Luke Guerdan

According to our database, Luke Guerdan authored at least 9 papers between 2019 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Causal-HRI: Causal Learning for Human-Robot Interaction.

Jiaee Cheong, Nikhil Churamani, Luke Guerdan, Tabitha Edith Lee, Zhao Han, Hatice Gunes

Proceedings of the Companion of the 2024 ACM/IEEE International Conference on Human-Robot Interaction, 2024

2023

Federated Continual Learning for Socially Aware Robotics.

Luke Guerdan, Hatice Gunes

Proceedings of the 32nd IEEE International Conference on Robot and Human Interactive Communication, 2023

Ground(less) Truth: A Causal Framework for Proxy Labels in Human-Algorithm Decision-Making.

Luke Guerdan, Amanda Coston, Zhiwei Steven Wu, Kenneth Holstein

Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency, 2023

Counterfactual Prediction Under Outcome Measurement Error.

Luke Guerdan, Amanda Coston, Kenneth Holstein, Zhiwei Steven Wu

Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency, 2023

Training Towards Critical Use: Learning to Situate AI Predictions Relative to Human Knowledge.

Anna Kawakami, Luke Guerdan, Yanghuidi Cheng, Kate Glazko, Matthew L. Lee, Scott A. Carter, Nikos Aréchiga, Haiyi Zhu, Kenneth Holstein

Proceedings of The ACM Collective Intelligence Conference, 2023

2022

Towards a Learner-Centered Explainable AI: Lessons from the learning sciences.

Anna Kawakami, Luke Guerdan, Yang Cheng, Anita Sun, Alison Hu, Kate Glazko, Nikos Aréchiga, Matthew L. Lee, Scott A. Carter, Haiyi Zhu, Kenneth Holstein

CoRR, 2022

Decentralized Robot Learning for Personalization and Privacy.

Luke Guerdan, Hatice Gunes

CoRR, 2022

2021

Toward Affective XAI: Facial Affect Analysis for Understanding Explainable Human-AI Interactions.

Luke Guerdan, Alex Raymond, Hatice Gunes

Proceedings of the IEEE/CVF International Conference on Computer Vision Workshops, 2021

2019

Extracting Motion-Related Subspaces from EEG in Mobile Brain/Body Imaging Studies using Source Power Comodulation.

Lukas Gehrke, Luke Guerdan, Klaus Gramann

Proceedings of the 2019 9th International IEEE/EMBS Conference on Neural Engineering (NER), 2019