Our paper “Deep Classifier Mimicry without Data Access” got accepted at the International Conference on Artificial Intelligence and Statistics (AISTATS) 2024. We are honored to have been selected for an oral presentation!
Our paper “Adaptive Rational Activations to Boost Deep Reinforcement Learning” was accepted at the International Conference on Learning Representations (ICLR) 2024. We are honored to have been selected for a spotlight presentation!
Following the in-person European Summer School on AI (ESSAI) in Ljubljana, Slovenia from July 24-28. 2023, the recordings for the 5-day course on “Machine Learning Beyond Static Datasets” have now been made publicly available.
We are delighted to welcome Qi Li as a research assistant in the OWLL group. In the process of working on her Master’s degree, Qi will spend the next year exploring continual learning models for climate within the recently granted project CAIMAN: “Continual Artificial Intelligence… Read More »Qi Li joins as research assistant for project CAIMAN
Our paper title “Designing a Hybrid Neural System to Learn Real-world Crack Segmentation from Fractal-based Simulation” has been accepted for publication at the Winter Conference on Applications of Computer Vision (WACV). The paper tackles the challenging real-world task to semantically segment cracks in concrete infrastructure.… Read More »“Designing a Hybrid Neural System to Learn Real-world Crack Segmentation from Fractal-based Simulation” accepted at WACV 2024
MICCAI 2023 is hosting the DAICOW tutorial on October 12st 2023: the 1st MICCAI tutorial on dynamic and continual AI for medical imaging. As part of the tutorial, Martin Mundt talks about the “Pillars of Forgetting & Lifelong Evaluation”. If you have missed the tutorial… Read More »Tutorial at MICCAI 2023 -“Pillars of Forgetting & Lifelong Evaluation”
The recently accepted Queer in AI paper titled “Queer in AI: A case Study in Community-led Participatory AI” has received the best paper award at the ACM Conference on Fairness, Accountability, and Transparency (ACM FAccT) 2023.
The proceedings, Proceedings of Machine Learning (PMLR) Volume 208, are now publicly available for the AAAI-23 Continual Causality bridge (https://www.continualcausality.org). Proceedings include close to a 100 pages of content that initiates a first bridge between continual learning & causality research. As a special foreword, the organizers… Read More »Continual Causality PMLR proceedings & retrospective paper are out
Our paper titled “Probabilistic Circuits That Know What They Don’t Know” has been accepted for publication at the Uncertainty in Artificial Intelligence (UAI) conference 2023 and has been selected for a 25 minute oral presentation. The paper draws inspiration from the overconfidence phenomenon in neural… Read More »“Probabilistic Circuits That Know What They Don’t Know” accepted with oral presentation at UAI 2023
We are pleased to announce the Call for Papers (to be published in PMLR) and Call for Talks for the upcoming ContinualAI Unconference (CLAI Unconf). Organized by the non-profit research organization, ContinualAI, the conference seeks to accelerate inclusive and sustainable progress in our academic community through… Read More »Announcing the 1st Continual AI Unconference