Ole Winther - RankMe

167 papers A* 19A 5B 6Misc 1Journal 106Unranked 30

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Protein Language Model Embeddings Improve Generalization of Implicit Transfer Operators. CoRR Panagiotis Antoniadis, Beatrice Pavesi, Simon Olsson, Ole Winther
2025	J	`jnl`	Bi-Axial Transformers: Addressing the Increasing Complexity of EHR Classification. CoRR Rachael DeVries, Casper Christensen, Marie Lisandra Zepeda Mendoza, Ole Winther
2025	J	`jnl`	Few-shot Protein Fitness Prediction via In-context Learning and Test-time Training. CoRR Felix Teufel, Aaron Kollasch, Yining Huang, Ole Winther, Kevin K. Yang, Pascal Notin, Debora S. Marks
2025	J	`jnl`	NetStart 2.0: prediction of eukaryotic translation initiation sites using a protein language model. BMC Bioinform. Line Sandvad Nielsen, Anders Gorm Pedersen, Ole Winther, Henrik Nielsen
2025	J	`jnl`	Temporal Variational Implicit Neural Representations. CoRR Batuhan Koyuncu, Rachael DeVries, Ole Winther, Isabel Valera
2025	J	`jnl`	Towards Self-Supervised Foundation Models for Critical Care Time Series. CoRR Katja Naasunnguaq Jagd, Rachael DeVries, Ole Winther
2024	A*	`conf`	BEND: Benchmarking DNA Language Models on Biologically Meaningful Tasks. ICLR Frederikke Isa Marin, Felix Teufel, Marc Horlacher, Dennis Madsen, Dennis Pultz, Ole Winther, Wouter Boomsma
2024	J	`jnl`	Can large language models reason about medical questions? Patterns Valentin Liévin, Christoffer Egeberg Hother, Andreas Geert Motzfeldt, Ole Winther
2024	J	`jnl`	DeepLocRNA: an interpretable deep learning model for predicting RNA subcellular localization with domain-specific transfer-learning. Bioinform. Jun Wang, Marc Horlacher, Lixin Cheng, Ole Winther
2024	A*	`conf`	DiffEnc: Variational Diffusion with a Learned Encoder. ICLR Beatrix Miranda Ginn Nielsen, Anders Christensen, Andrea Dittadi, Ole Winther
2024	J	`jnl`	Generative Diffusion Models for Sequential Recommendations. CoRR Sharare Zolghadr, Ole Winther, Paul Jeha
2024	—	`conf`	Geometry Fidelity for Spherical Images. ECCV (80) Anders Christensen, Nooshin Mojab, Khushman Patel, Karan Ahuja, Zeynep Akata, Ole Winther, Mar González-Franco, Andrea Colaco
2024	J	`jnl`	Geometry Fidelity for Spherical Images. CoRR Anders Christensen, Nooshin Mojab, Khushman Patel, Karan Ahuja, Zeynep Akata, Ole Winther, Mar González-Franco, Andrea Colaco
2024	J	`jnl`	Predicting the subcellular location of prokaryotic proteins with DeepLocPro. Bioinform. Jaime Moreno, Henrik Nielsen, Ole Winther, Felix Teufel
2023	J	`jnl`	Addressing caveats of neural persistence with deep graph persistence. CoRR Leander Girrbach, Anders Christensen, Ole Winther, Zeynep Akata, A. Sophia Koepke
2023	J	`jnl`	Addressing caveats of neural persistence with deep graph persistence. Trans. Mach. Learn. Res. Leander Girrbach, Anders Christensen, Ole Winther, Zeynep Akata, A. Sophia Koepke
2023	A*	`conf`	Aligning Optimization Trajectories with Diffusion Models for Constrained Design Generation. NeurIPS Giorgio Giannone, Akash Srivastava, Ole Winther, Faez Ahmed
2023	J	`jnl`	Aligning Optimization Trajectories with Diffusion Models for Constrained Design Generation. CoRR Giorgio Giannone, Akash Srivastava, Ole Winther, Faez Ahmed
2023	J	`jnl`	BEND: Benchmarking DNA Language Models on biologically meaningful tasks. CoRR Frederikke Isa Marin, Felix Teufel, Marc Horlacher, Dennis Madsen, Dennis Pultz, Ole Winther, Wouter Boomsma
