1 code implementation • 7 Feb 2023 • Fredrik K. Gustafsson, Martin Danelljan, Thomas B. Schön
We then employ our benchmark to evaluate many of the most common uncertainty estimation methods, as well as two state-of-the-art uncertainty scores from the task of out-of-distribution detection.
1 code implementation • 27 Jan 2023 • Ziwei Luo, Fredrik K. Gustafsson, Zheng Zhao, Jens Sjölund, Thomas B. Schön
This paper presents a stochastic differential equation (SDE) approach for general-purpose image restoration.
Ranked #2 on Single Image Deraining on Rain100H
1 code implementation • 21 Dec 2022 • Philipp Von Bachmann, Daniel Gedon, Fredrik K. Gustafsson, Antônio H. Ribeiro, Erik Lampa, Stefan Gustafsson, Johan Sundström, Thomas B. Schön
We therefore investigate if regression methods can be used for accurate ECG-based prediction of electrolyte concentrations.
1 code implementation • 22 Oct 2021 • Fredrik K. Gustafsson, Martin Danelljan, Thomas B. Schön
Energy-based models (EBMs) have experienced a resurgence within machine learning in recent years, including as a promising alternative for probabilistic regression.
1 code implementation • 18 Jan 2021 • Taro Langner, Fredrik K. Gustafsson, Benny Avelin, Robin Strand, Håkan Ahlström, Joel Kullberg
The results indicate that deep regression ensembles could ultimately provide automated, uncertainty-aware measurements of body composition for more than 120, 000 UK Biobank neck-to-knee body MRI that are to be acquired within the coming years.
1 code implementation • 8 Dec 2020 • Fredrik K. Gustafsson, Martin Danelljan, Thomas B. Schön
On the KITTI dataset, our proposed approach consistently outperforms the SA-SSD baseline across all 3DOD metrics, demonstrating the potential of EBM-based regression for highly accurate 3DOD.
Ranked #1 on 3D Object Detection on KITTI Cars Easy val
1 code implementation • 8 Dec 2020 • Johannes N. Hendriks, Fredrik K. Gustafsson, Antônio H. Ribeiro, Adrian G. Wills, Thomas B. Schön
This paper is directed towards the problem of learning nonlinear ARX models based on system input--output data.
1 code implementation • 4 May 2020 • Fredrik K. Gustafsson, Martin Danelljan, Radu Timofte, Thomas B. Schön
While they are commonly employed for generative image modeling, recent work has applied EBMs also for regression tasks, achieving state-of-the-art performance on object detection and visual tracking.
Ranked #1 on Visual Object Tracking on OTB-100
1 code implementation • ECCV 2020 • Fredrik K. Gustafsson, Martin Danelljan, Goutam Bhat, Thomas B. Schön
In our proposed approach, we create an energy-based model of the conditional target density p(y|x), using a deep neural network to predict the un-normalized density from (x, y).
Ranked #1 on Object Detection on COCO test-dev (Hardware Burden metric)
1 code implementation • 4 Jun 2019 • Fredrik K. Gustafsson, Martin Danelljan, Thomas B. Schön
We therefore accept this task and propose a comprehensive evaluation framework for scalable epistemic uncertainty estimation methods in deep learning.