yang Ji Ying Sun Hengshu Zhu 46 1 0 17 Mar 2025
Re-Imagining Multimodal Instruction Tuning: A Representation View Yiyang Liu James Liang Ruixiang Tang Yugyung Lee Majid Rabbani ... Raghuveer M. Rao Lifu Huang Dongfang Liu Qifan Wang Cheng Han 183 0 0 02 Mar 2025
Uncertainty-Aware Explanations Through Probabilistic Self-Explainable Neural Networks Jon Vadillo Roberto Santana J. A. Lozano Marta Z. Kwiatkowska BDL AAML 73 0 0 17 Feb 2025
Shortcuts and Identifiability in Concept-based Models from a Neuro-Symbolic Lens Samuele Bortolotti Emanuele Marconato Paolo Morettin Andrea Passerini Stefano Teso 61 2 0 16 Feb 2025
Self-Explaining Hypergraph Neural Networks for Diagnosis Prediction Leisheng Yu Yanxiao Cai Minxing Zhang Xia Hu FAtt 195 0 0 15 Feb 2025
Cross- and Intra-image Prototypical Learning for Multi-label Disease Diagnosis and Interpretation Chong Wang Fengbei Liu Yuanhong Chen Helen Frazer Gustavo Carneiro 32 2 0 07 Nov 2024
Multi-Scale Grouped Prototypes for Interpretable Semantic Segmentation Hugo Porta Emanuele Dalsasso Diego Marcos D. Tuia 95 0 0 14 Sep 2024
Case-based Explainability for Random Forest: Prototypes, Critics, Counter-factuals and Semi-factuals Gregory Yampolsky Dhruv Desai Mingshu Li Stefano Pasquali Dhagash Mehta 34 4 0 13 Aug 2024
Novel Deep Neural Network Classifier Characterization Metrics with Applications to Dataless Evaluation Nathaniel R. Dean Dilip Sarkar 35 0 0 17 Jul 2024
Restyling Unsupervised Concept Based Interpretable Networks with Generative Models Jayneel Parekh Quentin Bouniot Pavlo Mozharovskyi A. Newson Florence dÁlché-Buc SSL 63 1 0 01 Jul 2024
Efficient User Sequence Learning for Online Services via Compressed Graph Neural Networks Yucheng Wu Liyue Chen Yu Cheng Shuai Chen Jinyu Xu Leye Wang GNN 32 0 0 05 Jun 2024
Improving deep learning with prior knowledge and cognitive models: A survey on enhancing explainability, adversarial robustness and zero-shot learning F. Mumuni A. Mumuni AAML 37 5 0 11 Mar 2024
Advancing Ante-Hoc Explainable Models through Generative Adversarial Networks Tanmay Garg Deepika Vemuri Vineeth N. Balasubramanian GAN 24 2 0 09 Jan 2024
HCDIR: End-to-end Hate Context Detection, and Intensity Reduction model for online comments Neeraj Kumar Singh Koyel Ghosh Joy Mahapatra Utpal Garain Apurbalal Senapati 19 0 0 20 Dec 2023
Prototypical Self-Explainable Models Without Re-training Srishti Gautam Ahcène Boubekki Marina M.-C. Höhne Michael C. Kampffmeyer 34 2 0 13 Dec 2023
ProtoArgNet: Interpretable Image Classification with Super-Prototypes and Argumentation [Technical Report] Hamed Ayoobi Nico Potyka Francesca Toni 44 2 0 26 Nov 2023
LSOR: Longitudinally-Consistent Self-Organized Representation Learning J. Ouyang Qingyu Zhao Ehsan Adeli Wei Peng Greg Zaharchuk K. Pohl 42 1 0 30 Sep 2023
Prototype-based Dataset Comparison Nanne van Noord 31 6 0 05 Sep 2023
UIPC-MF: User-Item Prototype Connection Matrix Factorization for Explainable Collaborative Filtering Lei Pan V. Soo 37 0 0 14 Aug 2023
Fantastic DNN Classifiers and How to Identify them without Data Nathaniel R. Dean D. Sarkar 23 1 0 24 May 2023
ICICLE: Interpretable Class Incremental Continual Learning Dawid Rymarczyk Joost van de Weijer Bartosz Zieliñski Bartlomiej Twardowski CLL 32 28 0 14 Mar 2023
Variational Information Pursuit for Interpretable Predictions Aditya Chattopadhyay Kwan Ho Ryan Chan B. Haeffele D. Geman René Vidal DRL 24 10 0 06 Feb 2023
ProtoSeg: Interpretable Semantic Segmentation with Prototypical Parts Mikolaj Sacha Dawid Rymarczyk Lukasz Struski Jacek Tabor Bartosz Zieliñski VLM 38 29 0 28 Jan 2023
Hierarchical Explanations for Video Action Recognition Sadaf Gulshad Teng Long Nanne van Noord FAtt 29 6 0 01 Jan 2023