2023	J	`jnl`	Coherent energy and force uncertainty in deep learning force fields. CoRR Peter Bjørn Jørgensen, Jonas Busk, Ole Winther, Mikkel N. Schmidt
2023	J	`jnl`	DeepPeptide predicts cleaved peptides in proteins using conditional random fields. Bioinform. Felix Teufel, Jan C. Refsgaard, Christian T. Madsen, Carsten Stahlhut, Mads Grønborg, Ole Winther, Dennis Madsen
2023	J	`jnl`	Deorphanizing Peptides Using Structure Prediction. J. Chem. Inf. Model. Felix Teufel, Jan C. Refsgaard, Marina A. Kasimova, Kristine K. Deibler, Christian T. Madsen, Carsten Stahlhut, Mads Grønborg, Ole Winther, Dennis Madsen
2023	J	`jnl`	DermX: An end-to-end framework for explainable automated dermatological diagnosis. Medical Image Anal. Raluca Jalaboi, Frederik Faye, Mauricio Orbes-Arteaga, Dan Richter Jørgensen, Ole Winther, Alfiia Galimzianova
2023	J	`jnl`	Dermatological Diagnosis Explainability Benchmark for Convolutional Neural Networks. CoRR Raluca Jalaboi, Ole Winther, Alfiia Galimzianova
2023	J	`jnl`	DiffEnc: Variational Diffusion with a Learned Encoder. CoRR Beatrix M. G. Nielsen, Anders Christensen, Andrea Dittadi, Ole Winther
2023	J	`jnl`	Graph Neural Network Interatomic Potential Ensembles with Calibrated Aleatoric and Epistemic Uncertainty on Energy and Forces. CoRR Jonas Busk, Mikkel N. Schmidt, Ole Winther, Tejs Vegge, Peter Bjørn Jørgensen
2023	A*	`conf`	Image-free Classifier Injection for Zero-Shot Classification. ICCV Anders Christensen, Massimiliano Mancini, A. Sophia Koepke, Ole Winther, Zeynep Akata
2023	J	`jnl`	Image-free Classifier Injection for Zero-Shot Classification. CoRR Anders Christensen, Massimiliano Mancini, A. Sophia Koepke, Ole Winther, Zeynep Akata
2023	A*	`conf`	Implicit Transfer Operator Learning: Multiple Time-Resolution Models for Molecular Dynamics. NeurIPS Mathias Schreiner, Ole Winther, Simon Olsson
2023	J	`jnl`	RNA trafficking and subcellular localization - a review of mechanisms, experimental and predictive methodologies. Briefings Bioinform. Jun Wang, Marc Horlacher, Lixin Cheng, Ole Winther
2023	J	`jnl`	ThoughtSource: A central hub for large language model reasoning data. CoRR Simon Ott, Konstantin Hebenstreit, Valentin Liévin, Christoffer Egeberg Hother, Milad Moradi, Maximilian Mayrhauser, Robert Praas, Ole Winther, Matthias Samwald
2023	A*	`conf`	Unifying Molecular and Textual Representations via Multi-task Language Modelling. ICML Dimitrios Christofidellis, Giorgio Giannone, Jannis Born, Ole Winther, Teodoro Laino, Matteo Manica
2023	J	`jnl`	Unifying Molecular and Textual Representations via Multi-task Language Modelling. CoRR Dimitrios Christofidellis, Giorgio Giannone, Jannis Born, Ole Winther, Teodoro Laino, Matteo Manica
2023	A*	`conf`	Variational Open-Domain Question Answering. ICML Valentin Liévin, Andreas Geert Motzfeldt, Ida Riis Jensen, Ole Winther
2022	J	`jnl`	Calibrated uncertainty for molecular property prediction using ensembles of message passing neural networks. Mach. Learn. Sci. Technol. Jonas Busk, Peter Bjørn Jørgensen, Arghya Bhowmik, Mikkel N. Schmidt, Ole Winther, Tejs Vegge
2022	J	`jnl`	Can large language models reason about medical questions? CoRR Valentin Liévin, Christoffer Egeberg Hother, Andreas Geert Motzfeldt, Ole Winther
