Stop the war!Остановите войну!
for scientists:
Google
Google Scholar
Semantic Scholar
IA Scholar
CiteSeerX
ORCIDOle Winther
Person information
Refine list
refinements active!
zoomed in on ?? of ?? records
view refined list in
export refined list as
showing all ?? records
2020 – today
- 2022
[c51]Andrea Dittadi, Samuele S. Papa, Michele De Vita, Bernhard Schölkopf, Ole Winther, Francesco Locatello:
Generalization and Robustness Implications in Object-Centric Learning. ICML 2022: 5221-5285- [c50]Giorgio Giannone, Ole Winther:
SCHA-VAE: Hierarchical Context Aggregation for Few-Shot Generation. ICML 2022: 7550-7569 - [i39]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 abs/2202.06956 (2022) - [i38]Darius Chira, Ilian Haralampiev, Ole Winther, Andrea Dittadi, Valentin Liévin:
Image Super-Resolution With Deep Variational Autoencoders. CoRR abs/2203.09445 (2022) - [i37]Samuele Papa, Ole Winther, Andrea Dittadi:
Inductive Biases for Object-Centric Representations in the Presence of Complex Textures. CoRR abs/2204.08479 (2022) - [i36]Giorgio Giannone, Didrik Nielsen, Ole Winther:
Few-Shot Diffusion Models. CoRR abs/2205.15463 (2022) - [i35]Valentin Liévin, Christoffer Egeberg Hother, Ole Winther:
Can large language models reason about medical questions? CoRR abs/2207.08143 (2022) - [i34]Mathias Schreiner, Arghya Bhowmik, Tejs Vegge, Ole Winther:
NeuralNEB - Neural Networks can find Reaction Paths Fast. CoRR abs/2207.09971 (2022) - [i33]Mathias Schreiner, Arghya Bhowmik, Tejs Vegge, Jonas Busk, Ole Winther:
Transition1x - a Dataset for Building Generalizable Reactive Machine Learning Potentials. CoRR abs/2207.12858 (2022) - 2021
- [c49]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 - [i32]Andrea Dittadi, Samuele Papa, Michele De Vita, Bernhard Schölkopf, Ole Winther, Francesco Locatello:
Generalization and Robustness Implications in Object-Centric Learning. CoRR abs/2107.00637 (2021) - [i31]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 abs/2107.05686 (2021) - [i30]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 abs/2107.06068 (2021) - [i29]Giorgio Giannone, Ole Winther:
Hierarchical Few-Shot Generative Models. CoRR abs/2110.12279 (2021) - 2020
- [j35]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): 4415-4422 (2020) - [c48]Valentin Liévin, Andrea Dittadi, Anders Christensen, Ole Winther:
Optimal Variance Control of the Score-Function Gradient Estimator for Importance-Weighted Bounds. NeurIPS 2020 - [c47]Didrik Nielsen, Priyank Jaini, Emiel Hoogeboom, Ole Winther, Max Welling:
SurVAE Flows: Surjections to Bridge the Gap between VAEs and Flows. NeurIPS 2020 - [c46]Didrik Nielsen, Ole Winther:
Closing the Dequantization Gap: PixelCNN as a Single-Layer Flow. NeurIPS 2020 - [i28]Didrik Nielsen, Ole Winther:
Closing the Dequantization Gap: PixelCNN as a Single-Layer Flow. CoRR abs/2002.02547 (2020) - [i27]Didrik Nielsen, Priyank Jaini, Emiel Hoogeboom, Ole Winther, Max Welling:
SurVAE Flows: Surjections to Bridge the Gap between VAEs and Flows. CoRR abs/2007.02731 (2020) - [i26]Valentin Liévin, Andrea Dittadi, Anders Christensen, Ole Winther:
