Jes Frellsen
20 papers · 2016–2025 · 7 conferences · across top CS/AI conferences
Achievements
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π Conference Polyglot (7) π§ Keyword Pioneer πΊοΈ Taxonomy Completionist (10) π Interdisciplinary Bridge π Academic Marathon (9)
π£
Hot Topic Early Bird
πΊοΈ
Taxonomy Completionist
(10)
π§
Keyword Pioneer
π§¬
Topic Evolution
π
Keyword Champion
π
Triple Crown
ποΈ
Keyword Collector
(75)
β‘
Prolific Year
(5)
π
Conference Pioneer
π
Century Club
(20)
π₯
Unstoppable
(5)
β
The Questioner
Conferences
ICML (6)
AISTATS (4)
NIPS (4)
ICLR (3)
EMNLP (1)
JMLR (1)
MICCAI (1)
Top co-authors
Keywords
generative model
(3)
density estimation
(2)
deep latent variable model
(2)
variational inference
(2)
gaussian process
(2)
cholesky decomposition
(2)
out-of-distribution detection
(2)
uncertainty quantification
(1)
gaussian processes
(1)
ensemble learning
(1)
markov chain monte carlo
(1)
partition function
(1)
statistical testing
(1)
exact inference
(1)
false positive rate
(1)
ising model
(1)
likelihood ratio
(1)
maximum likelihood estimation
(1)
feature importance
(1)
kernel matrix
(1)
Papers
Kinetic Langevin Diffusion for Crystalline Materials Generation
ICML 2025
Hyper-Transforming Latent Diffusion Models
ICML 2025
Bayesian Circular Regression with von Mises Quasi-Processes
AISTATS 2025
Laplacian Segmentation Networks Improve Epistemic Uncertainty Quantification
MICCAI 2024
Implicit Variational Inference for High-Dimensional Posteriors
NIPS 2023
Kernel-Matrix Determinant Estimates from stopped Cholesky Decomposition
JMLR 2023
Adaptive Cholesky Gaussian Processes
AISTATS 2023
Explainability as statistical inference
ICML 2023
That Label's got Style: Handling Label Style Bias for Uncertain Image Segmentation
ICLR 2023
How to deal with missing data in supervised deep learning?
ICLR 2022
Model-agnostic out-of-distribution detection using combined statistical tests
AISTATS 2022
Exploring Predictive Uncertainty and Calibration in NLP: A Study on the Impact of Method & Data Scarcity
EMNLP 2022
Bounds all around: training energy-based models with bidirectional bounds
NIPS 2021
not-MIWAE: Deep Generative Modelling with Missing not at Random Data
ICLR 2021
Hierarchical VAEs Know What They Donβt Know
ICML 2021
MIWAE: Deep Generative Modelling and Imputation of Incomplete Data Sets
ICML 2019
Partially Exchangeable Networks and Architectures for Learning Summary Statistics in Approximate Bayesian Computation
ICML 2019
Leveraging the Exact Likelihood of Deep Latent Variable Models
NIPS 2018
Spherical convolutions and their application in molecular modelling
NIPS 2017
Bayesian Generalised Ensemble Markov Chain Monte Carlo
AISTATS 2016