2022	J	`jnl`	DeepLoc 2.0: multi-label subcellular localization prediction using protein language models. Nucleic Acids Res. Vineet Thumuluri, José Juan Almagro Armenteros, Alexander Rosenberg Johansen, Henrik Nielsen, Ole Winther
2022	J	`jnl`	DermX: an end-to-end framework for explainable automated dermatological diagnosis. CoRR Raluca Jalaboi, Frederik Faye, Mauricio Orbes-Arteaga, Dan Richter Jørgensen, Ole Winther, Alfiia Galimzianova
2022	J	`jnl`	Explainable Image Quality Assessments in Teledermatological Photography. CoRR Raluca Jalaboi, Ole Winther, Alfiia Galimzianova
2022	J	`jnl`	Few-Shot Diffusion Models. CoRR Giorgio Giannone, Didrik Nielsen, Ole Winther
2022	A*	`conf`	Generalization and Robustness Implications in Object-Centric Learning. ICML Andrea Dittadi, Samuele S. Papa, Michele De Vita, Bernhard Schölkopf, Ole Winther, Francesco Locatello
2022	J	`jnl`	Image Super-Resolution With Deep Variational Autoencoders. CoRR Darius Chira, Ilian Haralampiev, Ole Winther, Andrea Dittadi, Valentin Liévin
2022	—	`conf`	Image Super-Resolution with Deep Variational Autoencoders. ECCV Workshops (2) Darius Chira, Ilian Haralampiev, Ole Winther, Andrea Dittadi, Valentin Liévin
2022	J	`jnl`	Inductive Biases for Object-Centric Representations in the Presence of Complex Textures. CoRR Samuele Papa, Ole Winther, Andrea Dittadi
2022	J	`jnl`	NetSurfP-3.0: accurate and fast prediction of protein structural features by protein language models and deep learning. Nucleic Acids Res. Magnus Haraldson Høie, Erik Nicolas Kiehl, Bent Petersen, Morten Nielsen, Ole Winther, Henrik Nielsen, Jeppe Hallgren, Paolo Marcatili
2022	J	`jnl`	NeuralNEB - Neural Networks can find Reaction Paths Fast. CoRR Mathias Schreiner, Arghya Bhowmik, Tejs Vegge, Ole Winther
2022	J	`jnl`	NeuralNEB - neural networks can find reaction paths fast. Mach. Learn. Sci. Technol. Mathias Schreiner, Arghya Bhowmik, Tejs Vegge, Peter Bjørn Jørgensen, Ole Winther
2022	A*	`conf`	SCHA-VAE: Hierarchical Context Aggregation for Few-Shot Generation. ICML Giorgio Giannone, Ole Winther
2022	A*	`conf`	The Role of Pretrained Representations for the OOD Generalization of RL Agents. ICLR Frederik Träuble, Andrea Dittadi, Manuel Wuthrich, Felix Widmaier, Peter Vincent Gehler, Ole Winther, Francesco Locatello, Olivier Bachem, Bernhard Schölkopf, Stefan Bauer
2022	J	`jnl`	Transition1x - a Dataset for Building Generalizable Reactive Machine Learning Potentials. CoRR Mathias Schreiner, Arghya Bhowmik, Tejs Vegge, Jonas Busk, Ole Winther
2022	J	`jnl`	Variational Open-Domain Question Answering. CoRR Valentin Liévin, Andreas Geert Motzfeldt, Ida Riis Jensen, Ole Winther
2021	J	`jnl`	Calibrated Uncertainty for Molecular Property Prediction using Ensembles of Message Passing Neural Networks. CoRR Jonas Busk, Peter Bjørn Jørgensen, Arghya Bhowmik, Mikkel N. Schmidt, Ole Winther, Tejs Vegge
2021	J	`jnl`	Generalization and Robustness Implications in Object-Centric Learning. CoRR Andrea Dittadi, Samuele Papa, Michele De Vita, Bernhard Schölkopf, Ole Winther, Francesco Locatello
2021	J	`jnl`	Hierarchical Few-Shot Generative Models. CoRR Giorgio Giannone, Ole Winther
2021	A*	`conf`	On the Transfer of Disentangled Representations in Realistic Settings. ICLR Andrea Dittadi, Frederik Träuble, Francesco Locatello, Manuel Wuthrich, Vaibhav Agrawal, Ole Winther, Stefan Bauer, Bernhard Schölkopf