Optimal Variance Control of the Score Function Gradient Estimator for Importance Weighted Bounds. CoRR abs/2008.01998 (2020) - [i25]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 abs/2010.14407 (2020)
2010 – 2019
- 2019
- [j34]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): 379:1-379:9 (2019) - [c45]Rasmus Berg Palm, Florian Laws, Ole Winther:
Attend, Copy, Parse End-to-end Information Extraction from Documents. ICDAR 2019: 329-336 - [c44]Lars Maaløe, Marco Fraccaro, Valentin Liévin, Ole Winther:
BIVA: A Very Deep Hierarchy of Latent Variables for Generative Modeling. NeurIPS 2019: 6548-6558 - [i24]Lars Maaløe, Marco Fraccaro, Valentin Liévin, Ole Winther:
BIVA: A Very Deep Hierarchy of Latent Variables for Generative Modeling. CoRR abs/1902.02102 (2019) - [i23]Andrea Dittadi, Ole Winther:
LAVAE: Disentangling Location and Appearance. CoRR abs/1909.11813 (2019) - 2018
- [c43]Michael Riis Andersen, Ole Winther, Lars Kai Hansen, Russell A. Poldrack, Oluwasanmi Koyejo:
Bayesian Structure Learning for Dynamic Brain Connectivity. AISTATS 2018: 1436-1446 - [c42]Andrea Dittadi, Thomas Bolander, Ole Winther:
Learning to Plan from Raw Data in Grid-based Games. GCAI 2018: 54-67 - [c41]Rasmus Berg Palm, Ulrich Paquet, Ole Winther:
Recurrent Relational Networks. NeurIPS 2018: 3372-3382 - [i22]Rasmus Berg Palm, Florian Laws, Ole Winther:
Attend, Copy, Parse - End-to-end information extraction from documents. CoRR abs/1812.07248 (2018) - 2017
- [j33]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): 3387-3395 (2017) - [j32]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): 3685-3690 (2017) - [j31]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): 4049 (2017) - [j30]Michael Riis Andersen, Aki Vehtari, Ole Winther, Lars Kai Hansen:
Bayesian Inference for Spatio-temporal Spike-and-Slab Priors. J. Mach. Learn. Res. 18: 139:1-139:58 (2017) - [j29]Ditte Høvenhoff Hald, Ricardo Henao, Ole Winther:
Gaussian process based independent analysis for temporal source separation in fMRI. NeuroImage 152: 563-574 (2017) - [c40]Alexander Rosenberg Johansen, Casper Kaae Sønderby, Søren Kaae Sønderby, Ole Winther:
Deep Recurrent Conditional Random Field Network for Protein Secondary Prediction. BCB 2017: 73-78 - [c39]Rasmus Berg Palm, Dirk Hovy, Florian Laws, Ole Winther:
End-to-End Information Extraction without Token-Level Supervision. SCNLP@EMNLP 2017 2017: 48-52 - [c38]Rasmus Berg Palm, Ole Winther, Florian Laws:
CloudScan - A Configuration-Free Invoice Analysis System Using Recurrent Neural Networks. ICDAR 2017: 406-413 - [c37]Burak Çakmak, Manfred Opper, Ole Winther, Bernard H. Fleury:
Dynamical functional theory for compressed sensing. ISIT 2017: 2143-2147 - [c36]Marco Fraccaro, Simon Kamronn, Ulrich Paquet, Ole Winther:
A Disentangled Recognition and Nonlinear Dynamics Model for Unsupervised Learning. NIPS 2017: 3601-3610 - [c35]Dan Svenstrup, Jonas Meinertz Hansen, Ole Winther:
Hash Embeddings for Efficient Word Representations. NIPS 2017: 4928-4936 - [i21]Lars Maaløe, Marco Fraccaro, Ole Winther:
Semi-Supervised Generation with Cluster-aware Generative Models. CoRR abs/1704.00637 (2017) - [i20]Burak Çakmak, Manfred Opper, Ole Winther, Bernard H. Fleury:
