Ole Winther

ORCID

Publication Activity (10 Years)

Years Active: 1993-2024
Publications (10 Years): 95

Top Venues

Publications

Anders Christensen, Nooshin Mojab, Khushman Patel, Karan Ahuja, Zeynep Akata, Ole Winther, Mar González-Franco, Andrea Colaco
Geometry Fidelity for Spherical Images. CoRR (2024)
Valentin Liévin, Christoffer Egeberg Hother, Andreas Geert Motzfeldt, Ole Winther
Can large language models reason about medical questions? Patterns 5 (3) (2024)
Frederikke Isa Marin, Felix Teufel, Marc Horlacher, Dennis Madsen, Dennis Pultz, Ole Winther, Wouter Boomsma
BEND: Benchmarking DNA Language Models on Biologically Meaningful Tasks. ICLR (2024)
Jun Wang, Marc Horlacher, Lixin Cheng, Ole Winther
DeepLocRNA: an interpretable deep learning model for predicting RNA subcellular localization with domain-specific transfer-learning. Bioinform. 40 (2) (2024)
Beatrix Miranda Ginn Nielsen, Anders Christensen, Andrea Dittadi, Ole Winther
DiffEnc: Variational Diffusion with a Learned Encoder. ICLR (2024)
Raluca Jalaboi, Frederik Faye, Mauricio Orbes-Arteaga, Dan Richter Jørgensen, Ole Winther, Alfiia Galimzianova
DermX: An end-to-end framework for explainable automated dermatological diagnosis. Medical Image Anal. 83 (2023)
Giorgio Giannone, Akash Srivastava, Ole Winther, Faez Ahmed
Aligning Optimization Trajectories with Diffusion Models for Constrained Design Generation. CoRR (2023)
Leander Girrbach, Anders Christensen, Ole Winther, Zeynep Akata, A. Sophia Koepke
Addressing caveats of neural persistence with deep graph persistence. CoRR (2023)
Simon Ott, Konstantin Hebenstreit, Valentin Liévin, Christoffer Egeberg Hother, Milad Moradi, Maximilian Mayrhauser, Robert Praas, Ole Winther, Matthias Samwald
ThoughtSource: A central hub for large language model reasoning data. CoRR (2023)
Beatrix M. G. Nielsen, Anders Christensen, Andrea Dittadi, Ole Winther
DiffEnc: Variational Diffusion with a Learned Encoder. CoRR (2023)
Mathias Schreiner, Ole Winther, Simon Olsson
Implicit Transfer Operator Learning: Multiple Time-Resolution Models for Molecular Dynamics. NeurIPS (2023)
Raluca Jalaboi, Ole Winther, Alfiia Galimzianova
Dermatological Diagnosis Explainability Benchmark for Convolutional Neural Networks. CoRR (2023)
Frederikke Isa Marin, Felix Teufel, Marc Horlacher, Dennis Madsen, Dennis Pultz, Ole Winther, Wouter Boomsma
BEND: Benchmarking DNA Language Models on biologically meaningful tasks. CoRR (2023)
Leander Girrbach, Anders Christensen, Ole Winther, Zeynep Akata, A. Sophia Koepke
Addressing caveats of neural persistence with deep graph persistence. Trans. Mach. Learn. Res. 2023 (2023)
Dimitrios Christofidellis, Giorgio Giannone, Jannis Born, Ole Winther, Teodoro Laino, Matteo Manica
Unifying Molecular and Textual Representations via Multi-task Language Modelling. CoRR (2023)
Jun Wang, Marc Horlacher, Lixin Cheng, Ole Winther
RNA trafficking and subcellular localization - a review of mechanisms, experimental and predictive methodologies. Briefings Bioinform. 24 (5) (2023)
Giorgio Giannone, Akash Srivastava, Ole Winther, Faez Ahmed
Aligning Optimization Trajectories with Diffusion Models for Constrained Design Generation. NeurIPS (2023)
Valentin Liévin, Andreas Geert Motzfeldt, Ida Riis Jensen, Ole Winther
Variational Open-Domain Question Answering. ICML (2023)
