Ole Winther

Orcid: 0000-0002-1966-3205

According to our database1, Ole Winther authored at least 130 papers between 1993 and 2024.

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Bibliography

2024
Can large language models reason about medical questions?
Patterns, March, 2024

DeepLocRNA: an interpretable deep learning model for predicting RNA subcellular localization with domain-specific transfer-learning.
Bioinform., February, 2024

Generative Diffusion Models for Sequential Recommendations.
CoRR, 2024

DiffEnc: Variational Diffusion with a Learned Encoder.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

BEND: Benchmarking DNA Language Models on Biologically Meaningful Tasks.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

Geometry Fidelity for Spherical Images.
Proceedings of the Computer Vision - ECCV 2024, 2024

2023
DeepPeptide predicts cleaved peptides in proteins using conditional random fields.
Bioinform., October, 2023

RNA trafficking and subcellular localization - a review of mechanisms, experimental and predictive methodologies.
Briefings Bioinform., September, 2023

Deorphanizing Peptides Using Structure Prediction.
J. Chem. Inf. Model., May, 2023

Addressing caveats of neural persistence with deep graph persistence.
Trans. Mach. Learn. Res., 2023

DermX: An end-to-end framework for explainable automated dermatological diagnosis.
Medical Image Anal., 2023

Coherent energy and force uncertainty in deep learning force fields.
CoRR, 2023

Graph Neural Network Interatomic Potential Ensembles with Calibrated Aleatoric and Epistemic Uncertainty on Energy and Forces.
CoRR, 2023

Dermatological Diagnosis Explainability Benchmark for Convolutional Neural Networks.
CoRR, 2023

ThoughtSource: A central hub for large language model reasoning data.
CoRR, 2023

Implicit Transfer Operator Learning: Multiple Time-Resolution Models for Molecular Dynamics.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Aligning Optimization Trajectories with Diffusion Models for Constrained Design Generation.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Variational Open-Domain Question Answering.
Proceedings of the International Conference on Machine Learning, 2023

Unifying Molecular and Textual Representations via Multi-task Language Modelling.
Proceedings of the International Conference on Machine Learning, 2023

Image-free Classifier Injection for Zero-Shot Classification.
Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

2022
NeuralNEB - neural networks can find reaction paths fast.
Mach. Learn. Sci. Technol., December, 2022

DeepLoc 2.0: multi-label subcellular localization prediction using protein language models.
Nucleic Acids Res., 2022

NetSurfP-3.0: accurate and fast prediction of protein structural features by protein language models and deep learning.
Nucleic Acids Res., 2022

Calibrated uncertainty for molecular property prediction using ensembles of message passing neural networks.
Mach. Learn. Sci. Technol., 2022

Explainable Image Quality Assessments in Teledermatological Photography.
CoRR, 2022

Transition1x - a Dataset for Building Generalizable Reactive Machine Learning Potentials.
CoRR, 2022

NeuralNEB - Neural Networks can find Reaction Paths Fast.
CoRR, 2022

Can large language models reason about medical questions?
CoRR, 2022

Few-Shot Diffusion Models.
CoRR, 2022

Inductive Biases for Object-Centric Representations in the Presence of Complex Textures.
CoRR, 2022

SCHA-VAE: Hierarchical Context Aggregation for Few-Shot Generation.
Proceedings of the International Conference on Machine Learning, 2022

Generalization and Robustness Implications in Object-Centric Learning.
Proceedings of the International Conference on Machine Learning, 2022

The Role of Pretrained Representations for the OOD Generalization of RL Agents.
Proceedings of the Tenth International Conference on Learning Representations, 2022

Image Super-Resolution with Deep Variational Autoencoders.
Proceedings of the Computer Vision - ECCV 2022 Workshops, 2022

2021
Hierarchical Few-Shot Generative Models.
CoRR, 2021

Representation Learning for Out-Of-Distribution Generalization in Reinforcement Learning.
CoRR, 2021

On the Transfer of Disentangled Representations in Realistic Settings.
Proceedings of the 9th International Conference on Learning Representations, 2021

2020
scVAE: variational auto-encoders for single-cell gene expression data.
Bioinform., 2020

Closing the Dequantization Gap: PixelCNN as a Single-Layer Flow.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

SurVAE Flows: Surjections to Bridge the Gap between VAEs and Flows.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Optimal Variance Control of the Score-Function Gradient Estimator for Importance-Weighted Bounds.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

2019
LAVAE: Disentangling Location and Appearance.
CoRR, 2019

Deconvolution of autoencoders to learn biological regulatory modules from single cell mRNA sequencing data.
BMC Bioinform., 2019

BIVA: A Very Deep Hierarchy of Latent Variables for Generative Modeling.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Attend, Copy, Parse End-to-end Information Extraction from Documents.
Proceedings of the 2019 International Conference on Document Analysis and Recognition, 2019

