Inga Strümke - RankMe

50 papers A 2B 2C 2Misc 1Journal 42Unranked 1

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	A Framework for Causal Concept-based Model Explanations. CoRR Anna Rodum Bjøru, Jacob Lysnæs-Larsen, Oskar Jørgensen, Inga Strümke, Helge Langseth
2025	J	`jnl`	A framework for causal concept-based model explanations. Frontiers Artif. Intell. Anna Rodum Bjøru, Jacob Lysnæs-Larsen, Oskar Jørgensen, Inga Strümke, Helge Langseth
2025	J	`jnl`	Choose your explanation: a comparison of SHAP and Grad-CAM in human activity recognition. Appl. Intell. Felix Tempel, Daniel Groos, Espen Alexander Fürst Ihlen, Lars Adde, Inga Strümke
2025	—	`conf`	Clash of Requirements: Users First vs. Model First. SIGSOFT FSE Companion Tor Sporsem, Rasmus Ulfsnes, Morten Hatling, Inga Strümke
2025	J	`jnl`	Clinicians don't know what explanations they need: A case study on eliciting AI software explainability requirements. CoRR Tor Sporsem, Stine Rasdal Finserås, Inga Strümke
2025	J	`jnl`	Evaluating Explainable AI Methods in Deep Learning Models for Early Detection of Cerebral Palsy. IEEE Access Kimji N. Pellano, Inga Strümke, Daniel Groos, Lars Adde, Espen A. F. Ihlen
2025	J	`jnl`	Explaining Human Activity Recognition with SHAP: Validating insights with perturbation and quantitative measures. Comput. Biol. Medicine Felix Tempel, Espen Alexander Fürst Ihlen, Lars Adde, Inga Strümke
2025	J	`jnl`	Integrating attention into explanation frameworks for language and vision transformers. CoRR Marte Eggen, Jacob Lysnæs-Larsen, Inga Strümke
2025	J	`jnl`	Probing the Probes: Methods and Metrics for Concept Alignment. CoRR Jacob Lysnæs-Larsen, Marte Eggen, Inga Strümke
2025	J	`jnl`	Towards Biomarker Discovery for Early Cerebral Palsy Detection: Evaluating Explanations Through Kinematic Perturbations. CoRR Kimji N. Pellano, Inga Strümke, Daniel Groos, Lars Adde, Pål Haugen, Espen Alexander Fürst Ihlen
2024	J	`jnl`	A transformer-based deep reinforcement learning approach to spatial navigation in a partially observable Morris Water Maze. CoRR Marte Eggen, Inga Strümke
2024	J	`jnl`	AutoGCN - Towards Generic Human Activity Recognition with Neural Architecture Search. CoRR Felix Tempel, Inga Strümke, Espen Alexander Fürst Ihlen
2024	J	`jnl`	AutoGCN-Toward Generic Human Activity Recognition With Neural Architecture Search. IEEE Access Felix Tempel, Espen Alexander Fürst Ihlen, Inga Strümke
2024	J	`jnl`	Choose Your Explanation: A Comparison of SHAP and GradCAM in Human Activity Recognition. CoRR Felix Tempel, Daniel Groos, Espen Alexander Fürst Ihlen, Lars Adde, Inga Strümke
2024	J	`jnl`	Evaluating Explainable AI Methods in Deep Learning Models for Early Detection of Cerebral Palsy. CoRR Kimji N. Pellano, Inga Strümke, Daniel Groos, Lars Adde, Espen Alexander Fürst Ihlen
2024	J	`jnl`	Explaining Human Activity Recognition with SHAP: Validating Insights with Perturbation and Quantitative Measures. CoRR Felix Tempel, Espen Alexander Fürst Ihlen, Lars Adde, Inga Strümke
2024	J	`jnl`	From Movements to Metrics: Evaluating Explainable AI Methods in Skeleton-Based Human Activity Recognition. CoRR Kimji N. Pellano, Inga Strümke, Espen Alexander Fürst Ihlen
2024	J	`jnl`	From Movements to Metrics: Evaluating Explainable AI Methods in Skeleton-Based Human Activity Recognition. Sensors Kimji N. Pellano, Inga Strümke, Espen A. F. Ihlen
2024	J	`jnl`	Interplay between Federated Learning and Explainable Artificial Intelligence: a Scoping Review. CoRR Luis M. Lopez-Ramos, Florian Leiser, Aditya Rastogi, Steven Hicks, Inga Strümke, Vince I. Madai, Tobias Budig, Ali Sunyaev, Adam Hilbert
2024	J	`jnl`	Lightweight Neural Architecture Search for Cerebral Palsy Detection. CoRR Felix Tempel, Espen A. F. Ihlen, Inga Strümke
2024	Misc	`conf`	Multi-choice Solutions for Feature and Parameter Importance. AusDM Daniel Vidali Fryer, David Lowing, Inga Strümke, Hien Duy Nguyen
2023	J	`jnl`	Against Algorithmic Exploitation of Human Vulnerabilities. CoRR Inga Strümke, Marija Slavkovik, Clemens Stachl
2023	J	`jnl`	Concept backpropagation: An Explainable AI approach for visualising learned concepts in neural network models. CoRR Patrik Hammersborg, Inga Strümke
2023	B	`conf`	Identifying Important Proteins in Meibomian Gland Dysfunction with Explainable Artificial Intelligence. CBMS Andrea M. Storås, Morten Magnø, Fredrik A. Fineide, Bernd Thiede, Xiangjun Chen, Inga Strümke, Pål Halvorsen, Tor P. Utheim, Michael A. Riegler
2023	J	`jnl`	Inferring feature importance with uncertainties with application to large genotype data. PLoS Comput. Biol. Pål Vegard Johnsen, Inga Strümke, Mette Langaas, Andrew Thomas DeWan, Signe Riemer-Sørensen