2021	J	`jnl`	Representation Learning for Out-Of-Distribution Generalization in Reinforcement Learning. CoRR Andrea Dittadi, Frederik Träuble, Manuel Wüthrich, Felix Widmaier, Peter V. Gehler, Ole Winther, Francesco Locatello, Olivier Bachem, Bernhard Schölkopf, Stefan Bauer
2020	A*	`conf`	Closing the Dequantization Gap: PixelCNN as a Single-Layer Flow. NeurIPS Didrik Nielsen, Ole Winther
2020	J	`jnl`	Closing the Dequantization Gap: PixelCNN as a Single-Layer Flow. CoRR Didrik Nielsen, Ole Winther
2020	J	`jnl`	On the Transfer of Disentangled Representations in Realistic Settings. CoRR Andrea Dittadi, Frederik Träuble, Francesco Locatello, Manuel Wüthrich, Vaibhav Agrawal, Ole Winther, Stefan Bauer, Bernhard Schölkopf
2020	J	`jnl`	Optimal Variance Control of the Score Function Gradient Estimator for Importance Weighted Bounds. CoRR Valentin Liévin, Andrea Dittadi, Anders Christensen, Ole Winther
2020	A*	`conf`	Optimal Variance Control of the Score-Function Gradient Estimator for Importance-Weighted Bounds. NeurIPS Valentin Liévin, Andrea Dittadi, Anders Christensen, Ole Winther
2020	A*	`conf`	SurVAE Flows: Surjections to Bridge the Gap between VAEs and Flows. NeurIPS Didrik Nielsen, Priyank Jaini, Emiel Hoogeboom, Ole Winther, Max Welling
2020	J	`jnl`	SurVAE Flows: Surjections to Bridge the Gap between VAEs and Flows. CoRR Didrik Nielsen, Priyank Jaini, Emiel Hoogeboom, Ole Winther, Max Welling
2020	J	`jnl`	scVAE: variational auto-encoders for single-cell gene expression data. Bioinform. Christopher Heje Grønbech, Maximillian Fornitz Vording, Pascal N. Timshel, Casper Kaae Sønderby, Tune H. Pers, Ole Winther, Bonnie Berger
2019	A	`conf`	Attend, Copy, Parse End-to-end Information Extraction from Documents. ICDAR Rasmus Berg Palm, Florian Laws, Ole Winther
2019	A*	`conf`	BIVA: A Very Deep Hierarchy of Latent Variables for Generative Modeling. NeurIPS Lars Maaløe, Marco Fraccaro, Valentin Liévin, Ole Winther
2019	J	`jnl`	BIVA: A Very Deep Hierarchy of Latent Variables for Generative Modeling. CoRR Lars Maaløe, Marco Fraccaro, Valentin Liévin, Ole Winther
2019	J	`jnl`	Deconvolution of autoencoders to learn biological regulatory modules from single cell mRNA sequencing data. BMC Bioinform. Savvas Kinalis, Finn Cilius Nielsen, Ole Winther, Frederik Otzen Bagger
2019	J	`jnl`	LAVAE: Disentangling Location and Appearance. CoRR Andrea Dittadi, Ole Winther
2018	J	`jnl`	Attend, Copy, Parse - End-to-end information extraction from documents. CoRR Rasmus Berg Palm, Florian Laws, Ole Winther
2018	A	`conf`	Bayesian Structure Learning for Dynamic Brain Connectivity. AISTATS Michael Riis Andersen, Ole Winther, Lars Kai Hansen, Russell A. Poldrack, Oluwasanmi Koyejo
2018	—	`conf`	Learning to Plan from Raw Data in Grid-based Games. GCAI Andrea Dittadi, Thomas Bolander, Ole Winther
2018	A*	`conf`	Recurrent Relational Networks. NeurIPS Rasmus Berg Palm, Ulrich Paquet, Ole Winther
2017	—	`conf`	A Disentangled Recognition and Nonlinear Dynamics Model for Unsupervised Learning. NIPS Marco Fraccaro, Simon Kamronn, Ulrich Paquet, Ole Winther
2017	J	`jnl`	A Disentangled Recognition and Nonlinear Dynamics Model for Unsupervised Learning. CoRR Marco Fraccaro, Simon Kamronn, Ulrich Paquet, Ole Winther
