Jes Frellsen

84 papers A* 13A 8Misc 1Journal 55Unranked 7
YearRankTypeTitle / Venue / Authors
2026 J jnl
An Isotropic Approach to Efficient Uncertainty Quantification with Gradient Norms.
CoRR
Nils Grünefeld, Jes Frellsen, Christian Hardmeier
2026 J jnl
Fast Sampling for Flows and Diffusions with Lazy and Point Mass Stochastic Interpolants.
CoRR
Gabriel Damsholt, Jes Frellsen, Susanne Ditlevsen
2026 J jnl
Learning Energy-Based Models by Self-Normalising the Likelihood.
Trans. Mach. Learn. Res.
Hugo Henri Joseph Senetaire, Paul Jeha, Jes Frellsen, Pierre-Alexandre Mattei
2026 J jnl
Noise-Response Calibration: A Causal Intervention Protocol for LLM-Judges.
CoRR
Maxim Khomiakov, Jes Frellsen
2026 J jnl
Scalable physical source-to-field inference with hypernetworks.
Trans. Mach. Learn. Res.
Berian James, Stefan Pollok, Ignacio Peis, Elizabeth Louise Baker, Jes Frellsen, Rasmus Bjørk
2026 J jnl
Supervised Guidance Training for Infinite-Dimensional Diffusion Models.
CoRR
Elizabeth Louise Baker, Alexander Denker, Jes Frellsen
2025 A conf
Bayesian Circular Regression with von Mises Quasi-Processes.
AISTATS
Yarden Cohen, Alexandre K. W. Navarro, Jes Frellsen, Richard E. Turner, Raziel Riemer, Ari Pakman
2025 J jnl
Debiasing Guidance for Discrete Diffusion with Sequential Monte Carlo.
CoRR
Cheuk Kit Lee, Paul Jeha, Jes Frellsen, Pietro Lio, Michael Samuel Albergo, Francisco Vargas
2025 J jnl
Exploring Bidirectional Bounds for Minimax-Training of Energy-Based Models.
Int. J. Comput. Vis.
Cong Geng, Jia Wang, Li Chen, Zhiyong Gao, Jes Frellsen, Søren Hauberg
2025 J jnl
Exploring bidirectional bounds for minimax-training of Energy-based models.
CoRR
Cong Geng, Jia Wang, Li Chen, Zhiyong Gao, Jes Frellsen, Søren Hauberg
2025 A* conf
Hyper-Transforming Latent Diffusion Models.
ICML
Ignacio Peis, Batuhan Koyuncu, Isabel Valera, Jes Frellsen
2025 J jnl
Hyper-Transforming Latent Diffusion Models.
CoRR
Ignacio Peis, Batuhan Koyuncu, Isabel Valera, Jes Frellsen
2025 A* conf
Kinetic Langevin Diffusion for Crystalline Materials Generation.
ICML
François R. J. Cornet, Federico Bergamin, Arghya Bhowmik, Juan Maria Garcia Lastra, Jes Frellsen, Mikkel N. Schmidt
2025 J jnl
Kinetic Langevin Diffusion for Crystalline Materials Generation.
CoRR
François R. J. Cornet, Federico Bergamin, Arghya Bhowmik, Juan Maria Garcia Lastra, Jes Frellsen, Mikkel N. Schmidt
2025 J jnl
Learning Energy-Based Models by Self-normalising the Likelihood.
CoRR
Hugo Senetaire, Paul Jeha, Pierre-Alexandre Mattei, Jes Frellsen
2025 A conf
Normative Alignment of Recommender Systems via Internal Label Shift.
RecSys
Johannes Kruse, Kasper Lindskow, Michael Riis Andersen, Ryotaro Shimizu, Julian J. McAuley, Pierre-Alexandre Mattei, Jes Frellsen
2025 J jnl
Zero-shot protein stability prediction by inverse folding models: a free energy interpretation.
