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
In collaboration with the Queer in AI community, a paper titled “Queer in AI: A Case Study in Community-led Participatory AI” has been accepted for publication at the ACM Conference on Fairness, Accountability, and Transparency (ACM FAccT) 2023. As implied in the title, the paper… Read More »“Queer in AI: A Case Study in Community-led Participatory AI” accepted at ACM FAccT 2023
Martin Mundt has given an invited talk at the Sensor and Measurement Science International Conference 2023 (SMSI) As sensors and measurement may drift in practice for a variety of reasons, it is important that intelligent systems are equipped with respective capabilities to recognize and update… Read More »Invited talk at SMSI 2023: “Continually Learning Machines That Understand What They Don’t Know”
We are excited to present a 5-day course on “Machine Learning Beyond Static Datasets” as part of the European Summer School on AI (ESSAI) in Ljubljana, Slovenia from July 24-28. Join the course to learn how to transcend the traditional static train-test machine learning focus… Read More »“Machine Learning Beyond Static Datasets”Course at European Summer School on AI
The Continual Machine Learning Course is starting on April 14th 2023 and will contain an overall 14 lectures to learn all about machine learning beyond assumptions of a static world. Following an updated outline on last year’s iteration , we will cover important elements spanning… Read More »Continual Machine Learning Course – Summer 2023
Our paper titled “A Wholistic View of Continual Learning with Deep Neural Networks: Forgotten Lessons and the Bridge to Active and Open World Learning” is now published in Neural Networks, volume 160, Pages 306-336. This paper is a comprehensive 30 page resource to both survey… Read More »“A Wholistic View of Continual Learning with Deep Neural Networks” paper now in Neural Networks 160
We are very excited that Martin Mundt is co-chairing and organizing the Queer in AI diversity & inclusion event at the AAAI 2023 conference: https://www.queerinai.com/aaai-2023 Queer in AI’s presence at AAAI 2023 aims to create a safe and inclusive casual networking and socializing space for… Read More »AAAI-23 Queer in AI