Peter Bjørn Jørgensen, Jonas Busk, Ole Winther, Mikkel N. Schmidt
Coherent energy and force uncertainty in deep learning force fields. CoRR (2023)
Jonas Busk, Mikkel N. Schmidt, Ole Winther, Tejs Vegge, Peter Bjørn Jørgensen
Graph Neural Network Interatomic Potential Ensembles with Calibrated Aleatoric and Epistemic Uncertainty on Energy and Forces. CoRR (2023)
Anders Christensen, Massimiliano Mancini, A. Sophia Koepke, Ole Winther, Zeynep Akata
Image-free Classifier Injection for Zero-Shot Classification. ICCV (2023)
Felix Teufel, Jan C. Refsgaard, Marina A. Kasimova, Kristine K. Deibler, Christian T. Madsen, Carsten Stahlhut, Mads Grønborg, Ole Winther, Dennis Madsen
Deorphanizing Peptides Using Structure Prediction. J. Chem. Inf. Model. 63 (9) (2023)
Felix Teufel, Jan C. Refsgaard, Christian T. Madsen, Carsten Stahlhut, Mads Grønborg, Ole Winther, Dennis Madsen
DeepPeptide predicts cleaved peptides in proteins using conditional random fields. Bioinform. 39 (10) (2023)
Dimitrios Christofidellis, Giorgio Giannone, Jannis Born, Ole Winther, Teodoro Laino, Matteo Manica
Unifying Molecular and Textual Representations via Multi-task Language Modelling. ICML (2023)
Anders Christensen, Massimiliano Mancini, A. Sophia Koepke, Ole Winther, Zeynep Akata
Image-free Classifier Injection for Zero-Shot Classification. CoRR (2023)
Samuele Papa, Ole Winther, Andrea Dittadi
Inductive Biases for Object-Centric Representations in the Presence of Complex Textures. CoRR (2022)
Mathias Schreiner, Arghya Bhowmik, Tejs Vegge, Jonas Busk, Ole Winther
Transition1x - a Dataset for Building Generalizable Reactive Machine Learning Potentials. CoRR (2022)
Jonas Busk, Peter Bjørn Jørgensen, Arghya Bhowmik, Mikkel N. Schmidt, Ole Winther, Tejs Vegge
Calibrated uncertainty for molecular property prediction using ensembles of message passing neural networks. Mach. Learn. Sci. Technol. 3 (1) (2022)
Raluca Jalaboi, Frederik Faye, Mauricio Orbes-Arteaga, Dan Richter Jørgensen, Ole Winther, Alfiia Galimzianova
DermX: an end-to-end framework for explainable automated dermatological diagnosis. CoRR (2022)
Valentin Liévin, Christoffer Egeberg Hother, Ole Winther
Can large language models reason about medical questions? CoRR (2022)
Mathias Schreiner, Arghya Bhowmik, Tejs Vegge, Peter Bjørn Jørgensen, Ole Winther
NeuralNEB - neural networks can find reaction paths fast. Mach. Learn. Sci. Technol. 3 (4) (2022)
Mathias Schreiner, Arghya Bhowmik, Tejs Vegge, Ole Winther
NeuralNEB - Neural Networks can find Reaction Paths Fast. CoRR (2022)
Magnus Haraldson Høie, Erik Nicolas Kiehl, Bent Petersen, Morten Nielsen, Ole Winther, Henrik Nielsen, Jeppe Hallgren, Paolo Marcatili
NetSurfP-3.0: accurate and fast prediction of protein structural features by protein language models and deep learning. Nucleic Acids Res. 50 (W1) (2022)
Darius Chira, Ilian Haralampiev, Ole Winther, Andrea Dittadi, Valentin Liévin
Image Super-Resolution With Deep Variational Autoencoders. CoRR (2022)
Giorgio Giannone, Ole Winther
SCHA-VAE: Hierarchical Context Aggregation for Few-Shot Generation. ICML (2022)
Valentin Liévin, Andreas Geert Motzfeldt, Ida Riis Jensen, Ole Winther
Variational Open-Domain Question Answering. CoRR (2022)
Darius Chira, Ilian Haralampiev, Ole Winther, Andrea Dittadi, Valentin Liévin
Image Super-Resolution with Deep Variational Autoencoders. ECCV Workshops (2) (2022)
Andrea Dittadi, Samuele S. Papa, Michele De Vita, Bernhard Schölkopf, Ole Winther, Francesco Locatello
Generalization and Robustness Implications in Object-Centric Learning. ICML (2022)
Vineet Thumuluri, José Juan Almagro Armenteros, Alexander Rosenberg Johansen, Henrik Nielsen, Ole Winther
DeepLoc 2.0: multi-label subcellular localization prediction using protein language models. Nucleic Acids Res. 50 (W1) (2022)
Raluca Jalaboi, Ole Winther, Alfiia Galimzianova
Explainable Image Quality Assessments in Teledermatological Photography. CoRR (2022)
Frederik Träuble, Andrea Dittadi, Manuel Wuthrich, Felix Widmaier, Peter Vincent Gehler, Ole Winther, Francesco Locatello, Olivier Bachem, Bernhard Schölkopf, Stefan Bauer
The Role of Pretrained Representations for the OOD Generalization of RL Agents. ICLR (2022)
Giorgio Giannone, Didrik Nielsen, Ole Winther
Few-Shot Diffusion Models. CoRR (2022)
Andrea Dittadi, Frederik Träuble, Francesco Locatello, Manuel Wuthrich, Vaibhav Agrawal, Ole Winther, Stefan Bauer, Bernhard Schölkopf
On the Transfer of Disentangled Representations in Realistic Settings. ICLR (2021)
Andrea Dittadi, Frederik Träuble, Manuel Wüthrich, Felix Widmaier, Peter V. Gehler, Ole Winther, Francesco Locatello, Olivier Bachem, Bernhard Schölkopf, Stefan Bauer
Representation Learning for Out-Of-Distribution Generalization in Reinforcement Learning. CoRR (2021)
Andrea Dittadi, Samuele Papa, Michele De Vita, Bernhard Schölkopf, Ole Winther, Francesco Locatello
Generalization and Robustness Implications in Object-Centric Learning. CoRR (2021)
Jonas Busk, Peter Bjørn Jørgensen, Arghya Bhowmik, Mikkel N. Schmidt, Ole Winther, Tejs Vegge
Calibrated Uncertainty for Molecular Property Prediction using Ensembles of Message Passing Neural Networks. CoRR (2021)
Giorgio Giannone, Ole Winther
Hierarchical Few-Shot Generative Models. CoRR (2021)
Didrik Nielsen, Ole Winther
Closing the Dequantization Gap: PixelCNN as a Single-Layer Flow. NeurIPS (2020)
Andrea Dittadi, Frederik Träuble, Francesco Locatello, Manuel Wüthrich, Vaibhav Agrawal, Ole Winther, Stefan Bauer, Bernhard Schölkopf
On the Transfer of Disentangled Representations in Realistic Settings. CoRR (2020)
Didrik Nielsen, Ole Winther
Closing the Dequantization Gap: PixelCNN as a Single-Layer Flow. CoRR (2020)
Didrik Nielsen, Priyank Jaini, Emiel Hoogeboom, Ole Winther, Max Welling
SurVAE Flows: Surjections to Bridge the Gap between VAEs and Flows. CoRR (2020)
Didrik Nielsen, Priyank Jaini, Emiel Hoogeboom, Ole Winther, Max Welling
SurVAE Flows: Surjections to Bridge the Gap between VAEs and Flows. NeurIPS (2020)
Christopher Heje Grønbech, Maximillian Fornitz Vording, Pascal N. Timshel, Casper Kaae Sønderby, Tune H. Pers, Ole Winther, Bonnie Berger
scVAE: variational auto-encoders for single-cell gene expression data. Bioinform. 36 (16) (2020)
Valentin Liévin, Andrea Dittadi, Anders Christensen, Ole Winther
Optimal Variance Control of the Score-Function Gradient Estimator for Importance-Weighted Bounds. NeurIPS (2020)
Valentin Liévin, Andrea Dittadi, Anders Christensen, Ole Winther
Optimal Variance Control of the Score Function Gradient Estimator for Importance Weighted Bounds. CoRR (2020)
Savvas Kinalis, Finn Cilius Nielsen, Ole Winther, Frederik Otzen Bagger
Deconvolution of autoencoders to learn biological regulatory modules from single cell mRNA sequencing data. BMC Bioinform. 20 (1) (2019)
Lars Maaløe, Marco Fraccaro, Valentin Liévin, Ole Winther
BIVA: A Very Deep Hierarchy of Latent Variables for Generative Modeling. CoRR (2019)
Lars Maaløe, Marco Fraccaro, Valentin Liévin, Ole Winther
BIVA: A Very Deep Hierarchy of Latent Variables for Generative Modeling. NeurIPS (2019)
Rasmus Berg Palm, Florian Laws, Ole Winther
Attend, Copy, Parse End-to-end Information Extraction from Documents. ICDAR (2019)
Andrea Dittadi, Ole Winther
LAVAE: Disentangling Location and Appearance. CoRR (2019)
Rasmus Berg Palm, Ulrich Paquet, Ole Winther
Recurrent Relational Networks. NeurIPS (2018)
Michael Riis Andersen, Ole Winther, Lars Kai Hansen, Russell A. Poldrack, Oluwasanmi Koyejo
Bayesian Structure Learning for Dynamic Brain Connectivity. AISTATS (2018)
Rasmus Berg Palm, Florian Laws, Ole Winther
Attend, Copy, Parse - End-to-end information extraction from documents. CoRR (2018)
Andrea Dittadi, Thomas Bolander, Ole Winther
Learning to Plan from Raw Data in Grid-based Games. GCAI (2018)
Marco Fraccaro, Simon Kamronn, Ulrich Paquet, Ole Winther
A Disentangled Recognition and Nonlinear Dynamics Model for Unsupervised Learning. CoRR (2017)
Rasmus Berg Palm, Ole Winther, Florian Laws
CloudScan - A Configuration-Free Invoice Analysis System Using Recurrent Neural Networks. ICDAR (2017)
Rasmus Berg Palm, Ulrich Paquet, Ole Winther
Recurrent Relational Networks for Complex Relational Reasoning. CoRR (2017)
Rasmus Berg Palm, Ole Winther, Florian Laws
CloudScan - A configuration-free invoice analysis system using recurrent neural networks. CoRR (2017)
José Juan Almagro Armenteros, Casper Kaae Sønderby, Søren Kaae Sønderby, Henrik Nielsen, Ole Winther
DeepLoc: prediction of protein subcellular localization using deep learning. Bioinform. 33 (21) (2017)
José Juan Almagro Armenteros, Casper Kaae Sønderby, Søren Kaae Sønderby, Henrik Nielsen, Ole Winther
DeepLoc: prediction of protein subcellular localization using deep learning. Bioinform. 33 (24) (2017)
Marco Fraccaro, Simon Kamronn, Ulrich Paquet, Ole Winther
A Disentangled Recognition and Nonlinear Dynamics Model for Unsupervised Learning. NIPS (2017)
Vanessa Isabell Jurtz, Alexander Rosenberg Johansen, Morten Nielsen, José Juan Almagro Armenteros, Henrik Nielsen, Casper Kaae Sønderby, Ole Winther, Søren Kaae Sønderby
An introduction to deep learning on biological sequence data: examples and solutions. Bioinform. 33 (22) (2017)
Dan Svenstrup, Jonas Meinertz Hansen, Ole Winther
Hash Embeddings for Efficient Word Representations. CoRR (2017)
Lars Maaløe, Marco Fraccaro, Ole Winther
Semi-Supervised Generation with Cluster-aware Generative Models. CoRR (2017)
Rasmus Berg Palm, Dirk Hovy, Florian Laws, Ole Winther
End-to-End Information Extraction without Token-Level Supervision. CoRR (2017)
Rasmus Berg Palm, Dirk Hovy, Florian Laws, Ole Winther
End-to-End Information Extraction without Token-Level Supervision. SCNLP@EMNLP 2017 (2017)
Dan Svenstrup, Jonas Meinertz Hansen, Ole Winther
Hash Embeddings for Efficient Word Representations. NIPS (2017)
Burak Çakmak, Manfred Opper, Ole Winther, Bernard H. Fleury
Dynamical Functional Theory for Compressed Sensing. CoRR (2017)
Ditte Høvenhoff Hald, Ricardo Henao, Ole Winther