CoRR
Jes Frellsen, Maher M. Kassem, Tone Bengtsen, Lars Olsen, Kresten Lindorff-Larsen, Jesper Ferkinghoff-Borg, Wouter Boomsma
2024 J jnl
A Continuous Relaxation for Discrete Bayesian Optimization.
CoRR
Richard Michael, Simon Bartels, Miguel González Duque, Yevgen Zainchkovskyy, Jes Frellsen, Søren Hauberg, Wouter Boomsma
2024 — conf
EB-NeRD a large-scale dataset for news recommendation.
RecSys Challenge
Johannes Kruse, Kasper Lindskow, Saikishore Kalloori, Marco Polignano, Claudio Pomo, Abhishek Srivastava, Anshuk Uppal, Michael Riis Andersen, Jes Frellsen
2024 J jnl
EB-NeRD: A Large-Scale Dataset for News Recommendation.
CoRR
Johannes Kruse, Kasper Lindskow, Saikishore Kalloori, Marco Polignano, Claudio Pomo, Abhishek Srivastava, Anshuk Uppal, Michael Riis Andersen, Jes Frellsen
2024 — conf
GAST: Geometry-Aware Structure Transformer.
WACV (Workshops)
Maxim Khomiakov, Michael Riis Andersen, Jes Frellsen
2024 A conf
GeoFormer: A Multi-Polygon Segmentation Transformer.
BMVC
Maxim Khomiakov, Michael Riis Andersen, Jes Frellsen
2024 J jnl
GeoFormer: A Multi-Polygon Segmentation Transformer.
CoRR
Maxim Khomiakov, Michael Riis Andersen, Jes Frellsen
2024 J jnl
Internal-Coordinate Density Modelling of Protein Structure: Covariance Matters.
Trans. Mach. Learn. Res.
Marloes Arts, Jes Frellsen, Wouter Boomsma
2024 — conf
Laplacian Segmentation Networks Improve Epistemic Uncertainty Quantification.
MICCAI (8)
Kilian Zepf, Selma Wanna, Marco Miani, Juston Moore, Jes Frellsen, Søren Hauberg, Frederik Warburg, Aasa Feragen
2024 J jnl
MolMiner: Transformer architecture for fragment-based autoregressive generation of molecular stories.
CoRR
Raul Ortega Ochoa, Tejs Vegge, Jes Frellsen
2024 — conf
Navigating Uncertainty in Medical Image Segmentation.
ISBI
Kilian Zepf, Jes Frellsen, Aasa Feragen
2024 J jnl
Navigating Uncertainty in Medical Image Segmentation.
CoRR
Kilian Zepf, Jes Frellsen, Aasa Feragen
2024 A conf
RecSys Challenge 2024: Balancing Accuracy and Editorial Values in News Recommendations.
RecSys
Johannes Kruse, Kasper Lindskow, Saikishore Kalloori, Marco Polignano, Claudio Pomo, Abhishek Srivastava, Anshuk Uppal, Michael Riis Andersen, Jes Frellsen
2024 J jnl
RecSys Challenge 2024: Balancing Accuracy and Editorial Values in News Recommendations.
CoRR
Johannes Kruse, Kasper Lindskow, Saikishore Kalloori, Marco Polignano, Claudio Pomo, Abhishek Srivastava, Anshuk Uppal, Michael Riis Andersen, Jes Frellsen
2024 J jnl
Scalable physical source-to-field inference with hypernetworks.
CoRR
Berian James, Stefan Pollok, Ignacio Peis, Jes Frellsen, Rasmus Bjørk
2024 J jnl
Variance reduction of diffusion model's gradients with Taylor approximation-based control variate.
CoRR
Paul Jeha, Will Grathwohl, Michael Riis Andersen, Carl Henrik Ek, Jes Frellsen
2024 J jnl
von Mises Quasi-Processes for Bayesian Circular Regression.
