Publications by topic
Estimation theory[These papers propose principles for estimation of statistical models, especially non-normalized ones, a.k.a. energy-based models.]
Review on the topic
M. U. Gutmann and A. Hyvärinen. Estimation of unnormalized statistical models without numerical integration. Proc. Int. Workshop on Information-Theoretic Methods in Science and Engineering, Tokyo, Japan, 2013.
T. Matsuda, M. Uehara, and A. Hyvärinen. Information criteria for non-normalized models. JMLR, 22: 1-33, 2021
Noise-contrastive estimationM. Gutmann and A. Hyvärinen. Noise-Contrastive Estimation of Unnormalized Statistical Models, with Applications to Natural Image Statistics, J. Machine Learning Research 13:307-361, 2012.
pdf Matlab code
[One of our two fundamental methods for estimating statistical models when the normalization constant (partition function) is not known. Based on AISTATS2010 paper.]
O. Chehab, A. Gramfort and A. Hyvärinen.
Optimizing the Noise in Self-Supervised Learning: from Importance Sampling to Noise-Contrastive Estimation. Arxiv, Jan 2023.
M. Pihlaja, M. Gutmann and A. Hyvärinen. A Family of Computationally Efficient and Simple Estimators for Unnormalized Statistical Models. Proc. UAI2010.
M. Gutmann and A. Hyvärinen.
Learning features by contrasting natural images with noise. >
Proc. Int. Conf. on Artificial Neural Networks (ICANN2009), Limassol, Cyprus, 2009.
A. Hyvärinen. Estimation of non-normalized statistical models using score matching.
Journal of Machine Learning Research, 6:695--709, 2005.
A. Hyvärinen. Optimal approximation of signal priors.
Neural Computation, 20:3087-3110, 2008.
A. Hyvärinen. Some extensions of score matching.
Computational Statistics & Data Analysis, 51:2499-2512, 2007.
A. Hyvärinen. Connections between score matching, contrastive divergence, and pseudolikelihood for continuous-valued variables.
IEEE Transactions on Neural Networks, 18(5):1529-1531, 2007.
A. Hyvärinen. Estimation theory and information geometry based on denoising.
Proc. Workshop on Information Theory in Science and Engineering, Tampere, Finland, 2008.