2018
Recurrent Relational Networks.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Learning to Plan from Raw Data in Grid-based Games.
Proceedings of the GCAI-2018, 2018

Bayesian Structure Learning for Dynamic Brain Connectivity.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2018

2017
Gaussian process based independent analysis for temporal source separation in fMRI.
NeuroImage, 2017

Bayesian Inference for Spatio-temporal Spike-and-Slab Priors.
J. Mach. Learn. Res., 2017

Recurrent Relational Networks for Complex Relational Reasoning.
CoRR, 2017

Semi-Supervised Generation with Cluster-aware Generative Models.
CoRR, 2017

An introduction to deep learning on biological sequence data: examples and solutions.
Bioinform., 2017

DeepLoc: prediction of protein subcellular localization using deep learning.
Bioinform., 2017

Hash Embeddings for Efficient Word Representations.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

A Disentangled Recognition and Nonlinear Dynamics Model for Unsupervised Learning.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Dynamical functional theory for compressed sensing.
Proceedings of the 2017 IEEE International Symposium on Information Theory, 2017

CloudScan - A Configuration-Free Invoice Analysis System Using Recurrent Neural Networks.
Proceedings of the 14th IAPR International Conference on Document Analysis and Recognition, 2017

End-to-End Information Extraction without Token-Level Supervision.
Proceedings of the Workshop on Speech-Centric Natural Language Processing, 2017

Deep Recurrent Conditional Random Field Network for Protein Secondary Prediction.
Proceedings of the 8th ACM International Conference on Bioinformatics, 2017

2016
BloodSpot: a database of gene expression profiles and transcriptional programs for healthy and malignant haematopoiesis.
Nucleic Acids Res., 2016

Bayesian Leave-One-Out Cross-Validation Approximations for Gaussian Latent Variable Models.
J. Mach. Learn. Res., 2016

How to Train Deep Variational Autoencoders and Probabilistic Ladder Networks.
CoRR, 2016

Neural Machine Translation with Characters and Hierarchical Encoding.
CoRR, 2016

Self-Averaging Expectation Propagation.
CoRR, 2016

Ladder Variational Autoencoders.
Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

Sequential Neural Models with Stochastic Layers.
Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

Auxiliary Deep Generative Models.
Proceedings of the 33nd International Conference on Machine Learning, 2016

Autoencoding beyond pixels using a learned similarity metric.
Proceedings of the 33nd International Conference on Machine Learning, 2016

Bayesian Generalised Ensemble Markov Chain Monte Carlo.
Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, 2016

Indexable Probabilistic Matrix Factorization for Maximum Inner Product Search.
Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence, 2016

2015
Recurrent Spatial Transformer Networks.
CoRR, 2015

A Theory of Solving TAP Equations for Ising Models with General Invariant Random Matrices.
CoRR, 2015

Deep Belief Nets for Topic Modeling.
CoRR, 2015

Autoencoding beyond pixels using a learned similarity metric.
CoRR, 2015

S-AMP for non-linear observation models.
Proceedings of the IEEE International Symposium on Information Theory, 2015

Convolutional LSTM Networks for Subcellular Localization of Proteins.
Proceedings of the Algorithms for Computational Biology, 2015

2014
Comparison of Neural Network Error Measures for Simulation of Slender Marine Structures.
J. Appl. Math., 2014

Protein Secondary Structure Prediction with Long Short Term Memory Networks.
CoRR, 2014

Bayesian Inference for Structured Spike and Slab Priors.
Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014

S-AMP: Approximate message passing for general matrix ensembles.
Proceedings of the 2014 IEEE Information Theory Workshop, 2014

Applications of expectation maximization algorithm for coherent optical communication.
Proceedings of the 22nd European Signal Processing Conference, 2014

Model Selection in Data Analysis Competitions.
Proceedings of the International Workshop on Meta-learning and Algorithm Selection co-located with 21st European Conference on Artificial Intelligence, 2014

2013
HemaExplorer: a database of mRNA expression profiles in normal and malignant haematopoiesis.
Nucleic Acids Res., 2013

Perturbative corrections for approximate inference in Gaussian latent variable models.
J. Mach. Learn. Res., 2013

FindZebra: A search engine for rare diseases.
Int. J. Medical Informatics, 2013

2012
A hierarchical model for ordinal matrix factorization.
Stat. Comput., 2012

Predictive active set selection methods for Gaussian processes.
Neurocomputing, 2012

2011
Simultaneous EEG Source and Forward Model Reconstruction (SOFOMORE) Using a Hierarchical Bayesian Approach.
J. Signal Process. Syst., 2011

Sparse Linear Identifiable Multivariate Modeling.
J. Mach. Learn. Res., 2011

Rare Disease Diagnosis as an Information Retrieval Task.
Proceedings of the Advances in Information Retrieval Theory, 2011

2010
Computing the minimum-phase filter using the QL-factorization.
IEEE Trans. Signal Process., 2010

Multivariate Hawkes process models of the occurrence of regulatory elements.
BMC Bioinform., 2010