CoRR
Yarden Cohen, Alexandre K. W. Navarro, Jes Frellsen, Richard E. Turner, Raziel Riemer, Ari Pakman
2023 A conf
Adaptive Cholesky Gaussian Processes.
AISTATS
Simon Bartels, Kristoffer Stensbo-Smidt, Pablo Moreno-Muñoz, Wouter Boomsma, Jes Frellsen, Søren Hauberg
2023 A conf
Creating the next generation of news experience on ekstrabladet.dk with recommender systems.
RecSys
Johannes Kruse, Kasper Lindskow, Michael Riis Andersen, Jes Frellsen
2023 A* conf
Explainability as statistical inference.
ICML
Hugo Henri Joseph Senetaire, Damien Garreau, Jes Frellsen, Pierre-Alexandre Mattei
2023 A* conf
Implicit Variational Inference for High-Dimensional Posteriors.
NeurIPS
Anshuk Uppal, Kristoffer Stensbo-Smidt, Wouter Boomsma, Jes Frellsen
2023 J jnl
Implicit Variational Inference for High-Dimensional Posteriors.
CoRR
Anshuk Uppal, Kristoffer Stensbo-Smidt, Wouter K. Boomsma, Jes Frellsen
2023 J jnl
Internal-Coordinate Density Modelling of Protein Structure: Covariance Matters.
CoRR
Marloes Arts, Jes Frellsen, Wouter Boomsma
2023 J jnl
Kernel-Matrix Determinant Estimates from stopped Cholesky Decomposition.
J. Mach. Learn. Res.
Simon Bartels, Wouter Boomsma, Jes Frellsen, Damien Garreau
2023 J jnl
Laplacian Segmentation Networks: Improved Epistemic Uncertainty from Spatial Aleatoric Uncertainty.
CoRR
Kilian Zepf, Selma Wanna, Marco Miani, Juston Moore, Jes Frellsen, Søren Hauberg, Aasa Feragen, Frederik Warburg
2023 Misc conf
Learning To Generate 3d Representations of Building Roofs Using Single-View Aerial Imagery.
ICASSP
Maxim Khomiakov, Alejandro Valverde Mahou, Alba Reinders Sánchez, Jes Frellsen, Michael Riis Andersen
2023 J jnl
Learning to Generate 3D Representations of Building Roofs Using Single-View Aerial Imagery.
CoRR
Maxim Khomiakov, Alejandro Valverde Mahou, Alba Reinders Sánchez, Jes Frellsen, Michael Riis Andersen
2023 J jnl
Polygonizer: An auto-regressive building delineator.
CoRR
Maxim Khomiakov, Michael Riis Andersen, Jes Frellsen
2023 J jnl
Prior and Posterior Networks: A Survey on Evidential Deep Learning Methods For Uncertainty Estimation.
Trans. Mach. Learn. Res.
Dennis Ulmer, Christian Hardmeier, Jes Frellsen
2023 J jnl
That Label's Got Style: Handling Label Style Bias for Uncertain Image Segmentation.
CoRR
Kilian Zepf, Eike Petersen, Jes Frellsen, Aasa Feragen
2023 A* conf
That Label's got Style: Handling Label Style Bias for Uncertain Image Segmentation.
ICLR
Kilian Zepf, Eike Petersen, Jes Frellsen, Aasa Feragen
2022 J jnl
Adaptive Cholesky Gaussian Processes.
CoRR
Simon Bartels, Kristoffer Stensbo-Smidt, Pablo Moreno-Muñoz, Wouter Boomsma, Jes Frellsen, Søren Hauberg
2022 J jnl
Benchmarking Generative Latent Variable Models for Speech.
CoRR
Jakob D. Havtorn, Lasse Borgholt, Søren Hauberg, Jes Frellsen, Lars Maaløe
2022 J jnl
Explainability as statistical inference.
