We are more than happy to welcome Malte Schwerin as a new PhD student in the OWL-ML lab. Malte Schwerin has previously completed a master’s degree in computer science at RWTH Aachen. For his master’s thesis, he visited UBC in Vancouver for four months, working… Read More »Malte Schwerin has joined as a PhD Student
We are hiring two fully-funded PhD students to build up the new OWL-ML lab at the University of Bremen. The deadline for applications is December 10th, 2024. Exact applications instructions can be found here. The positions are not tied to a specific project and have… Read More »Hiring 2 fully-funded PhD Students – Deadline Dec. 10
We are delighted to announce that Martin Mundt has accepted the position of full professor for Lifelong Machine Learning at the University of Bremen. Consequently, the lab will relocate to form the Open World Lifelong Machine Learning (OWL-ML) group in Bremen from January 2025. The… Read More »OWL-ML is moving to the University of Bremen
In addition to our call for papers at our third bridge on Continual Causality at AAAI-25 we are launching the Continual Confounding: ConCon Challenge! In the ConCon challenge participants can submit contributions to solve one of two (or both) challenging scenarios surrounding the newly found… Read More »We are launching the ConCon Challenge at the Continual Causality Bridge!
we are happy to co-organize the third edition of the Continual Causality bridge at AAAI-25! Continual Causality is a full two-day event (25+26th of February 2025 at AAAI-25 in Philadelphia, USA): a “bridge” with the aim of bringing together the research fields of continual learning and causality. Beyond scientific advance, one primary goal is to… Read More »The Continual Causality Bridge is back for round 3
Our paper “Distribution-Aware Replay for Continual MRI Segmentation” got accepted the Workshop Personalized Incremental Learning in Medicine at MICCAI 2024, with proceedings to be published in Lecture Notes in Computer Science (LNCS), Springer. In the paper, we demonstrate that a small generative model (a variational… Read More »”Distribution-Aware Replay for Continual MRI Segmentation” accepted at PILM-MICCAI 2024
We are very honored and grateful that our paper “Deep Classifier Mimicry without Data Access” has received an Outstanding Student Paper Highlight award at AISTATS 2024. In the paper, we introduce a method to distill a deep classifiers knowledge without making assumptions on model structure… Read More »We received the AISTATS 2024 outstanding student paper highlight
Our paper “Masked Autoencoders are Efficient Continual Federated Learners” got accepted for publication at the Conference on Lifelong Learning Agents (CoLLAs) 2024! In the paper we investigate the challenging task of unsupervised continual learning in federated (distributed) scenarios. Our key motivation is that even if… Read More »“Masked Autoencoders are Efficient Continual Federated Learners” accepted at CoLLAs 2024
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!