Dynamical Functional Theory for Compressed Sensing. CoRR abs/1705.04284 (2017) - [i19]Rasmus Berg Palm, Dirk Hovy, Florian Laws, Ole Winther:
End-to-End Information Extraction without Token-Level Supervision. CoRR abs/1707.04913 (2017) - [i18]Rasmus Berg Palm, Ole Winther, Florian Laws:
CloudScan - A configuration-free invoice analysis system using recurrent neural networks. CoRR abs/1708.07403 (2017) - [i17]Dan Svenstrup, Jonas Meinertz Hansen, Ole Winther:
Hash Embeddings for Efficient Word Representations. CoRR abs/1709.03933 (2017) - [i16]Marco Fraccaro, Simon Kamronn, Ulrich Paquet, Ole Winther:
A Disentangled Recognition and Nonlinear Dynamics Model for Unsupervised Learning. CoRR abs/1710.05741 (2017) - [i15]Rasmus Berg Palm, Ulrich Paquet, Ole Winther:
Recurrent Relational Networks for Complex Relational Reasoning. CoRR abs/1711.08028 (2017) - 2016
- [j28]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: 103:1-103:38 (2016) - [j27]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): 917-924 (2016) - [c34]Marco Fraccaro, Ulrich Paquet, Ole Winther:
Indexable Probabilistic Matrix Factorization for Maximum Inner Product Search. AAAI 2016: 1554-1560 - [c33]Jes Frellsen, Ole Winther, Zoubin Ghahramani, Jesper Ferkinghoff-Borg:
Bayesian Generalised Ensemble Markov Chain Monte Carlo. AISTATS 2016: 408-416 - [c32]Lars Maaløe, Casper Kaae Sønderby, Søren Kaae Sønderby, Ole Winther:
Auxiliary Deep Generative Models. ICML 2016: 1445-1453 - [c31]Anders Boesen Lindbo Larsen, Søren Kaae Sønderby, Hugo Larochelle, Ole Winther:
Autoencoding beyond pixels using a learned similarity metric. ICML 2016: 1558-1566 - [c30]Marco Fraccaro, Søren Kaae Sønderby, Ulrich Paquet, Ole Winther:
Sequential Neural Models with Stochastic Layers. NIPS 2016: 2199-2207 - [c29]Casper Kaae Sønderby, Tapani Raiko, Lars Maaløe, Søren Kaae Sønderby, Ole Winther:
Ladder Variational Autoencoders. NIPS 2016: 3738-3746 - [i14]Casper Kaae Sønderby, Tapani Raiko, Lars Maaløe, Søren Kaae Sønderby, Ole Winther:
How to Train Deep Variational Autoencoders and Probabilistic Ladder Networks. CoRR abs/1602.02282 (2016) - [i13]Lars Maaløe, Casper Kaae Sønderby, Søren Kaae Sønderby, Ole Winther:
Auxiliary Deep Generative Models. CoRR abs/1602.05473 (2016) - [i12]Marco Fraccaro, Søren Kaae Sønderby, Ulrich Paquet, Ole Winther:
Sequential Neural Models with Stochastic Layers. CoRR abs/1605.07571 (2016) - [i11]Burak Çakmak, Manfred Opper, Bernard H. Fleury, Ole Winther:
Self-Averaging Expectation Propagation. CoRR abs/1608.06602 (2016) - [i10]Alexander Rosenberg Johansen, Jonas Meinertz Hansen, Elias Khazen Obeid, Casper Kaae Sønderby, Ole Winther:
Neural Machine Translation with Characters and Hierarchical Encoding. CoRR abs/1610.06550 (2016) - 2015
- [c28]Søren Kaae Sønderby, Casper Kaae Sønderby, Henrik Nielsen, Ole Winther:
Convolutional LSTM Networks for Subcellular Localization of Proteins. AlCoB 2015: 68-80 - [c27]Burak Çakmak, Ole Winther, Bernard H. Fleury:
S-AMP for non-linear observation models. ISIT 2015: 2807-2811 - [i9]Lars Maaloe, Morten Arngren, Ole Winther:
