Interpretability and Explainability: A Machine Learning Zoo Mini-tour

3 December 2020

Papers citing "Interpretability and Explainability: A Machine Learning Zoo Mini-tour"

50 / 53 papers shown

Title
Combining Bayesian Inference and Reinforcement Learning for Agent Decision Making: A Review Chengmin Zhou Ville Kyrki P. Fränti Laura Ruotsalainen BDL AI4CE 42 0 0 12 May 2025
Explainable and Interpretable Multimodal Large Language Models: A Comprehensive Survey Yunkai Dang Kaichen Huang Jiahao Huo Yibo Yan S. Huang ... Kun Wang Yong Liu Jing Shao Hui Xiong Xuming Hu LRM 101 14 0 03 Dec 2024
From Logits to Hierarchies: Hierarchical Clustering made Simple Emanuele Palumbo Moritz Vandenhirtz Alain Ryser Imant Daunhawer Julia E. Vogt 26 1 0 10 Oct 2024
Explainable Artificial Intelligence: A Survey of Needs, Techniques, Applications, and Future Direction Melkamu Mersha Khang Lam Joseph Wood Ali AlShami Jugal Kalita XAI AI4TS 67 28 0 30 Aug 2024
Introducing Ínside' Out of Distribution Teddy Lazebnik 31 1 0 05 Jul 2024
Unifying Interpretability and Explainability for Alzheimer's Disease Progression Prediction Raja Farrukh Ali Stephanie Milani John Woods Emmanuel Adenij Ayesha Farooq Clayton Mansel Jeffrey Burns William Hsu 33 0 0 11 Jun 2024
P-NAL: an Effective and Interpretable Entity Alignment Method Chuanhao Xu Jingwei Cheng Fu Zhang 52 1 0 18 Apr 2024
Interpretability in Symbolic Regression: a benchmark of Explanatory Methods using the Feynman data set Guilherme Seidyo Imai Aldeia Fabrício Olivetti de França 21 10 0 08 Apr 2024
The Probabilities Also Matter: A More Faithful Metric for Faithfulness of Free-Text Explanations in Large Language Models Noah Y. Siegel Oana-Maria Camburu N. Heess Maria Perez-Ortiz 20 8 0 04 Apr 2024
Intrinsic Subgraph Generation for Interpretable Graph based Visual Question Answering Pascal Tilli Ngoc Thang Vu 33 1 0 26 Mar 2024
On the Challenges and Opportunities in Generative AI Laura Manduchi Kushagra Pandey Robert Bamler Ryan Cotterell Sina Daubener ... F. Wenzel Frank Wood Stephan Mandt Vincent Fortuin Vincent Fortuin 56 17 0 28 Feb 2024
Taking Class Imbalance Into Account in Open Set Recognition Evaluation Joanna Komorniczak Pawel Ksieniewicz 25 0 0 09 Feb 2024
Experimental Insights Towards Explainable and Interpretable Pedestrian Crossing Prediction Angie Nataly Melo Carlota Salinas Miguel Ángel Sotelo 30 3 0 05 Dec 2023
MetaSymNet: A Dynamic Symbolic Regression Network Capable of Evolving into Arbitrary Formulations Yanjie Li Weijun Li Lina Yu Min Wu Jinyi Liu Wenqiang Li Meilan Hao Shu Wei Yusong Deng 18 1 0 13 Nov 2023
Is Machine Learning Unsafe and Irresponsible in Social Sciences? Paradoxes and Reconsidering from Recidivism Prediction Tasks Jianhong Liu D. Li 10 1 0 11 Nov 2023
Symbolic Regression as Feature Engineering Method for Machine and Deep Learning Regression Tasks Assaf Shmuel Oren Glickman Teddy Lazebnik 38 9 0 10 Nov 2023
Massively-Parallel Heat Map Sorting and Applications To Explainable Clustering Sepideh Aghamolaei Mohammad Ghodsi 16 0 0 14 Sep 2023
