papers
Publications (12)
cs.AI2018
Embedding Models for Episodic Knowledge Graphs
Yunpu Ma, Volker Tresp, Erik Daxberger
cs.CV2025
MM-Spatial: Exploring 3D Spatial Understanding in Multimodal LLMs
Erik Daxberger, Nina Wenzel, David Griffiths +8
cs.CV2023
Mobile V-MoEs: Scaling Down Vision Transformers via Sparse Mixture-of-Experts
Erik Daxberger, Floris Weers, Bowen Zhang +7
cs.CV2025
MM-Ego: Towards Building Egocentric Multimodal LLMs for Video QA
Hanrong Ye, Haotian Zhang, Erik Daxberger +9
cs.LG2020
Sample-Efficient Optimization in the Latent Space of Deep Generative Models via Weighted Retraining
Austin Tripp, Erik Daxberger, José Miguel Hernández-Lobato
cs.LG2025
Apple Intelligence Foundation Language Models: Tech Report 2025
Ethan Li, Anders Boesen Lindbo Larsen, Chen Zhang +395
cs.LG2022
Laplace Redux -- Effortless Bayesian Deep Learning
Erik Daxberger, Agustinus Kristiadi, Alexander Immer +3
cs.LG2020
Bayesian Variational Autoencoders for Unsupervised Out-of-Distribution Detection
Erik Daxberger, José Miguel Hernández-Lobato
cs.LG2022
Bayesian Deep Learning via Subnetwork Inference
Erik Daxberger, Eric Nalisnick, James Urquhart Allingham +2
cs.LG2021
Mixtures of Laplace Approximations for Improved Post-Hoc Uncertainty in Deep Learning
Runa Eschenhagen, Erik Daxberger, Philipp Hennig +1
cs.LG2020
Mixed-Variable Bayesian Optimization
Erik Daxberger, Anastasia Makarova, Matteo Turchetta +1
stat.ML2022
Adapting the Linearised Laplace Model Evidence for Modern Deep Learning
Javier Antorán, David Janz, James Urquhart Allingham +4