Alexander Ilin

According to our database1, Alexander Ilin authored at least 39 papers between 2004 and 2020.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Other 

Links

On csauthors.net:

Bibliography

2020
Conditional Spoken Digit Generation with StyleGAN.
CoRR, 2020

2019
Coupled thermo-mechanical process simulation method for selective laser melting considering phase transformation steels.
Comput. Math. Appl., 2019

Regularizing Trajectory Optimization with Denoising Autoencoders.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Active one-shot learning with Prototypical Networks.
Proceedings of the 27th European Symposium on Artificial Neural Networks, 2019

Regularizing Model-Based Planning with Energy-Based Models.
Proceedings of the 3rd Annual Conference on Robot Learning, 2019

2018
Semi-Supervised Few-Shot Learning with MAML.
Proceedings of the 6th International Conference on Learning Representations, 2018

2017
Semi-Supervised Few-Shot Learning with Prototypical Networks.
CoRR, 2017

Recurrent Ladder Networks.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

2014
Linear State-Space Model with Time-Varying Dynamics.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2014

2013
Enhanced Gradient for Training Restricted Boltzmann Machines.
Neural Computation, 2013

Gaussian-Bernoulli deep Boltzmann machine.
Proceedings of the 2013 International Joint Conference on Neural Networks, 2013

Gaussian-Bernoulli restricted Boltzmann machines and automatic feature extraction for noise robust missing data mask estimation.
Proceedings of the IEEE International Conference on Acoustics, 2013

A Two-Stage Pretraining Algorithm for Deep Boltzmann Machines.
Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2013, 2013

2012
Bayesian Robust PCA of Incomplete Data.
Neural Processing Letters, 2012

Efficient Gaussian Process Inference for Short-Scale Spatio-Temporal Modeling.
Proceedings of the Fifteenth International Conference on Artificial Intelligence and Statistics, 2012

Gated Boltzmann Machine in Texture Modeling.
Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2012, 2012

Tikhonov-Type Regularization for Restricted Boltzmann Machines.
Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2012, 2012

2011
Enhanced Gradient and Adaptive Learning Rate for Training Restricted Boltzmann Machines.
Proceedings of the 28th International Conference on Machine Learning, 2011

Improved Learning of Gaussian-Bernoulli Restricted Boltzmann Machines.
Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2011, 2011

Methodology for Behavioral-based Malware Analysis and Detection Using Random Projections and K-Nearest Neighbors Classifiers.
Proceedings of the Seventh International Conference on Computational Intelligence and Security, 2011

2010
Practical Approaches to Principal Component Analysis in the Presence of Missing Values.
J. Mach. Learn. Res., 2010

Transformations in variational Bayesian factor analysis to speed up learning.
Neurocomputing, 2010

Parallel tempering is efficient for learning restricted Boltzmann machines.
Proceedings of the International Joint Conference on Neural Networks, 2010

2009
Variational Gaussian-process factor analysis for modeling spatio-temporal data.
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

Bayesian PCA for reconstruction of historical sea surface temperatures.
Proceedings of the International Joint Conference on Neural Networks, 2009

Transformations for variational factor analysis to speed up learning.
Proceedings of the ESANN 2009, 2009

2007
Blind separation of nonlinear mixtures by variational Bayesian learning.
Digit. Signal Process., 2007

Principal Component Analysis for Sparse High-Dimensional Data.
Proceedings of the Neural Information Processing, 14th International Conference, 2007

Principal Component Analysis for Large Scale Problems with Lots of Missing Values.
Proceedings of the Machine Learning: ECML 2007, 2007

2006
Advanced source separation methods with applications to spatio-temporal datasets.
PhD thesis, 2006

Exploratory analysis of climate data using source separation methods.
Neural Networks, 2006

Extraction of Components with Structured Variance.
Proceedings of the International Joint Conference on Neural Networks, 2006

Comparison of BSS Methods for the Detection of alpha-Activity Components in EEG.
Proceedings of the Independent Component Analysis and Blind Signal Separation, 2006

Independent dynamics subspace analysis.
Proceedings of the ESANN 2006, 2006

2005
On the Effect of the Form of the Posterior Approximation in Variational Learning of ICA Models.
Neural Processing Letters, 2005

Towards an Analytical Model for Characterizing Behavior of High-Speed VVoIP Applications.
Proceedings of the world of pervasive networking, 2005

Frequency-Based Separation of Climate Signals.
Proceedings of the Knowledge Discovery in Databases: PKDD 2005, 2005

2004
Nonlinear dynamical factor analysis for state change detection.
IEEE Trans. Neural Networks, 2004

Post-nonlinear Independent Component Analysis by Variational Bayesian Learning.
Proceedings of the Independent Component Analysis and Blind Signal Separation, 2004


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