Trustworthy Representation Learning Across Domains Ronghang Zhu Dongliang Guo Daiqing Qi Zhixuan Chu Xiang Yu Sheng R. Li FaML AI4TS 33 2 0 23 Aug 2023
R-Cut: Enhancing Explainability in Vision Transformers with Relationship Weighted Out and Cut Yingjie Niu Ming Ding Maoning Ge Robin Karlsson Yuxiao Zhang K. Takeda ViT 26 3 0 18 Jul 2023
Neurosymbolic AI for Reasoning on Biomedical Knowledge Graphs L. Delong Ramon Fernández Mir Zonglin Ji Fiona Niamh Coulter Smith Jacques D. Fleuriot 35 1 0 17 Jul 2023
Improving Explainability of Disentangled Representations using Multipath-Attribution Mappings Lukas Klein João B. S. Carvalho Mennatallah El-Assady Paolo Penna J. M. Buhmann Paul F. Jaeger 16 4 0 15 Jun 2023
Sanity Checks for Saliency Methods Explaining Object Detectors Deepan Padmanabhan Paul G. Plöger Octavio Arriaga Matias Valdenegro-Toro FAtt AAML XAI 18 2 0 04 Jun 2023
torchosr -- a PyTorch extension package for Open Set Recognition models evaluation in Python Joanna Komorniczak Pawel Ksieniewicz 3DV 10 3 0 16 May 2023
MLHOps: Machine Learning for Healthcare Operations Kristoffer Larsen Vallijah Subasri A. Krishnan Cláudio Tinoco Mesquita Diana Paez Laleh Seyyed-Kalantari Amalia Peix LM&MA AI4TS VLM 27 2 0 04 May 2023
Survey on Leveraging Uncertainty Estimation Towards Trustworthy Deep Neural Networks: The Case of Reject Option and Post-training Processing M. Hasan Moloud Abdar Abbas Khosravi U. Aickelin Pietro Lio' Ibrahim Hossain Ashikur Rahman Saeid Nahavandi 32 4 0 11 Apr 2023
A Scalable Space-efficient In-database Interpretability Framework for Embedding-based Semantic SQL Queries P. Kudva R. Bordawekar Apoorva Nitsure 12 0 0 23 Feb 2023
Neurosymbolic AI for Reasoning over Knowledge Graphs: A Survey L. Delong Ramon Fernández Mir Jacques D. Fleuriot NAI 28 12 0 14 Feb 2023
The Contextual Lasso: Sparse Linear Models via Deep Neural Networks Ryan Thompson Amir Dezfouli Robert Kohn 31 4 0 02 Feb 2023
Explaining Quantum Circuits with Shapley Values: Towards Explainable Quantum Machine Learning R. Heese Thore Gerlach Sascha Mucke Sabine Muller Matthias Jakobs Nico Piatkowski 24 18 0 22 Jan 2023
What Makes a Good Explanation?: A Harmonized View of Properties of Explanations Zixi Chen Varshini Subhash Marton Havasi Weiwei Pan Finale Doshi-Velez XAI FAtt 33 18 0 10 Nov 2022
Explainable Deep Learning to Profile Mitochondrial Disease Using High Dimensional Protein Expression Data Atif Khan C. Lawless Amy Vincent Satish Pilla S. Ramesh A. Mcgough 33 0 0 31 Oct 2022
Explanation Method for Anomaly Detection on Mixed Numerical and Categorical Spaces Iñigo López-Riobóo Botana Carlos Eiras-Franco Julio César Hernández Castro Amparo Alonso-Betanzos 19 0 0 09 Sep 2022
Interpretable Time Series Clustering Using Local Explanations Ozan Ozyegen Nicholas Prayogo Mucahit Cevik Ayse Basar FAtt AI4TS 16 1 0 01 Aug 2022
From Correlation to Causation: Formalizing Interpretable Machine Learning as a Statistical Process Lukas Klein Mennatallah El-Assady Paul F. Jäger CML 11 1 0 11 Jul 2022