2023	J	`jnl`	Information based explanation methods for deep learning agents - with applications on large open-source chess models. CoRR Patrik Hammersborg, Inga Strümke
2023	J	`jnl`	Lecture Notes in Probabilistic Diffusion Models. CoRR Inga Strümke, Helge Langseth
2023	J	`jnl`	Model tree methods for explaining deep reinforcement learning agents in real-time robotic applications. Neurocomputing Vilde B. Gjærum, Inga Strümke, Jakob Løver, Timothy Miller, Anastasios M. Lekkas
2022	C	`conf`	Causal versus Marginal Shapley Values for Robotic Lever Manipulation Controlled using Deep Reinforcement Learning. ACC Sindre Benjamin Remman, Inga Strümke, Anastasios M. Lekkas
2022	C	`conf`	Experiences and Lessons Learned from a Crowdsourced-Remote Hybrid User Survey Framework. ISM Cise Midoglu, Andrea M. Storås, Saeed Shafiee Sabet, Malek Hammou, Steven Alexander Hicks, Inga Strümke, Michael Alexander Riegler, Carsten Griwodz, Pål Halvorsen
2022	A	`conf`	Explainability methods for machine learning systems for multimodal medical datasets: research proposal. MMSys Andrea M. Storås, Inga Strümke, Michael A. Riegler, Pål Halvorsen
2022	J	`jnl`	Explaining a Deep Reinforcement Learning Docking Agent Using Linear Model Trees with User Adapted Visualization. CoRR Vilde B. Gjærum, Inga Strümke, Ole Andreas Alsos, Anastasios M. Lekkas
2022	A	`conf`	Huldra: a framework for collecting crowdsourced feedback on multimedia assets. MMSys Malek Hammou, Cise Midoglu, Steven Alexander Hicks, Andrea M. Storås, Saeed Shafiee Sabet, Inga Strümke, Michael A. Riegler, Pål Halvorsen
2022	J	`jnl`	Interpretable machine learning in Physics. CoRR Christophe Grojean, Ayan Paul, Zhuoni Qian, Inga Strümke
2022	B	`conf`	Predicting Tacrolimus Exposure in Kidney Transplanted Patients Using Machine Learning. CBMS Andrea M. Storås, Anders Åsberg, Pål Halvorsen, Michael A. Riegler, Inga Strümke
2022	J	`jnl`	Predicting tacrolimus exposure in kidney transplanted patients using machine learning. CoRR Andrea M. Storås, Anders Åsberg, Pål Halvorsen, Michael A. Riegler, Inga Strümke
2022	J	`jnl`	Real-Time Counterfactual Explanations For Robotic Systems With Multiple Continuous Outputs. CoRR Vilde B. Gjærum, Inga Strümke, Anastasios M. Lekkas, Tim Miller
2022	J	`jnl`	Reinforcement Learning in an Adaptable Chess Environment for Detecting Human-understandable Concepts. CoRR Patrik Hammersborg, Inga Strümke
2022	J	`jnl`	Socioeconomic disparities and COVID-19: the causal connections. CoRR Tannista Banerjee, Ayan Paul, Vishak Srikanth, Inga Strümke
2022	J	`jnl`	The social dilemma in artificial intelligence development and why we have to solve it. AI Ethics Inga Strümke, Marija Slavkovik, Vince Istvan Madai
2022	J	`jnl`	Visual explanations for polyp detection: How medical doctors assess intrinsic versus extrinsic explanations. CoRR Steven Hicks, Andrea M. Storås, Michael Riegler, Cise Midoglu, Malek Hammou, Thomas de Lange, Sravanthi Parasa, Pål Halvorsen, Inga Strümke
2021	J	`jnl`	Artificial Intelligence in Dry Eye Disease. CoRR Andrea M. Storås, Inga Strümke, Michael A. Riegler, Jakob Grauslund, Hugo Lewi Hammer, Anis Yazidi, Pål Halvorsen, Kjell G. Gundersen, Tor Paaske Utheim, Catherine Jackson
2021	J	`jnl`	Causal versus Marginal Shapley Values for Robotic Lever Manipulation Controlled using Deep Reinforcement Learning. CoRR Sindre Benjamin Remman, Inga Strümke, Anastasios M. Lekkas
2021	J	`jnl`	Inferring feature importance with uncertainties in high-dimensional data. CoRR Pål Vegard Johnsen, Inga Strümke, Signe Riemer-Sørensen, Andrew Thomas DeWan, Mette Langaas
2021	J	`jnl`	Model independent feature attributions: Shapley values that uncover non-linear dependencies. PeerJ Comput. Sci. Daniel Vidali Fryer, Inga Strümke, Hien D. Nguyen
2021	J	`jnl`	Shapley Values for Feature Selection: The Good, the Bad, and the Axioms. IEEE Access Daniel Vidali Fryer, Inga Strümke, Hien D. Nguyen
2021	J	`jnl`	Shapley values for feature selection: The good, the bad, and the axioms. CoRR Daniel Vidali Fryer, Inga Strümke, Hien D. Nguyen
2021	J	`jnl`	The social dilemma in AI development and why we have to solve it. CoRR Inga Strümke, Marija Slavkovik, Vince I. Madai
2020	J	`jnl`	Explaining the data or explaining a model? Shapley values that uncover non-linear dependencies. CoRR Daniel Vidali Fryer, Inga Strümke, Hien D. Nguyen
2020	J	`jnl`	Shapley Value Confidence Intervals for Attributing Variance Explained. Frontiers Appl. Math. Stat. Daniel Vidali Fryer, Inga Strümke, Hien D. Nguyen