2017	J	`jnl`	An introduction to deep learning on biological sequence data: examples and solutions. Bioinform. Vanessa Isabell Jurtz, Alexander Rosenberg Johansen, Morten Nielsen, José Juan Almagro Armenteros, Henrik Nielsen, Casper Kaae Sønderby, Ole Winther, Søren Kaae Sønderby
2017	J	`jnl`	Bayesian Inference for Spatio-temporal Spike-and-Slab Priors. J. Mach. Learn. Res. Michael Riis Andersen, Aki Vehtari, Ole Winther, Lars Kai Hansen
2017	A	`conf`	CloudScan - A Configuration-Free Invoice Analysis System Using Recurrent Neural Networks. ICDAR Rasmus Berg Palm, Ole Winther, Florian Laws
2017	J	`jnl`	CloudScan - A configuration-free invoice analysis system using recurrent neural networks. CoRR Rasmus Berg Palm, Ole Winther, Florian Laws
2017	—	`conf`	Deep Recurrent Conditional Random Field Network for Protein Secondary Prediction. BCB Alexander Rosenberg Johansen, Casper Kaae Sønderby, Søren Kaae Sønderby, Ole Winther
2017	J	`jnl`	DeepLoc: prediction of protein subcellular localization using deep learning. Bioinform. José Juan Almagro Armenteros, Casper Kaae Sønderby, Søren Kaae Sønderby, Henrik Nielsen, Ole Winther
2017	J	`jnl`	DeepLoc: prediction of protein subcellular localization using deep learning. Bioinform. José Juan Almagro Armenteros, Casper Kaae Sønderby, Søren Kaae Sønderby, Henrik Nielsen, Ole Winther
2017	J	`jnl`	Dynamical Functional Theory for Compressed Sensing. CoRR Burak Çakmak, Manfred Opper, Ole Winther, Bernard H. Fleury
2017	B	`conf`	Dynamical functional theory for compressed sensing. ISIT Burak Çakmak, Manfred Opper, Ole Winther, Bernard H. Fleury
2017	—	`conf`	End-to-End Information Extraction without Token-Level Supervision. SCNLP@EMNLP 2017 Rasmus Berg Palm, Dirk Hovy, Florian Laws, Ole Winther
2017	J	`jnl`	End-to-End Information Extraction without Token-Level Supervision. CoRR Rasmus Berg Palm, Dirk Hovy, Florian Laws, Ole Winther
2017	J	`jnl`	Gaussian process based independent analysis for temporal source separation in fMRI. NeuroImage Ditte Høvenhoff Hald, Ricardo Henao, Ole Winther
2017	—	`conf`	Hash Embeddings for Efficient Word Representations. NIPS Dan Svenstrup, Jonas Meinertz Hansen, Ole Winther
2017	J	`jnl`	Hash Embeddings for Efficient Word Representations. CoRR Dan Svenstrup, Jonas Meinertz Hansen, Ole Winther
2017	J	`jnl`	Recurrent Relational Networks for Complex Relational Reasoning. CoRR Rasmus Berg Palm, Ulrich Paquet, Ole Winther
2017	J	`jnl`	Semi-Supervised Generation with Cluster-aware Generative Models. CoRR Lars Maaløe, Marco Fraccaro, Ole Winther
2016	A*	`conf`	Autoencoding beyond pixels using a learned similarity metric. ICML Anders Boesen Lindbo Larsen, Søren Kaae Sønderby, Hugo Larochelle, Ole Winther
2016	A*	`conf`	Auxiliary Deep Generative Models. ICML Lars Maaløe, Casper Kaae Sønderby, Søren Kaae Sønderby, Ole Winther
2016	J	`jnl`	Auxiliary Deep Generative Models. CoRR Lars Maaløe, Casper Kaae Sønderby, Søren Kaae Sønderby, Ole Winther
2016	A	`conf`	Bayesian Generalised Ensemble Markov Chain Monte Carlo. AISTATS Jes Frellsen, Ole Winther, Zoubin Ghahramani, Jesper Ferkinghoff-Borg
2016	J	`jnl`	Bayesian Leave-One-Out Cross-Validation Approximations for Gaussian Latent Variable Models. J. Mach. Learn. Res. Aki Vehtari, Tommi Mononen, Ville Tolvanen, Tuomas Sivula, Ole Winther
2016	J	`jnl`	BloodSpot: a database of gene expression profiles and transcriptional programs for healthy and malignant haematopoiesis. Nucleic Acids Res. Frederik Otzen Bagger, Damir Sasivarevic, Sina Hadi Sohi, Linea Gøricke Laursen, Sachin Pundhir, Casper Kaae Sønderby, Ole Winther, Nicolas Rapin, Bo T. Porse