2009
Discovery of Regulatory Elements is Improved by a Discriminatory Approach.
PLoS Comput. Biol., 2009

Perturbation Corrections in Approximate Inference: Mixture Modelling Applications.
J. Mach. Learn. Res., 2009

Bayesian Sparse Factor Models and DAGs Inference and Comparison.
Proceedings of the Advances in Neural Information Processing Systems 22: 23rd Annual Conference on Neural Information Processing Systems 2009. Proceedings of a meeting held 7-10 December 2009, 2009

Sofomore: Combined EEG Source and Forward Model Reconstruction.
Proceedings of the 2009 IEEE International Symposium on Biomedical Imaging: From Nano to Macro, Boston, MA, USA, June 28, 2009

Bayesian Non-negative Matrix Factorization.
Proceedings of the Independent Component Analysis and Signal Separation, 2009

2008
JASPAR, the open access database of transcription factor-binding profiles: new content and tools in the 2008 update.
Nucleic Acids Res., 2008

BayesMD: Flexible Biological Modeling for Motif Discovery.
J. Comput. Biol., 2008

Improving on Expectation Propagation.
Proceedings of the Advances in Neural Information Processing Systems 21, 2008

2007
Particle Filter Inference in an Articulatory-Based Speech Model.
IEEE Signal Process. Lett., 2007

Semi-Supervised Mean Fields.
Proceedings of the Eleventh International Conference on Artificial Intelligence and Statistics, 2007

Flexible and efficient implementations of Bayesian independent component analysis.
Neurocomputing, 2007

Bayesian independent component analysis: Variational methods and non-negative decompositions.
Digit. Signal Process., 2007

On Sphere Detection and Minimum-Phase Prefiltered Reduced-State Sequence Estimation.
Proceedings of the Global Communications Conference, 2007

2006
Robust multi-scale clustering of large DNA microarray datasets with the consensus algorithm.
Bioinform., 2006

2005
On the Slow Convergence of EM and VBEM in Low-Noise Linear Models.
Neural Comput., 2005

Expectation Consistent Approximate Inference.
J. Mach. Learn. Res., 2005

The EM algorithm in independent component analysis.
Proceedings of the 2005 IEEE International Conference on Acoustics, 2005

2004
Expectation Consistent Free Energies for Approximate Inference.
Proceedings of the Advances in Neural Information Processing Systems 17 [Neural Information Processing Systems, 2004

Low complexity Bayesian single channel source separation.
Proceedings of the 2004 IEEE International Conference on Acoustics, 2004

Approximate Inference in Probabilistic Models.
Proceedings of the Algorithmic Learning Theory, 15th International Conference, 2004

2003
Tractable inference for probabilistic data models.
Complex., 2003

Variational Linear Response.
Proceedings of the Advances in Neural Information Processing Systems 16 [Neural Information Processing Systems, 2003

2002
Mean-Field Approaches to Independent Component Analysis.
Neural Comput., 2002

Analysis of functional neuroimages using ICA with adaptive binary sources.
Neurocomputing, 2002

Independent component analysis for understanding multimedia content.
Proceedings of the 12th IEEE Workshop on Neural Networks for Signal Processing, 2002

Incremental Gaussian Processes.
Proceedings of the Advances in Neural Information Processing Systems 15 [Neural Information Processing Systems, 2002

2001
TAP Gibbs Free Energy, Belief Propagation and Sparsity.
Proceedings of the Advances in Neural Information Processing Systems 14 [Neural Information Processing Systems: Natural and Synthetic, 2001

2000
Gaussian Processes for Classification: Mean-Field Algorithms.
Neural Comput., 2000

Computing with Finite and Infinite Networks.
Proceedings of the Advances in Neural Information Processing Systems 13, 2000

Ensemble Learning and Linear Response Theory for ICA.
Proceedings of the Advances in Neural Information Processing Systems 13, 2000

1999
Efficient Approaches to Gaussian Process Classification.
Proceedings of the Advances in Neural Information Processing Systems 12, [NIPS Conference, Denver, Colorado, USA, November 29, 1999

1998
Mean Field Methods for Classification with Gaussian Processes.
Proceedings of the Advances in Neural Information Processing Systems 11, [NIPS Conference, Denver, Colorado, USA, November 30, 1998

1997
Bayesian online learning in the perceptron.
Proceedings of the 5th Eurorean Symposium on Artificial Neural Networks, 1997

1996
A Mean Field Algorithm for Bayes Learning in Large Feed-forward Neural Networks.
Proceedings of the Advances in Neural Information Processing Systems 9, 1996

The Effect of Correlated Input Data on the Dynamics of Learning.
Proceedings of the Advances in Neural Information Processing Systems 9, 1996

1993
A Quantitative Study Of Pruning By Optimal Brain Damage.
Int. J. Neural Syst., 1993

Neural Networks and Cellular Automata Complexity.
Complex Syst., 1993


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