Independent Variable Group Analysis. - Krista Lagus; Esa Alhoniemi; Harri Valpola (ICANN, 2001)

An Unsupervised Ensemble Learning Method for Nonlinear Dynamic State-Space Models. - Harri Valpola; Juha Karhunen (Neural Comput., 2002)

Nonlinear Blind Source Separation by Variational Bayesian Learning. - Harri Valpola; Erkki Oja; Alexander Ilin; Antti Honkela; Juha Karhunen (IEICE Trans. Fundam. Electron. Commun. Comput. Sci., 2003)

Independent component analysis for artefact separation in astrophysical images. - Maria Funaro; Erkki Oja; Harri Valpola (Neural Networks, 2003)

Accelerating Cyclic Update Algorithms for Parameter Estimation by Pattern Searches. - Antti Honkela; Harri Valpola; Juha Karhunen (Neural Process. Lett., 2003)

Using Kernel PCA for Initialisation of Variational Bayesian Nonlinear Blind Source Separation Method. - Antti Honkela; Stefan Harmeling; Leo Lundqvist; Harri Valpola (ICA, 2004)

Accurate, Fast and Stable Denoising Source Separation Algorithms. - Harri Valpola; Jaakko Särelä (ICA, 2004)

Unsupervised Variational Bayesian Learning of Nonlinear Models. - Antti Honkela; Harri Valpola (NIPS, 2004)

Hierarchical models of variance sources. - Harri Valpola; Markus Harva; Juha Karhunen (Signal Process., 2004)

Variational learning and bits-back coding: an information-theoretic view to Bayesian learning. - Antti Honkela; Harri Valpola (IEEE Trans. Neural Networks, 2004)

Nonlinear dynamical factor analysis for state change detection. - Alexander Ilin; Harri Valpola; Erkki Oja (IEEE Trans. Neural Networks, 2004)

Development of Representations, Categories and Concepts - a Hypothesis. - Harri Valpola (CIRA, 2005)

Semiblind source separation of climate data detects El Nino as the component with the highest interannual variability. - Alexander Ilin; Harri Valpola; Erkki Oja (IJCNN, 2005)

Frequency-Based Separation of Climate Signals. - Alexander Ilin; Harri Valpola (PKDD, 2005)

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

Denoising Source Separation. - Jaakko Särelä; Harri Valpola (J. Mach. Learn. Res., 2005)

On the Effect of the Form of the Posterior Approximation in Variational Learning of ICA Models. - Alexander Ilin; Harri Valpola (Neural Process. Lett., 2005)

Separation of Nonlinear Image Mixtures by Denoising Source Separation. - Mariana S. C. Almeida; Harri Valpola; Jaakko Särelä (ICA, 2006)

Extraction of Components with Structured Variance. - Alexander Ilin; Harri Valpola; Erkki Oja (IJCNN, 2006)

Exploratory analysis of climate data using source separation methods. - Alexander Ilin; Harri Valpola; Erkki Oja (Neural Networks, 2006)

Blind separation of nonlinear mixtures by variational Bayesian learning. - Antti Honkela; Harri Valpola; Alexander Ilin; Juha Karhunen (Digit. Signal Process., 2007)

Building Blocks for Variational Bayesian Learning of Latent Variable Models. - Tapani Raiko; Harri Valpola; Markus Harva; Juha Karhunen (J. Mach. Learn. Res., 2007)

Compact Modeling of Data Using Independent Variable Group Analysis. - Esa Alhoniemi; Antti Honkela; Krista Lagus; Santeri Jeremias Seppä; Paul Wagner; Harri Valpola (IEEE Trans. Neural Networks, 2007)

Selective Attention Improves Learning. - Antti Yli-Krekola; Jaakko Särelä; Harri Valpola (ICANN (2), 2009)

Deep Learning Made Easier by Linear Transformations in Perceptrons. - Tapani Raiko; Harri Valpola; Yann LeCun (AISTATS, 2012)

Pushing Stochastic Gradient towards Second-Order Methods – Backpropagation Learning with Transformations in Nonlinearities - Tommi Vatanen; Tapani Raiko; Harri Valpola; Yann LeCun (ICLR (Workshop Poster), 2013)

From neural PCA to deep unsupervised learning. - Harri Valpola (CoRR, 2014)

Semi-supervised Learning with Ladder Networks. - Antti Rasmus; Mathias Berglund; Mikko Honkala; Harri Valpola; Tapani Raiko (NIPS, 2015)

Denoising autoencoder with modulated lateral connections learns invariant representations of natural images. - Antti Rasmus; Tapani Raiko; Harri Valpola (ICLR (Workshop), 2015)

Semi-Supervised Learning with Ladder Network. - Antti Rasmus; Harri Valpola; Mikko Honkala; Mathias Berglund; Tapani Raiko (CoRR, 2015)

Lateral Connections in Denoising Autoencoders Support Supervised Learning. - Antti Rasmus; Harri Valpola; Tapani Raiko (CoRR, 2015)

Tagger: Deep Unsupervised Perceptual Grouping. - Klaus Greff; Antti Rasmus; Mathias Berglund; Tele Hotloo Hao; Harri Valpola; Jürgen Schmidhuber (NIPS, 2016)

Recurrent Ladder Networks. - Isabeau Prémont-Schwarz; Alexander Ilin; Tele Hao; Antti Rasmus; Rinu Boney; Harri Valpola (NIPS, 2017)

Mean teachers are better role models: Weight-averaged consistency targets improve semi-supervised deep learning results. - Antti Tarvainen; Harri Valpola (NIPS, 2017)

Weight-averaged consistency targets improve semi-supervised deep learning results. - Antti Tarvainen; Harri Valpola (CoRR, 2017)

On the exact relationship between the denoising function and the data distribution. - Heikki Arponen; Matti Herranen; Harri Valpola (CoRR, 2017)

Improving Model-Based Control and Active Exploration with Reconstruction Uncertainty Optimization. - Norman Di Palo; Harri Valpola (CoRR, 2018)

Regularizing Trajectory Optimization with Denoising Autoencoders. - Rinu Boney; Norman Di Palo; Mathias Berglund; Alexander Ilin; Juho Kannala; Antti Rasmus; Harri Valpola (NeurIPS, 2019)

Knowledge Injection via Prompt Distillation. - Kalle Kujanpää; Harri Valpola; Alexander Ilin (CoRR, 2024)

Efficient Knowledge Injection in LLMs via Self-Distillation. - Kalle Kujanpää; Pekka Marttinen; Harri Valpola; Alexander Ilin (Trans. Mach. Learn. Res., 2025)

Memento No More: Coaching AI Agents to Master Multiple Tasks via Hints Internalization. - Minttu Alakuijala; Ya Gao 005; Georgy Ananov; Samuel Kaski; Pekka Marttinen; Alexander Ilin; Harri Valpola (CoRR, 2025)