CoRR
Hugo Henri Joseph Senetaire, Damien Garreau, Jes Frellsen, Pierre-Alexandre Mattei
2022 — conf
Exploring Predictive Uncertainty and Calibration in NLP: A Study on the Impact of Method & Data Scarcity.
EMNLP (Findings)
Dennis Ulmer, Jes Frellsen, Christian Hardmeier
2022 J jnl
Exploring Predictive Uncertainty and Calibration in NLP: A Study on the Impact of Method & Data Scarcity.
CoRR
Dennis Ulmer, Jes Frellsen, Christian Hardmeier
2022 A* conf
How to deal with missing data in supervised deep learning?
ICLR
Niels Bruun Ipsen, Pierre-Alexandre Mattei, Jes Frellsen
2022 A conf
Model-agnostic out-of-distribution detection using combined statistical tests.
AISTATS
Federico Bergamin, Pierre-Alexandre Mattei, Jakob Drachmann Havtorn, Hugo Sénétaire, Hugo Schmutz, Lars Maaløe, Søren Hauberg, Jes Frellsen
2022 J jnl
Model-agnostic out-of-distribution detection using combined statistical tests.
CoRR
Federico Bergamin, Pierre-Alexandre Mattei, Jakob D. Havtorn, Hugo Senetaire, Hugo Schmutz, Lars Maaløe, Søren Hauberg, Jes Frellsen
2022 J jnl
SolarDK: A high-resolution urban solar panel image classification and localization dataset.
CoRR
Maxim Khomiakov, Julius Holbech Radzikowski, Carl Anton Schmidt, Mathias Bonde Sørensen, Mads Andersen, Michael Riis Andersen, Jes Frellsen
2022 J jnl
Uphill Roads to Variational Tightness: Monotonicity and Monte Carlo Objectives.
CoRR
Pierre-Alexandre Mattei, Jes Frellsen
2022 J jnl
deep-significance - Easy and Meaningful Statistical Significance Testing in the Age of Neural Networks.
CoRR
Dennis Ulmer, Christian Hardmeier, Jes Frellsen
2021 A* conf
Bounds all around: training energy-based models with bidirectional bounds.
NeurIPS
Cong Geng, Jia Wang, Zhiyong Gao, Jes Frellsen, Søren Hauberg
2021 J jnl
Bounds all around: training energy-based models with bidirectional bounds.
CoRR
Cong Geng, Jia Wang, Zhiyong Gao, Jes Frellsen, Søren Hauberg
2021 A* conf
Hierarchical VAEs Know What They Don't Know.
ICML
Jakob Drachmann Havtorn, Jes Frellsen, Søren Hauberg, Lars Maaløe
2021 J jnl
Hierarchical VAEs Know What They Don't Know.
CoRR
Jakob D. Havtorn, Jes Frellsen, Søren Hauberg, Lars Maaløe
2021 J jnl
Neural network predictions of the simulated rheological response of cement paste in the FlowCyl.
Neural Comput. Appl.
Shohreh Sheiati, Navid Ranjbar, Jes Frellsen, Elisabeth L. Skare, Rolands Cepuritis, Stefan Jacobsen, Jon Spangenberg
2021 J jnl
Rapid Risk Minimization with Bayesian Models Through Deep Learning Approximation.
CoRR
Mathias Löwe, Jes Frellsen, Per Lunnemann Hansen, Sebastian Risi
2021 J jnl
Sequential Neural Posterior and Likelihood Approximation.
CoRR
Samuel Wiqvist, Jes Frellsen, Umberto Picchini
2021 A* conf
not-MIWAE: Deep Generative Modelling with Missing not at Random Data.
ICLR
Niels Bruun Ipsen, Pierre-Alexandre Mattei, Jes Frellsen
2020 J jnl
not-MIWAE: Deep Generative Modelling with Missing not at Random Data.