2016	J	`jnl`	How to Train Deep Variational Autoencoders and Probabilistic Ladder Networks. CoRR Casper Kaae Sønderby, Tapani Raiko, Lars Maaløe, Søren Kaae Sønderby, Ole Winther
2016	A*	`conf`	Indexable Probabilistic Matrix Factorization for Maximum Inner Product Search. AAAI Marco Fraccaro, Ulrich Paquet, Ole Winther
2016	—	`conf`	Ladder Variational Autoencoders. NIPS Casper Kaae Sønderby, Tapani Raiko, Lars Maaløe, Søren Kaae Sønderby, Ole Winther
2016	J	`jnl`	Neural Machine Translation with Characters and Hierarchical Encoding. CoRR Alexander Rosenberg Johansen, Jonas Meinertz Hansen, Elias Khazen Obeid, Casper Kaae Sønderby, Ole Winther
2016	J	`jnl`	Self-Averaging Expectation Propagation. CoRR Burak Çakmak, Manfred Opper, Bernard H. Fleury, Ole Winther
2016	—	`conf`	Sequential Neural Models with Stochastic Layers. NIPS Marco Fraccaro, Søren Kaae Sønderby, Ulrich Paquet, Ole Winther
2016	J	`jnl`	Sequential Neural Models with Stochastic Layers. CoRR Marco Fraccaro, Søren Kaae Sønderby, Ulrich Paquet, Ole Winther
2015	J	`jnl`	A Theory of Solving TAP Equations for Ising Models with General Invariant Random Matrices. CoRR Manfred Opper, Burak Çakmak, Ole Winther
2015	J	`jnl`	Autoencoding beyond pixels using a learned similarity metric. CoRR Anders Boesen Lindbo Larsen, Søren Kaae Sønderby, Ole Winther
2015	—	`conf`	Convolutional LSTM Networks for Subcellular Localization of Proteins. AlCoB Søren Kaae Sønderby, Casper Kaae Sønderby, Henrik Nielsen, Ole Winther
2015	J	`jnl`	Convolutional LSTM Networks for Subcellular Localization of Proteins. CoRR Søren Kaae Sønderby, Casper Kaae Sønderby, Henrik Nielsen, Ole Winther
2015	J	`jnl`	Deep Belief Nets for Topic Modeling. CoRR Lars Maaloe, Morten Arngren, Ole Winther
2015	J	`jnl`	Recurrent Spatial Transformer Networks. CoRR Søren Kaae Sønderby, Casper Kaae Sønderby, Lars Maaløe, Ole Winther
2015	J	`jnl`	S-AMP for Non-linear Observation Models. CoRR Burak Çakmak, Ole Winther, Bernard H. Fleury
2015	B	`conf`	S-AMP for non-linear observation models. ISIT Burak Çakmak, Ole Winther, Bernard H. Fleury
2014	—	`conf`	Applications of expectation maximization algorithm for coherent optical communication. EUSIPCO Darko Zibar, Ole Winther, Robert Borkowski, Idelfonso Tafur Monroy, Luis Henrique Hecker de Carvalho, Júlio Oliveira
2014	—	`conf`	Bayesian Inference for Structured Spike and Slab Priors. NIPS Michael Riis Andersen, Ole Winther, Lars Kai Hansen
2014	J	`jnl`	Comparison of Neural Network Error Measures for Simulation of Slender Marine Structures. J. Appl. Math. Niels H. Christiansen, Per Erlend Torbergsen Voie, Ole Winther, Jan Høgsberg
2014	—	`conf`	Model Selection in Data Analysis Competitions. MetaSel@ECAI David Kofoed Wind, Ole Winther
2014	J	`jnl`	Protein Secondary Structure Prediction with Long Short Term Memory Networks. CoRR Søren Kaae Sønderby, Ole Winther
2014	J	`jnl`	S-AMP: Approximate Message Passing for General Matrix Ensembles. CoRR Burak Çakmak, Ole Winther, Bernard H. Fleury
2014	B	`conf`	S-AMP: Approximate message passing for general matrix ensembles. ITW Burak Çakmak, Ole Winther, Bernard H. Fleury
2013	J	`jnl`	FindZebra: A search engine for rare diseases CoRR Radu Dragusin, Paula Petcu, Christina Lioma, Birger Larsen, Henrik Jørgensen, Ingemar J. Cox, Lars Kai Hansen, Peter Ingwersen, Ole Winther
