Accepted Papers
Accepted vision papers are publicly accessible on OpenReview and are in the process of being compiled into a Proceedings of Machine Learning Volume. All accepted papers will present a poster at the Continual Causality Bridge. In addition, four papers have been selected for additional contributed talks.
Selected for Oral Presentation
- Modeling Uplift from Observational Time-Series in Continual Scenarios
Sanghyun Kim, Jungwon Choi, NamHee Kim, Jaesung Ryu, Juho Lee - From IID to the Independent Mechanisms assumption in continual learning
Oleksiy Ostapenko, Alexandre Lacoste, Laurent Charlin - Never Ending Reasoning and Learning: Opportunities and Challenges
Sriraam Natarajan, Kristian Kersting - Towards Causal Replay for Knowledge Rehearsal in Continual Learning
Nikhil Churamani, Jiaee Cheong, Sinan Kalkan, Hatice Gunes
Selected for Poster Presentation
- Issues for Continual Learning in the Presence of Dataset Bias
Donggyu Lee, Sangwon Jung, Taesup Moon - From Continual Learning to Causal Discovery in Robotics
Luca Castri, Sariah Mghames, Nicola Bellotto - Spurious Features in Continual Learning
Timothée Lesort - Causal Concept Identification in Open World Environments
Moritz Willig, Matej Zečević, Jonas Seng, Florian Peter Busch - Continual Causal Abstractions
Matej Zečević, Moritz Willig, Florian Peter Busch, Jonas Seng - Treatment Effect Estimation to Guide Model Optimization in Continual Learning
Jonas Seng, Florian Peter Busch, Matej Zečević, Moritz Willig - Continually Updating Neural Causal Models
Florian Peter Busch, Jonas Seng, Moritz Willig, Matej Zečević - Prospects of Continual Causality for Industrial Applications
Daigo Fujiwara, Kazuki Koyama, Keisuke Kiritoshi, Tomomi Okawachi, Tomonori Izumitani, Shohei Shimizu - Continual Treatment Effect Estimation: Challenges and Opportunities
Zhixuan Chu, Sheng Li