CoRR
Niels Bruun Ipsen, Pierre-Alexandre Mattei, Jes Frellsen
2019 J jnl
(q, p)-Wasserstein GANs: Comparing Ground Metrics for Wasserstein GANs.
CoRR
Anton Mallasto, Jes Frellsen, Wouter Boomsma, Aasa Feragen
2019 A* conf
MIWAE: Deep Generative Modelling and Imputation of Incomplete Data Sets.
ICML
Pierre-Alexandre Mattei, Jes Frellsen
2019 A* conf
Partially Exchangeable Networks and Architectures for Learning Summary Statistics in Approximate Bayesian Computation.
ICML
Samuel Wiqvist, Pierre-Alexandre Mattei, Umberto Picchini, Jes Frellsen
2019 J jnl
Partially Exchangeable Networks and Architectures for Learning Summary Statistics in Approximate Bayesian Computation.
CoRR
Samuel Wiqvist, Pierre-Alexandre Mattei, Umberto Picchini, Jes Frellsen
2018 A* conf
Leveraging the Exact Likelihood of Deep Latent Variable Models.
NeurIPS
Pierre-Alexandre Mattei, Jes Frellsen
2018 J jnl
Leveraging the Exact Likelihood of Deep Latent Variable Models.
CoRR
Pierre-Alexandre Mattei, Jes Frellsen
2018 J jnl
missIWAE: Deep Generative Modelling and Imputation of Incomplete Data.
CoRR
Pierre-Alexandre Mattei, Jes Frellsen
2017 — conf
Comparative Study of Inference Methods for Bayesian Nonnegative Matrix Factorisation.
ECML/PKDD (1)
Thomas Brouwer, Jes Frellsen, Pietro Liò
2017 J jnl
Comparative Study of Inference Methods for Bayesian Nonnegative Matrix Factorisation.
CoRR
Thomas Brouwer, Jes Frellsen, Pietro Liò
2017 — conf
Spherical convolutions and their application in molecular modelling.
NIPS
Wouter Boomsma, Jes Frellsen
2017 A* conf
The Multivariate Generalised von Mises Distribution: Inference and Applications.
AAAI
Alexandre K. W. Navarro, Jes Frellsen, Richard E. Turner
2016 A conf
Bayesian Generalised Ensemble Markov Chain Monte Carlo.
AISTATS
Jes Frellsen, Ole Winther, Zoubin Ghahramani, Jesper Ferkinghoff-Borg
2016 J jnl
Fast Bayesian Non-Negative Matrix Factorisation and Tri-Factorisation.
CoRR
Thomas Brouwer, Jes Frellsen, Pietro Liò
2014 J jnl
Adaptable probabilistic mapping of short reads using position specific scoring matrices.
BMC Bioinform.
Peter Kerpedjiev, Jes Frellsen, Stinus Lindgreen, Anders Krogh
2013 J jnl
PHAISTOS: A framework for Markov chain Monte Carlo simulation and inference of protein structure.
J. Comput. Chem.
Wouter Boomsma, Jes Frellsen, Tim Harder, Sandro Bottaro, Kristoffer E. Johansson, Pengfei Tian, Kasper Stovgaard, Christian Andreetta, Simon Olsson, Jan B. Valentin, Lubomir D. Antonov, Anders S. Christensen, Mikael Borg, Jan H. Jensen, Kresten Lindorff-Larsen, Jesper Ferkinghoff-Borg, Thomas Hamelryck
2010 J jnl
Beyond rotamers: a generative, probabilistic model of side chains in proteins.
BMC Bioinform.
Tim Harder, Wouter Boomsma, Martin Paluszewski, Jes Frellsen, Kristoffer E. Johansson, Thomas Hamelryck
2009 J jnl
A Probabilistic Model of RNA Conformational Space.
PLoS Comput. Biol.
Jes Frellsen, Ida Moltke, Martin Thiim, Kanti V. Mardia, Jesper Ferkinghoff-Borg, Thomas Hamelryck