Jes Frellsen

Jes Frellsen

Danmarks Tekniske Universitet

H-index: 20

Europe-Denmark

About Jes Frellsen

Jes Frellsen, With an exceptional h-index of 20 and a recent h-index of 16 (since 2020), a distinguished researcher at Danmarks Tekniske Universitet, specializes in the field of Deep Learning, Deep generative models, Statistical Machine Learning, Directional Statistics, Bioinformatics.

His recent articles reflect a diverse array of research interests and contributions to the field:

GAST: Geometry-Aware Structure Transformer

A Continuous Relaxation for Discrete Bayesian Optimization

Implicit Variational Inference for High-Dimensional Posteriors

Prior and Posterior Networks: A Survey on Evidential Deep Learning Methods For Uncertainty Estimation

Adaptive Cholesky Gaussian Processes

Internal-Coordinate Density Modelling of Protein Structure: Covariance Matters

Learning energy-based models by self-normalising the likelihood

Polygonizer: An auto-regressive building delineator

Jes Frellsen Information

University

Position

Associate Professor (DTU)

Citations(all)

1466

Citations(since 2020)

939

Cited By

766

hIndex(all)

20

hIndex(since 2020)

16

i10Index(all)

31

i10Index(since 2020)

24

Email

University Profile Page

Danmarks Tekniske Universitet

Google Scholar

View Google Scholar Profile

Jes Frellsen Skills & Research Interests

Deep Learning

Deep generative models

Statistical Machine Learning

Directional Statistics

Bioinformatics

Top articles of Jes Frellsen

Title

Journal

Author(s)

Publication Date

GAST: Geometry-Aware Structure Transformer

Maxim Khomiakov

Michael Riis Andersen

Jes Frellsen

2024

A Continuous Relaxation for Discrete Bayesian Optimization

arXiv preprint arXiv:2404.17452

Richard Michael

Simon Bartels

Miguel González-Duque

Yevgen Zainchkovskyy

Jes Frellsen

...

2024/4/26

Implicit Variational Inference for High-Dimensional Posteriors

Advances in Neural Information Processing Systems

Anshuk Uppal

Kristoffer Stensbo-Smidt

Wouter Boomsma

Jes Frellsen

2024/2/13

Prior and Posterior Networks: A Survey on Evidential Deep Learning Methods For Uncertainty Estimation

arXiv preprint arXiv:2110.03051

Dennis Ulmer

Christian Hardmeier

Jes Frellsen

2023/3/7

Adaptive Cholesky Gaussian Processes

Simon Bartels

Kristoffer Stensbo-Smidt

Pablo Moreno-Muñoz

Wouter Boomsma

Jes Frellsen

...

2023/4/11

Internal-Coordinate Density Modelling of Protein Structure: Covariance Matters

arXiv preprint arXiv:2302.13711

Marloes Arts

Jes Frellsen

Wouter Boomsma

2023/2/27

Learning energy-based models by self-normalising the likelihood

Hugo Henri Joseph Senetaire

Paul Jeha

Jes Frellsen

Pierre-Alexandre Mattei

2023/10/13

Polygonizer: An auto-regressive building delineator

arXiv preprint arXiv:2304.04048

Maxim Khomiakov

Michael Riis Andersen

Jes Frellsen

2023/4/8

Kernel-Matrix Determinant Estimates from stopped Cholesky Decomposition

Journal of Machine Learning Research

Simon Bartels

Wouter Boomsma

Jes Frellsen

Damien Garreau

2023

Creating the next generation of news experience on ekstrabladet. dk with recommender systems

Johannes Kruse

Kasper Lindskow

Michael Riis Andersen

Jes Frellsen

2023/9/14

That Label's Got Style: Handling Label Style Bias for Uncertain Image Segmentation

arXiv preprint arXiv:2303.15850

Kilian Zepf

Eike Petersen

Jes Frellsen

Aasa Feragen

2023/3/28

Explainability as statistical inference

Hugo Henri Joseph Senetaire

Damien Garreau

Jes Frellsen

Pierre-Alexandre Mattei

2023/7/3

Laplacian Segmentation Networks: Improved Epistemic Uncertainty from Spatial Aleatoric Uncertainty

arXiv preprint arXiv:2303.13123

Kilian Zepf

Selma Wanna

Marco Miani

Juston Moore

Jes Frellsen

...

2023/3/23

Learning To Generate 3d Representations of Building Roofs Using Single-View Aerial Imagery

Maxim Khomiakov

Alejandro Valverde Mahou

Alba Reinders Sánchez

Jes Frellsen

Michael Riis Andersen

2023/6/4

Model-agnostic out-of-distribution detection using combined statistical tests

Federico Bergamin

Pierre-Alexandre Mattei

Jakob Drachmann Havtorn

Hugo Senetaire

Hugo Schmutz

...

2022/5/3

Deep-significance-easy and meaningful statistical significance testing in the age of neural networks

arXiv preprint arXiv:2204.06815

Dennis Ulmer

Christian Hardmeier

Jes Frellsen

2022/4/14

Benchmarking generative latent variable models for speech

arXiv preprint arXiv:2202.12707

Jakob D Havtorn

Lasse Borgholt

Søren Hauberg

Jes Frellsen

Lars Maaløe

2022/2/22

Uphill roads to variational tightness: Monotonicity and Monte Carlo objectives

arXiv preprint arXiv:2201.10989

Pierre-Alexandre Mattei

Jes Frellsen

2022/1/26

SolarDK: A high-resolution urban solar panel image classification and localization dataset

arXiv preprint arXiv:2212.01260

Maxim Khomiakov

Julius Holbech Radzikowski

Carl Anton Schmidt

Mathias Bonde Sørensen

Mads Andersen

...

2022/12/2

deep-significance: Easy and meaningful signifcance testing in the age of neural networks

Dennis Ulmer

Christian Hardmeier

Jes Frellsen

2022

See List of Professors in Jes Frellsen University(Danmarks Tekniske Universitet)

Co-Authors

H-index: 85
Anders Krogh

Anders Krogh

Københavns Universitet

H-index: 72
Kanti Mardia

Kanti Mardia

University of Leeds

H-index: 36
Ida Moltke

Ida Moltke

Københavns Universitet

H-index: 31
Thomas Hamelryck

Thomas Hamelryck

Københavns Universitet

H-index: 30
Søren Hauberg

Søren Hauberg

Danmarks Tekniske Universitet

H-index: 27
Wouter Boomsma

Wouter Boomsma

Københavns Universitet

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