Raiko, Tapani

18 publications

NeurIPS 2016 Ladder Variational Autoencoders Casper Kaae Sønderby, Tapani Raiko, Lars Maaløe, Søren Kaae Sønderby, Ole Winther

ICML 2016 Scalable Gradient-Based Tuning of Continuous Regularization Hyperparameters Jelena Luketina, Mathias Berglund, Klaus Greff, Tapani Raiko

NeurIPS 2015 Bidirectional Recurrent Neural Networks as Generative Models Mathias Berglund, Tapani Raiko, Mikko Honkala, Leo Kärkkäinen, Akos Vetek, Juha T Karhunen

ICLR 2015 Denoising Autoencoder with Modulated Lateral Connections Learns Invariant Representations of Natural Images Antti Rasmus, Tapani Raiko, Harri Valpola

NeurIPS 2015 Semi-Supervised Learning with Ladder Networks Antti Rasmus, Mathias Berglund, Mikko Honkala, Harri Valpola, Tapani Raiko

ICLR 2015 Techniques for Learning Binary Stochastic Feedforward Neural Networks Tapani Raiko, Mathias Berglund, Guillaume Alain, Laurent Dinh

NeurIPS 2014 Iterative Neural Autoregressive Distribution Estimator NADE-K Tapani Raiko, Yao Li, Kyunghyun Cho, Yoshua Bengio

ECML-PKDD 2014 Linear State-Space Model with Time-Varying Dynamics Jaakko Luttinen, Tapani Raiko, Alexander Ilin

ICLR 2014 Stochastic Gradient Estimate Variance in Contrastive Divergence and Persistent Contrastive Divergence Mathias Berglund, Tapani Raiko

ICLR 2013 Pushing Stochastic Gradient Towards Second-Order Methods -- Backpropagation Learning with Transformations in Nonlinearities Tommi Vatanen, Tapani Raiko, Harri Valpola, Yann LeCun

AISTATS 2012 Deep Learning Made Easier by Linear Transformations in Perceptrons Tapani Raiko, Harri Valpola, Yann Lecun

ICML 2011 Enhanced Gradient and Adaptive Learning Rate for Training Restricted Boltzmann Machines KyungHyun Cho, Tapani Raiko, Alexander Ilin

JMLR 2010 Approximate Riemannian Conjugate Gradient Learning for Fixed-Form Variational Bayes Antti Honkela, Tapani Raiko, Mikael Kuusela, Matti Tornio, Juha Karhunen

JMLR 2010 Practical Approaches to Principal Component Analysis in the Presence of Missing Values Alexander Ilin, Tapani Raiko

JMLR 2007 Building Blocks for Variational Bayesian Learning of Latent Variable Models Tapani Raiko, Harri Valpola, Markus Harva, Juha Karhunen

JAIR 2006 Logical Hidden Markov Models Kristian Kersting, Luc De Raedt, Tapani Raiko

UAI 2005 "Say EM" for Selecting Probabilistic Models for Logical Sequences Kristian Kersting, Tapani Raiko

UAI 2005 Bayes Blocks: An Implementation of the Variational Bayesian Building Blocks Framework Markus Harva, Tapani Raiko, Antti Honkela, Harri Valpola, Juha Karhunen