A systematic review of biologically-informed deep learning models for cancer: fundamental trends for encoding and interpreting oncology data Magdalena Wysocka Oskar Wysocki Marie Zufferey Dónal Landers André Freitas AI4CE 48 28 0 02 Jul 2022
Think About the Stakeholders First! Towards an Algorithmic Transparency Playbook for Regulatory Compliance Andrew Bell O. Nov Julia Stoyanovich 27 26 0 10 Jun 2022
Can Requirements Engineering Support Explainable Artificial Intelligence? Towards a User-Centric Approach for Explainability Requirements Umm-e-Habiba Justus Bogner Stefan Wagner XAI 16 13 0 03 Jun 2022
Sparse Visual Counterfactual Explanations in Image Space Valentyn Boreiko Maximilian Augustin Francesco Croce Philipp Berens Matthias Hein BDL CML 30 26 0 16 May 2022
System Cards for AI-Based Decision-Making for Public Policy Furkan Gursoy I. Kakadiaris MLAU 21 14 0 01 Mar 2022
Testing Granger Non-Causality in Panels with Cross-Sectional Dependencies Lenon Minorics Ali Caner Türkmen D. Kernert Patrick Bloebaum Laurent Callot Dominik Janzing 14 1 0 23 Feb 2022
Discrete and continuous representations and processing in deep learning: Looking forward Ruben Cartuyvels Graham Spinks Marie-Francine Moens OCL 30 20 0 04 Jan 2022
Explainability Is in the Mind of the Beholder: Establishing the Foundations of Explainable Artificial Intelligence Kacper Sokol Peter A. Flach 36 20 0 29 Dec 2021
How to Find a Good Explanation for Clustering? Sayan Bandyapadhyay F. Fomin P. Golovach W. Lochet Nidhi Purohit Kirill Simonov 24 33 0 13 Dec 2021
TorchEsegeta: Framework for Interpretability and Explainability of Image-based Deep Learning Models S. Chatterjee Arnab Das Chirag Mandal Budhaditya Mukhopadhyay Manish Vipinraj Aniruddh Shukla R. Rao Chompunuch Sarasaen Oliver Speck A. Nürnberger MedIm 34 14 0 16 Oct 2021
FUTURE-AI: Guiding Principles and Consensus Recommendations for Trustworthy Artificial Intelligence in Medical Imaging Karim Lekadira Richard Osuala C. Gallin Noussair Lazrak Kaisar Kushibar ... Nickolas Papanikolaou Zohaib Salahuddin Henry C. Woodruff Philippe Lambin L. Martí-Bonmatí AI4TS 68 56 0 20 Sep 2021
Logic Explained Networks Gabriele Ciravegna Pietro Barbiero Francesco Giannini Marco Gori Pietro Lió Marco Maggini S. Melacci 35 69 0 11 Aug 2021
Responsible and Regulatory Conform Machine Learning for Medicine: A Survey of Challenges and Solutions Eike Petersen Yannik Potdevin Esfandiar Mohammadi Stephan Zidowitz Sabrina Breyer ... Sandra Henn Ludwig Pechmann M. Leucker P. Rostalski Christian Herzog FaML AILaw OOD 27 21 0 20 Jul 2021
An Imprecise SHAP as a Tool for Explaining the Class Probability Distributions under Limited Training Data Lev V. Utkin A. Konstantinov Kirill Vishniakov FAtt 23 5 0 16 Jun 2021
Context-Sensitive Visualization of Deep Learning Natural Language Processing Models A. Dunn Diana Inkpen Razvan Andonie 14 8 0 25 May 2021
Ensembles of Random SHAPs Lev V. Utkin A. Konstantinov FAtt 16 20 0 04 Mar 2021