Daxberger, Erik

7 publications

ICCV 2025 MM-Spatial: Exploring 3D Spatial Understanding in Multimodal LLMs Erik Daxberger, Nina Wenzel, David Griffiths, Haiming Gang, Justin Lazarow, Gefen Kohavi, Kai Kang, Marcin Eichner, Yinfei Yang, Afshin Dehghan, Peter Grasch

ICLR 2025 MMEgo: Towards Building Egocentric Multimodal LLMs for Video QA Hanrong Ye, Haotian Zhang, Erik Daxberger, Lin Chen, Zongyu Lin, Yanghao Li, Bowen Zhang, Haoxuan You, Dan Xu, Zhe Gan, Jiasen Lu, Yinfei Yang

TMLR 2023 Improving Continual Learning by Accurate Gradient Reconstructions of the past Erik Daxberger, Siddharth Swaroop, Kazuki Osawa, Rio Yokota, Richard E Turner, José Miguel Hernández-Lobato, Mohammad Emtiyaz Khan

ICML 2022 Adapting the Linearised Laplace Model Evidence for Modern Deep Learning Javier Antoran, David Janz, James U Allingham, Erik Daxberger, Riccardo Rb Barbano, Eric Nalisnick, Jose Miguel Hernandez-Lobato

ICML 2021 Bayesian Deep Learning via Subnetwork Inference Erik Daxberger, Eric Nalisnick, James U Allingham, Javier Antoran, Jose Miguel Hernandez-Lobato

NeurIPS 2021 Laplace Redux - Effortless Bayesian Deep Learning Erik Daxberger, Agustinus Kristiadi, Alexander Immer, Runa Eschenhagen, Matthias Bauer, Philipp Hennig

NeurIPS 2020 Sample-Efficient Optimization in the Latent Space of Deep Generative Models via Weighted Retraining Austin Tripp, Erik Daxberger, José Miguel Hernández-Lobato