activity
20192021
most citedHow to Train Your Energy-Based Model for Regression

15 citations · 15 across the 3 of their papers we have counts for

collaborators

9 papers

eess.IV2021

Uncertainty-Aware Body Composition Analysis with Deep Regression Ensembles on UK Biobank MRI

Taro Langner, Fredrik K. Gustafsson, Benny Avelin +3

Along with rich health-related metadata, medical images have been acquired for over 40,000 male and female UK Biobank participants, aged 44-82, since 2014. Phenotypes derived from…

cs.LG2020

Deep Energy-Based NARX Models

Johannes N. Hendriks, Fredrik K. Gustafsson, Antônio H. Ribeiro +2

This paper is directed towards the problem of learning nonlinear ARX models based on system input--output data. In particular, our interest is in learning a conditional distributio…

cs.CV202015 cited

How to Train Your Energy-Based Model for Regression

Fredrik K. Gustafsson, Martin Danelljan, Radu Timofte +1

Energy-based models (EBMs) have become increasingly popular within computer vision in recent years. While they are commonly employed for generative image modeling, recent work has…

eess.SP2019

Exploring Positive Noise in Estimation Theory

Kamiar Radnosrati, Gustaf Hendeby, Fredrik Gustafsson

Estimation of a deterministic quantity observed in non-Gaussian additive noise is explored via order statistics approach. More specifically, we study the estimation problem when me…

cs.LG2019

Energy-Based Models for Deep Probabilistic Regression

Fredrik K. Gustafsson, Martin Danelljan, Goutam Bhat +1

While deep learning-based classification is generally tackled using standardized approaches, a wide variety of techniques are employed for regression. In computer vision, one parti…

eess.SP2019

Asynchronous Averaging of Gait Cycles for Classification of Gait and Device Modes

Parinaz Kasebzadeh, Gustaf Hendeby, Fredrik Gustafsson

An approach for computing unique gait signature using measurements collected from body-worn inertial measurement units (IMUs) is proposed. The gait signature represents one full cy…