2013	J	`jnl`	FindZebra: A search engine for rare diseases. Int. J. Medical Informatics Radu Dragusin, Paula Petcu, Christina Lioma, Birger Larsen, Henrik Jørgensen, Ingemar J. Cox, Lars Kai Hansen, Peter Ingwersen, Ole Winther
2013	J	`jnl`	HemaExplorer: a database of mRNA expression profiles in normal and malignant haematopoiesis. Nucleic Acids Res. Frederik Otzen Bagger, Nicolas Rapin, Kim Theilgaard-Mönch, Bogumil Kaczkowski, Lina A. Thoren, Johan Jendholm, Ole Winther, Bo T. Porse
2013	J	`jnl`	Perturbative corrections for approximate inference in Gaussian latent variable models. J. Mach. Learn. Res. Manfred Opper, Ulrich Paquet, Ole Winther
2012	J	`jnl`	A hierarchical model for ordinal matrix factorization. Stat. Comput. Ulrich Paquet, Blaise Thomson, Ole Winther
2012	J	`jnl`	Predictive active set selection methods for Gaussian processes. Neurocomputing Ricardo Henao, Ole Winther
2011	Misc	`conf`	Rare Disease Diagnosis as an Information Retrieval Task. ICTIR Radu Dragusin, Paula Petcu, Christina Lioma, Birger Larsen, Henrik Jørgensen, Ole Winther
2011	J	`jnl`	Simultaneous EEG Source and Forward Model Reconstruction (SOFOMORE) Using a Hierarchical Bayesian Approach. J. Signal Process. Syst. Carsten Stahlhut, Morten Mørup, Ole Winther, Lars Kai Hansen
2011	J	`jnl`	Sparse Linear Identifiable Multivariate Modeling. J. Mach. Learn. Res. Ricardo Henao, Ole Winther
2010	J	`jnl`	Computing the minimum-phase filter using the QL-factorization. IEEE Trans. Signal Process. Morten Hansen, Lars P. B. Christensen, Ole Winther
2010	J	`jnl`	Multivariate Hawkes process models of the occurrence of regulatory elements. BMC Bioinform. Lisbeth Carstensen, Albin Sandelin, Ole Winther, Niels Richard Hansen
2009	—	`conf`	Bayesian Non-negative Matrix Factorization. ICA Mikkel N. Schmidt, Ole Winther, Lars Kai Hansen
2009	—	`conf`	Bayesian Sparse Factor Models and DAGs Inference and Comparison. NIPS Ricardo Henao, Ole Winther
2009	J	`jnl`	Discovery of Regulatory Elements is Improved by a Discriminatory Approach. PLoS Comput. Biol. Eivind Valen, Albin Sandelin, Ole Winther, Anders Krogh
2009	J	`jnl`	Perturbation Corrections in Approximate Inference: Mixture Modelling Applications. J. Mach. Learn. Res. Ulrich Paquet, Ole Winther, Manfred Opper
2009	—	`conf`	Sofomore: Combined EEG Source and Forward Model Reconstruction. ISBI Carsten Stahlhut, Morten Mørup, Ole Winther, Lars Kai Hansen
2008	J	`jnl`	BayesMD: Flexible Biological Modeling for Motif Discovery. J. Comput. Biol. Man-Hung Eric Tang, Anders Krogh, Ole Winther
2008	—	`conf`	Improving on Expectation Propagation. NIPS Manfred Opper, Ulrich Paquet, Ole Winther
2008	J	`jnl`	JASPAR, the open access database of transcription factor-binding profiles: new content and tools in the 2008 update. Nucleic Acids Res. Jan Christian Bryne, Eivind Valen, Man-Hung Eric Tang, Troels Torben Marstrand, Ole Winther, Isabelle da Piedade, Anders Krogh, Boris Lenhard, Albin Sandelin
2007	J	`jnl`	Bayesian independent component analysis: Variational methods and non-negative decompositions. Digit. Signal Process. Ole Winther, Kaare Brandt Petersen
2007	J	`jnl`	Flexible and efficient implementations of Bayesian independent component analysis. Neurocomputing Ole Winther, Kaare Brandt Petersen