Deep Belief Nets for Topic Modeling. CoRR abs/1501.04325 (2015) - [i8]Burak Çakmak, Ole Winther, Bernard H. Fleury:
S-AMP for Non-linear Observation Models. CoRR abs/1501.06216 (2015) - [i7]Søren Kaae Sønderby, Casper Kaae Sønderby, Henrik Nielsen, Ole Winther:
Convolutional LSTM Networks for Subcellular Localization of Proteins. CoRR abs/1503.01919 (2015) - [i6]Manfred Opper, Burak Çakmak, Ole Winther:
A Theory of Solving TAP Equations for Ising Models with General Invariant Random Matrices. CoRR abs/1509.01229 (2015) - [i5]Søren Kaae Sønderby, Casper Kaae Sønderby, Lars Maaløe, Ole Winther:
Recurrent Spatial Transformer Networks. CoRR abs/1509.05329 (2015) - [i4]Anders Boesen Lindbo Larsen, Søren Kaae Sønderby, Ole Winther:
Autoencoding beyond pixels using a learned similarity metric. CoRR abs/1512.09300 (2015) - 2014
- [j26]Niels H. Christiansen, Per Erlend Torbergsen Voie, Ole Winther, Jan Høgsberg:
Comparison of Neural Network Error Measures for Simulation of Slender Marine Structures. J. Appl. Math. 2014: 759834:1-759834:11 (2014) - [c26]David Kofoed Wind, Ole Winther:
Model Selection in Data Analysis Competitions. MetaSel@ECAI 2014: 55-60 - [c25]Darko Zibar, Ole Winther, Robert Borkowski, Idelfonso Tafur Monroy, Luis Henrique Hecker de Carvalho, Júlio Oliveira:
Applications of expectation maximization algorithm for coherent optical communication. EUSIPCO 2014: 1890-1894 - [c24]Burak Çakmak, Ole Winther, Bernard H. Fleury:
S-AMP: Approximate message passing for general matrix ensembles. ITW 2014: 192-196 - [c23]Michael Riis Andersen, Ole Winther, Lars Kai Hansen:
Bayesian Inference for Structured Spike and Slab Priors. NIPS 2014: 1745-1753 - [i3]Burak Çakmak, Ole Winther, Bernard H. Fleury:
S-AMP: Approximate Message Passing for General Matrix Ensembles. CoRR abs/1405.2767 (2014) - [i2]Søren Kaae Sønderby, Ole Winther:
Protein Secondary Structure Prediction with Long Short Term Memory Networks. CoRR abs/1412.7828 (2014) - 2013
- [j25]Radu Dragusin, Paula Petcu, Christina Lioma, Birger Larsen, Henrik Jørgensen, Ingemar J. Cox, Lars Kai Hansen, Peter Ingwersen, Ole Winther:
FindZebra: A search engine for rare diseases. Int. J. Medical Informatics 82(6): 528-538 (2013) - [j24]Manfred Opper, Ulrich Paquet, Ole Winther:
Perturbative corrections for approximate inference in Gaussian latent variable models. J. Mach. Learn. Res. 14(1): 2857-2898 (2013) - [j23]Frederik Otzen Bagger, Nicolas Rapin, Kim Theilgaard-Mönch, Bogumil Kaczkowski, Lina A. Thoren, Johan Jendholm, Ole Winther, Bo T. Porse:
HemaExplorer: a database of mRNA expression profiles in normal and malignant haematopoiesis. Nucleic Acids Res. 41(Database-Issue): 1034-1039 (2013) - [i1]Radu Dragusin, Paula Petcu, Christina Lioma, Birger Larsen, Henrik Jørgensen, Ingemar J. Cox, Lars Kai Hansen, Peter Ingwersen, Ole Winther:
FindZebra: A search engine for rare diseases. CoRR abs/1303.3229 (2013) - 2012
- [j22]Ricardo Henao, Ole Winther:
Predictive active set selection methods for Gaussian processes. Neurocomputing 80: 10-18 (2012) - [j21]Ulrich Paquet, Blaise Thomson, Ole Winther:
A hierarchical model for ordinal matrix factorization. Stat. Comput. 22(4): 945-957 (2012) - 2011
- [j20]Ricardo Henao, Ole Winther:
Sparse Linear Identifiable Multivariate Modeling. J. Mach. Learn. Res. 12: 863-905 (2011) - [j19]Carsten Stahlhut, Morten Mørup, Ole Winther, Lars Kai Hansen:
Simultaneous EEG Source and Forward Model Reconstruction (SOFOMORE) Using a Hierarchical Bayesian Approach. J. Signal Process. Syst. 65(3): 431-444 (2011) - [c22]Radu Dragusin, Paula Petcu, Christina Lioma, Birger Larsen, Henrik Jørgensen, Ole Winther:
Rare Disease Diagnosis as an Information Retrieval Task. ICTIR 2011: 356-359 - 2010
- [j18]Lisbeth Carstensen, Albin Sandelin, Ole Winther, Niels Richard Hansen:
Multivariate Hawkes process models of the occurrence of regulatory elements. BMC Bioinform. 11: 456 (2010) - [j17]Morten Hansen, Lars P. B. Christensen, Ole Winther:
Computing the minimum-phase filter using the QL-factorization. IEEE Trans. Signal Process. 58(6): 3195-3205 (2010)
2000 – 2009
- 2009
- [j16]Ulrich Paquet, Ole Winther, Manfred Opper:
Perturbation Corrections in Approximate Inference: Mixture Modelling Applications. J. Mach. Learn. Res. 10: 1263-1304 (2009) - [j15]Eivind Valen, Albin Sandelin, Ole Winther, Anders Krogh:
Discovery of Regulatory Elements is Improved by a Discriminatory Approach. PLoS Comput. Biol. 5(11) (2009) - [c21]Mikkel N. Schmidt, Ole Winther, Lars Kai Hansen:
Bayesian Non-negative Matrix Factorization. ICA 2009: 540-547 - [c20]Carsten Stahlhut, Morten Mørup, Ole Winther, Lars Kai Hansen:
Sofomore: Combined EEG Source and Forward Model Reconstruction. ISBI 2009: 450-453 - [c19]Ricardo Henao, Ole Winther:
Bayesian Sparse Factor Models and DAGs Inference and Comparison. NIPS 2009: 736-744 - 2008
- [j14]Man-Hung Eric Tang, Anders Krogh, Ole Winther:
BayesMD: Flexible Biological Modeling for Motif Discovery. J. Comput. Biol. 15(10): 1347-1363 (2008) - [j13]Jan Christian Bryne, Eivind Valen, Man-Hung Eric Tang, Troels Torben Marstrand, Ole Winther, Isabelle da Piedade, Anders Krogh, Boris Lenhard, Albin Sandelin:
JASPAR, the open access database of transcription factor-binding profiles: new content and tools in the 2008 update. Nucleic Acids Res. 36(Database-Issue): 102-106 (2008) - [c18]Manfred Opper, Ulrich Paquet, Ole Winther:
Improving on Expectation Propagation. NIPS 2008: 1241-1248 - 2007
- [j12]Ole Winther, Kaare Brandt Petersen:
Bayesian independent component analysis: Variational methods and non-negative decompositions. Digit. Signal Process. 17(5): 858-872 (2007) - [j11]Ole Winther, Kaare Brandt Petersen:
Flexible and efficient implementations of Bayesian independent component analysis. Neurocomputing 71(1-3): 221-233 (2007) - [j10]Thomas Beierholm, Ole Winther:
Particle Filter Inference in an Articulatory-Based Speech Model. IEEE Signal Process. Lett. 14(11): 883-886 (2007) - [c17]Morten Hansen, Ole Winther, Lars P. B. Christensen:
On Sphere Detection and Minimum-Phase Prefiltered Reduced-State Sequence Estimation. GLOBECOM 2007: 4237-4241 - [c16]Fei Wang, Shijun Wang, Changshui Zhang, Ole Winther:
Semi-Supervised Mean Fields. AISTATS 2007: 596-603 - 2006
- [j9]Thomas Grotkjær, Ole Winther, Birgitte Regenberg, Jens Nielsen, Lars Kai Hansen:
