Fast Machine Unlearning Without Retraining Through Selective Synaptic Dampening J Foster*, S Schoepf*, A Brintrup AAAI 2024 | *equal contribution, 2024 | 16 | 2024 |
An Information Theoretic Approach to Machine Unlearning J Foster, K Fogarty, S Schoepf, C Öztireli, A Brintrup arXiv preprint arXiv:2402.01401, 2024 | 3* | 2024 |
Parameter-tuning-free data entry error unlearning with adaptive selective synaptic dampening S Schoepf, J Foster, A Brintrup arXiv preprint arXiv:2402.10098, 2024 | 2 | 2024 |
Loss-Free Machine Unlearning J Foster*, S Schoepf*, A Brintrup ICLR 2024 Tiny Paper | *equal contribution, 2024 | 1 | 2024 |
Using Reinforcement Learning for the Three-Dimensional Loading Capacitated Vehicle Routing Problem S Schoepf, S Mak, J Senoner, L Xu, T Netland, A Brintrup IJCAI 2023; Workshop on Search and Planning with Complex Objectives (WoSePCO), 2023 | 1* | 2023 |
Implementation of Autonomous Supply Chains for Digital Twinning: a Multi-Agent Approach L Xu, Y Proselkov, S Schoepf, D Minarsch, M Minaricova, A Brintrup IFAC World Congress 2023 56 (2), 11076-11081, 2023 | 1 | 2023 |
NVH Signal Analysis via Pattern Recognition ANNs: Automotive Brake Creep Groan as Case Study M Pürscher, S Schoepf, P Fischer 8th Congress of the Alps Adria Acoustic Association (AAAA), 294-308, 2018 | 1 | 2018 |
Potion: Towards Poison Unlearning S Schoepf, J Foster, A Brintrup arXiv preprint arXiv:2406.09173, 2024 | | 2024 |
Identifying contributors to manufacturing outcomes in a multi-echelon setting: a decentralised uncertainty quantification approach S Schoepf, J Foster, A Brintrup ECML PKDD 2023; AI4M: AI for Manufacturing Workshop, 2023 | | 2023 |
Multi-Agent Digital Twinning for Collaborative Logistics: Framework and Implementation L Xu, S Mak, S Schoepf, M Ostroumov, A Brintrup Available at SSRN 4691072, 2023 | | 2023 |
Data augmentation and synthetic data generation for low-frequency and sparse data problems DSG The Alan Turing Institute Data Study Group https://zenodo.org/record/8328245, 2023 | | 2023 |