Bort: Towards Explainable Neural Networks with Bounded Orthogonal Constraint Borui Zhang Wenzhao Zheng Jie Zhou Jiwen Lu AAML 25 7 0 18 Dec 2022
Counterfactual Explanations for Misclassified Images: How Human and Machine Explanations Differ Eoin Delaney A. Pakrashi Derek Greene Markt. Keane 35 16 0 16 Dec 2022
Robust and Explainable Identification of Logical Fallacies in Natural Language Arguments Zhivar Sourati Vishnu Priya Prasanna Venkatesh D. Deshpande Himanshu Rawlani Filip Ilievski Hông-Ân Sandlin Alain Mermoud AAML 31 20 0 12 Dec 2022
Learning to Select Prototypical Parts for Interpretable Sequential Data Modeling Yifei Zhang Nengneng Gao Cunqing Ma 23 6 0 07 Dec 2022
Intermediate Entity-based Sparse Interpretable Representation Learning Diego Garcia-Olano Yasumasa Onoe Joydeep Ghosh Byron C. Wallace 19 2 0 03 Dec 2022
Prototypical Fine-tuning: Towards Robust Performance Under Varying Data Sizes Yiqiao Jin Xiting Wang Y. Hao Yizhou Sun Xing Xie 38 11 0 24 Nov 2022
Towards Human-Interpretable Prototypes for Visual Assessment of Image Classification Models Poulami Sinhamahapatra Lena Heidemann Maureen Monnet Karsten Roscher 45 5 0 22 Nov 2022
Explaining Cross-Domain Recognition with Interpretable Deep Classifier Yiheng Zhang Ting Yao Zhaofan Qiu Tao Mei OOD 35 3 0 15 Nov 2022
Privacy Meets Explainability: A Comprehensive Impact Benchmark S. Saifullah Dominique Mercier Adriano Lucieri Andreas Dengel Sheraz Ahmed 35 14 0 08 Nov 2022
Towards Prototype-Based Self-Explainable Graph Neural Network Enyan Dai Suhang Wang 33 12 0 05 Oct 2022
TFN: An Interpretable Neural Network with Time-Frequency Transform Embedded for Intelligent Fault Diagnosis Qian Chen Xingjian Dong Guowei Tu Dong Wang Baoxuan Zhao Zhike Peng AI4CE 16 66 0 05 Sep 2022
Visual Interpretable and Explainable Deep Learning Models for Brain Tumor MRI and COVID-19 Chest X-ray Images Yusuf Brima M. Atemkeng FAtt MedIm 29 0 0 01 Aug 2022
GlanceNets: Interpretabile, Leak-proof Concept-based Models Emanuele Marconato Andrea Passerini Stefano Teso 106 64 0 31 May 2022
Prototype Based Classification from Hierarchy to Fairness Mycal Tucker J. Shah FaML 19 6 0 27 May 2022
Cardinality-Minimal Explanations for Monotonic Neural Networks Ouns El Harzli Bernardo Cuenca Grau Ian Horrocks FAtt 40 5 0 19 May 2022
CBR-iKB: A Case-Based Reasoning Approach for Question Answering over Incomplete Knowledge Bases Dung Ngoc Thai Srinivas Ravishankar Ibrahim Abdelaziz Mudit Chaudhary Nandana Mihindukulasooriya Tahira Naseem Rajarshi Das Pavan Kapanipathi Achille Fokoue Andrew McCallum 34 8 0 18 Apr 2022
ProtoTEx: Explaining Model Decisions with Prototype Tensors Anubrata Das Chitrank Gupta Venelin Kovatchev Matthew Lease Junjie Li 31 26 0 11 Apr 2022
Attribute Prototype Network for Any-Shot Learning Wenjia Xu Yongqin Xian Jiuniu Wang Bernt Schiele Zeynep Akata VLM 34 37 0 04 Apr 2022
Rethinking Semantic Segmentation: A Prototype View Tianfei Zhou Wenguan Wang E. Konukoglu Luc Van Gool SSeg 34 260 0 28 Mar 2022
Deformable ProtoPNet: An Interpretable Image Classifier Using Deformable Prototypes Jonathan Donnelly A. Barnett Chaofan Chen 3DH 33 127 0 29 Nov 2021
Transparency of Deep Neural Networks for Medical Image Analysis: A Review of Interpretability Methods Zohaib Salahuddin Henry C. Woodruff A. Chatterjee Philippe Lambin 24 303 0 01 Nov 2021
Interpreting Deep Learning Models in Natural Language Processing: A Review Xiaofei Sun Diyi Yang Xiaoya Li Tianwei Zhang Yuxian Meng Han Qiu Guoyin Wang Eduard H. Hovy Jiwei Li 19 44 0 20 Oct 2021
A Field Guide to Scientific XAI: Transparent and Interpretable Deep Learning for Bioinformatics Research Thomas P. Quinn Sunil R. Gupta Svetha Venkatesh Vuong Le OOD 19 2 0 13 Oct 2021