Gaussian process based independent analysis for temporal source separation in fMRI. NeuroImage 152 (2017)
Alexander Rosenberg Johansen, Casper Kaae Sønderby, Søren Kaae Sønderby, Ole Winther
Deep Recurrent Conditional Random Field Network for Protein Secondary Prediction. BCB (2017)
Burak Çakmak, Manfred Opper, Ole Winther, Bernard H. Fleury
Dynamical functional theory for compressed sensing. ISIT (2017)
Michael Riis Andersen, Aki Vehtari, Ole Winther, Lars Kai Hansen
Bayesian Inference for Spatio-temporal Spike-and-Slab Priors. J. Mach. Learn. Res. 18 (2017)
Lars Maaløe, Casper Kaae Sønderby, Søren Kaae Sønderby, Ole Winther
Auxiliary Deep Generative Models. CoRR (2016)
Marco Fraccaro, Ulrich Paquet, Ole Winther
Indexable Probabilistic Matrix Factorization for Maximum Inner Product Search. AAAI (2016)
Aki Vehtari, Tommi Mononen, Ville Tolvanen, Tuomas Sivula, Ole Winther
Bayesian Leave-One-Out Cross-Validation Approximations for Gaussian Latent Variable Models. J. Mach. Learn. Res. 17 (2016)
Casper Kaae Sønderby, Tapani Raiko, Lars Maaløe, Søren Kaae Sønderby, Ole Winther
Ladder Variational Autoencoders. NIPS (2016)
Burak Çakmak, Manfred Opper, Bernard H. Fleury, Ole Winther
Self-Averaging Expectation Propagation. CoRR (2016)
Anders Boesen Lindbo Larsen, Søren Kaae Sønderby, Hugo Larochelle, Ole Winther
Autoencoding beyond pixels using a learned similarity metric. ICML (2016)
Marco Fraccaro, Søren Kaae Sønderby, Ulrich Paquet, Ole Winther
Sequential Neural Models with Stochastic Layers. CoRR (2016)
Lars Maaløe, Casper Kaae Sønderby, Søren Kaae Sønderby, Ole Winther
Auxiliary Deep Generative Models. ICML (2016)
Jes Frellsen, Ole Winther, Zoubin Ghahramani, Jesper Ferkinghoff-Borg
Bayesian Generalised Ensemble Markov Chain Monte Carlo. AISTATS (2016)
Alexander Rosenberg Johansen, Jonas Meinertz Hansen, Elias Khazen Obeid, Casper Kaae Sønderby, Ole Winther
Neural Machine Translation with Characters and Hierarchical Encoding. CoRR (2016)
Casper Kaae Sønderby, Tapani Raiko, Lars Maaløe, Søren Kaae Sønderby, Ole Winther
How to Train Deep Variational Autoencoders and Probabilistic Ladder Networks. CoRR (2016)
Marco Fraccaro, Søren Kaae Sønderby, Ulrich Paquet, Ole Winther
Sequential Neural Models with Stochastic Layers. NIPS (2016)
Frederik Otzen Bagger, Damir Sasivarevic, Sina Hadi Sohi, Linea Gøricke Laursen, Sachin Pundhir, Casper Kaae Sønderby, Ole Winther, Nicolas Rapin, Bo T. Porse
BloodSpot: a database of gene expression profiles and transcriptional programs for healthy and malignant haematopoiesis. Nucleic Acids Res. 44 (Database-Issue) (2016)
Søren Kaae Sønderby, Casper Kaae Sønderby, Henrik Nielsen, Ole Winther
Convolutional LSTM Networks for Subcellular Localization of Proteins. AlCoB (2015)
Søren Kaae Sønderby, Casper Kaae Sønderby, Lars Maaløe, Ole Winther
Recurrent Spatial Transformer Networks. CoRR (2015)
Manfred Opper, Burak Çakmak, Ole Winther
A Theory of Solving TAP Equations for Ising Models with General Invariant Random Matrices. CoRR (2015)
Burak Çakmak, Ole Winther, Bernard H. Fleury
S-AMP for non-linear observation models. ISIT (2015)
Lars Maaloe, Morten Arngren, Ole Winther
Deep Belief Nets for Topic Modeling. CoRR (2015)

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Publication Activity (10 Years)

Top Topics

Top Venues

Ole Winther