2007	B	`conf`	On Sphere Detection and Minimum-Phase Prefiltered Reduced-State Sequence Estimation. GLOBECOM Morten Hansen, Ole Winther, Lars P. B. Christensen
2007	J	`jnl`	Particle Filter Inference in an Articulatory-Based Speech Model. IEEE Signal Process. Lett. Thomas Beierholm, Ole Winther
2007	A	`conf`	Semi-Supervised Mean Fields. AISTATS Fei Wang, Shijun Wang, Changshui Zhang, Ole Winther
2006	J	`jnl`	Robust multi-scale clustering of large DNA microarray datasets with the consensus algorithm. Bioinform. Thomas Grotkjær, Ole Winther, Birgitte Regenberg, Jens Nielsen, Lars Kai Hansen
2005	J	`jnl`	Expectation Consistent Approximate Inference. J. Mach. Learn. Res. Manfred Opper, Ole Winther
2005	J	`jnl`	On the Slow Convergence of EM and VBEM in Low-Noise Linear Models. Neural Comput. Kaare Brandt Petersen, Ole Winther, Lars Kai Hansen
2005	—	`conf`	The EM algorithm in independent component analysis. ICASSP (5) Kaare Brandt Petersen, Ole Winther
2004	B	`conf`	Approximate Inference in Probabilistic Models. ALT Manfred Opper, Ole Winther
2004	—	`conf`	Expectation Consistent Free Energies for Approximate Inference. NIPS Manfred Opper, Ole Winther
2004	—	`conf`	Low complexity Bayesian single channel source separation. ICASSP (5) Thomas Beierholm, Brian Dam Pedersen, Ole Winther
2003	J	`jnl`	Tractable inference for probabilistic data models. Complex. Lehel Csató, Manfred Opper, Ole Winther
2003	—	`conf`	Variational Linear Response. NIPS Manfred Opper, Ole Winther
2002	J	`jnl`	Analysis of functional neuroimages using ICA with adaptive binary sources. Neurocomputing Pedro A. d. F. R. Højen-Sørensen, Ole Winther, Lars Kai Hansen
2002	—	`conf`	Incremental Gaussian Processes. NIPS Joaquin Quiñonero Candela, Ole Winther
2002	—	`conf`	Independent component analysis for understanding multimedia content. NNSP Thomas Kolenda, Lars Kai Hansen, Jan Larsen, Ole Winther
2002	J	`jnl`	Mean-Field Approaches to Independent Component Analysis. Neural Comput. Pedro A. d. F. R. Højen-Sørensen, Ole Winther, Lars Kai Hansen
2001	—	`conf`	TAP Gibbs Free Energy, Belief Propagation and Sparsity. NIPS Lehel Csató, Manfred Opper, Ole Winther
2000	—	`conf`	Computing with Finite and Infinite Networks. NIPS Ole Winther
2000	—	`conf`	Ensemble Learning and Linear Response Theory for ICA. NIPS Pedro A. d. F. R. Højen-Sørensen, Ole Winther, Lars Kai Hansen
2000	J	`jnl`	Gaussian Processes for Classification: Mean-Field Algorithms. Neural Comput. Manfred Opper, Ole Winther
1999	—	`conf`	Efficient Approaches to Gaussian Process Classification. NIPS Lehel Csató, Ernest Fokoué, Manfred Opper, Bernhard Schottky, Ole Winther
1998	—	`conf`	Mean Field Methods for Classification with Gaussian Processes. NIPS Manfred Opper, Ole Winther
1997	B	`conf`	Bayesian online learning in the perceptron. ESANN Ole Winther, Sara A. Solla
1996	—	`conf`	A Mean Field Algorithm for Bayes Learning in Large Feed-forward Neural Networks. NIPS Manfred Opper, Ole Winther
1996	—	`conf`	The Effect of Correlated Input Data on the Dynamics of Learning. NIPS Søren Halkjær, Ole Winther
1993	J	`jnl`	A Quantitative Study Of Pruning By Optimal Brain Damage. Int. J. Neural Syst. Jan Gorodkin, Lars Kai Hansen, Anders Krogh, Claus Svarer, Ole Winther
1993	J	`jnl`	Neural Networks and Cellular Automata Complexity. Complex Syst. Jan Gorodkin, Allan Sørensen, Ole Winther