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

Martin Mundt will join Sara Beery, Shamini Kothari and Talia Ringer as a panelist in the NeurIPS 2022 Queer in AI Workshop panel on “Faculty and Queerness” on November 28th. The panel brings together a diverse group of queer faculty to discuss their experiences in… Read More »Martin Mundt will be part of the Queer in AI “Faculty & Queerness” panel at NeurIPS-22

we are extremely excited to be part of the organizer team in the newest effort in advancing the field: the Continual Causality bridge at AAAI-23: https://www.continualcausality.org Continual Causality is a full two-day event (7+8th of February at AAAI-23 in Washington DC, USA): a “bridge” with the aim of bringing together the research… Read More »AAAI-23 Bridge on Continual Causality