Robust multi-scale clustering of large DNA microarray datasets with the consensus algorithm. Bioinform. 22(1): 58-67 (2006) - 2005
- [j8]Manfred Opper, Ole Winther:
Expectation Consistent Approximate Inference. J. Mach. Learn. Res. 6: 2177-2204 (2005) - [j7]Kaare Brandt Petersen, Ole Winther, Lars Kai Hansen:
On the Slow Convergence of EM and VBEM in Low-Noise Linear Models. Neural Comput. 17(9): 1921-1926 (2005) - [c15]Kaare Brandt Petersen, Ole Winther:
The EM algorithm in independent component analysis. ICASSP (5) 2005: 169-172 - 2004
- [c14]Manfred Opper, Ole Winther:
Approximate Inference in Probabilistic Models. ALT 2004: 494-504 - [c13]Thomas Beierholm, Brian Dam Pedersen, Ole Winther:
Low complexity Bayesian single channel source separation. ICASSP (5) 2004: 529-532 - [c12]Manfred Opper, Ole Winther:
Expectation Consistent Free Energies for Approximate Inference. NIPS 2004: 1001-1008 - 2003
- [j6]Lehel Csató, Manfred Opper, Ole Winther:
Tractable inference for probabilistic data models. Complex. 8(4): 64-68 (2003) - [c11]Manfred Opper, Ole Winther:
Variational Linear Response. NIPS 2003: 1157-1164 - 2002
- [j5]Pedro A. d. F. R. Højen-Sørensen, Ole Winther, Lars Kai Hansen:
Analysis of functional neuroimages using ICA with adaptive binary sources. Neurocomputing 49(1-4): 213-225 (2002) - [j4]Pedro A. d. F. R. Højen-Sørensen, Ole Winther, Lars Kai Hansen:
Mean-Field Approaches to Independent Component Analysis. Neural Comput. 14(4): 889-918 (2002) - [c10]Joaquin Quiñonero Candela, Ole Winther:
Incremental Gaussian Processes. NIPS 2002: 1001-1008 - [c9]Thomas Kolenda, Lars Kai Hansen, Jan Larsen, Ole Winther:
Independent component analysis for understanding multimedia content. NNSP 2002: 757-766 - 2001
- [c8]Lehel Csató, Manfred Opper, Ole Winther:
TAP Gibbs Free Energy, Belief Propagation and Sparsity. NIPS 2001: 657-663 - 2000
- [j3]Manfred Opper, Ole Winther:
Gaussian Processes for Classification: Mean-Field Algorithms. Neural Comput. 12(11): 2655-2684 (2000) - [c7]Ole Winther:
Computing with Finite and Infinite Networks. NIPS 2000: 336-342 - [c6]Pedro A. d. F. R. Højen-Sørensen, Ole Winther, Lars Kai Hansen:
Ensemble Learning and Linear Response Theory for ICA. NIPS 2000: 542-548
1990 – 1999
- 1999
- [c5]Lehel Csató, Ernest Fokoué, Manfred Opper, Bernhard Schottky, Ole Winther:
Efficient Approaches to Gaussian Process Classification. NIPS 1999: 251-257 - 1998
- [c4]Manfred Opper, Ole Winther:
Mean Field Methods for Classification with Gaussian Processes. NIPS 1998: 309-315 - 1997
- [c3]Ole Winther, Sara A. Solla:
Bayesian online learning in the perceptron. ESANN 1997 - 1996
- [c2]Søren Halkjær, Ole Winther:
The Effect of Correlated Input Data on the Dynamics of Learning. NIPS 1996: 169-175 - [c1]Manfred Opper, Ole Winther:
A Mean Field Algorithm for Bayes Learning in Large Feed-forward Neural Networks. NIPS 1996: 225-231 - 1993
- [j2]Jan Gorodkin, A. Sørensen, Ole Winther:
Neural Networks and Cellular Automata Complexity. Complex Syst. 7(1) (1993) - [j1]Jan Gorodkin, Lars Kai Hansen, Anders Krogh, Claus Svarer, Ole Winther:
A Quantitative Study Of Pruning By Optimal Brain Damage. Int. J. Neural Syst. 4(2): 159-169 (1993)