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

We are very pleased to announce that we are co-organizing the workshop on Continual Lifelong Learning at the Asian Conference on Machine Learning (ACML 2022), this December in hybrid format! The physical conference will be held December 8-10th in Hyderabad, India: https://www.acml-conf.org/2022/ The workshop spans many… Read More »Continual Lifelong Learning Workshop at ACML 2022

Our formerly pre-registered paper called “Elevating Perceptual Sample Quality in Probabilistic Circuits through Differentiable Sampling” is finally out in the Proceedings of Machine Learning Research (PMLR), Volume 181, Pages 1-21. The paper has started as part of the NeurIPS 2021 Preregister Science Workshop, where the… Read More »“Elevating Perceptual Sample Quality in Probabilistic Circuits through Differentiable Sampling” paper out now in PMLR 181

Our paper titled “Return of the normal distribution: Flexible deep continual learning with variational auto-encoders” is now published in Neural Networks, Volume 154, Pages 397-412, October 2022. In the paper we propose a novel two-stage variational auto-encoder approach to continual learning. Our approach comes with… Read More »“Return of the normal distribution: Flexible deep continual learning with variational auto-encoders” paper now in Neural Networks 154

Group leader Martin Mundt has joined the board of directors of the non-profit ContinualAI organization for the election term of 2022-2024. Following up on the last years’ successes of ContinualAI, the six board members will continue scaling up the organization’s efforts to facilitate public access… Read More »Martin Mundt has joined the board of ContinualAI