Hyvarinen, Aapo

1. Unsupervised Feature Extraction by Time-Contrastive Learning and Nonlinear ICA
   2016/05/20 by Aapo Hyvärinen, Hiroshi Morioka, Hyvarinen, Aapo +1 · 34 citations
   Computer Science · Chemistry · #Blind Source Separation Techniques #Neural Networks and Applications #Spectroscopy and Chemometric Analyses
2. Nonlinear ICA Using Auxiliary Variables and Generalized Contrastive Learning
   2018/05/22 by Aapo Hyvärinen, Hiroaki Sasaki, Hyvarinen, Aapo +3 · 35 citations
   Computer Science · #Blind Source Separation Techniques #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Neural Networks and Applications #Neural Networks and Reservoir Computing
3. DirectLiNGAM: A direct method for learning a linear non-Gaussian structural equation model
   2011/01/13 by Shohei Shimizu, Takanori Inazumi, Shimizu, Shohei +13 · 22 citations
   Computer Science · #Bayesian Modeling and Causal Inference #FOS: Computer and information sciences #Machine Learning (stat.ML)
4. On the Identifiability of the Post-Nonlinear Causal Model
   2012/05/09 by Zhang, Kun, Hyvarinen, Aapo · 18 citations
   #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML)
5. Disentangling Identifiable Features from Noisy Data with Structured\n Nonlinear ICA
   2021/06/17 by Hermanni Hälvä, Sylvain Le Corff, Hälvä, Hermanni +11 · 8 citations
   Computer Science · #Blind Source Separation Techniques #FOS: Computer and information sciences #Image and Signal Denoising Methods #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Neural Networks and Applications
6. Nonlinear Independent Component Analysis for Principled Disentanglement in Unsupervised Deep Learning
   2023/03/29 by Hyvarinen, Aapo, Khemakhem, Ilyes, Morioka, Hiroshi · 9 citations
   #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML)
7. Causal Discovery with General Non-Linear Relationships Using Non-Linear\n ICA
   2019/04/19 by Ricardo Pio Monti, Kun Zhang, Monti, Ricardo Pio +3 · 4 citations
   Chemistry · Computer Science · #Blind Source Separation Techniques #Electrochemical Analysis and Applications #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Spectroscopy and Chemometric Analyses
8. Estimation of causal orders in a linear non-Gaussian acyclic model: a method robust against latent confounders
   2012/04/09 by Tashiro, Tatsuya, Shimizu, Shohei, Hyvarinen, Aapo +1 · 1 citation
   #FOS: Computer and information sciences #Machine Learning (stat.ML)
9. ParceLiNGAM: A causal ordering method robust against latent confounders
   2013/03/29 by Tatsuya Tashiro, Shohei Shimizu, Tashiro, Tatsuya +5 · 1 citation
   Computer Science · Mathematics · #Bayesian Methods and Mixture Models #Bayesian Modeling and Causal Inference #FOS: Computer and information sciences #Machine Learning (stat.ML) #Statistical Methods and Bayesian Inference
10. Provable benefits of annealing for estimating normalizing constants: Importance Sampling, Noise-Contrastive Estimation, and beyond
    2023/10/05 by Chehab, Omar, Hyvarinen, Aapo, Risteski, Andrej · 2 citations
    #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML)