← Authors

Aapo Hyvärinen

39 papers · 2005–2025 · 6 conferences · across top CS/AI conferences

Achievements

🌍 Conference Polyglot (6) 🏃 Academic Marathon (20) 🗺️ Taxonomy Completionist (19) 🐝 Cross-Pollinator (10) 🌉 Interdisciplinary Bridge 🐣 Hot Topic Early Bird 🌈 Renaissance Researcher (8) 🧭 Keyword Pioneer 🌟 Keyword Trendsetter Combo (6) 🔬 Deep Specialist (17) 🏆 Keyword Champion (6) 🗃️ Keyword Collector (67) 🚀 Conference Pioneer 📈 Trend Setter ⚡ Prolific Year (6) 💎 Century Club (39) 🔥 Unstoppable (10)

Conferences

AISTATS (10) JMLR (9) NIPS (9) UAI (5) ACML (3) ICML (3)

Top co-authors

Hiroshi Morioka (5) Hiroaki Sasaki (5) Hermanni Hälvä (4) Ricardo Monti (4) Omar Chehab (3) Ilyes Khemakhem (3) Alexandre Gramfort (3) Kun Zhang (3) Hugo Richard (2) Luigi Gresele (2)

Keywords

independent component analysis (14) causal discovery (7) density estimation (5) nonlinear ica (5) contrastive learning (5) representation learning (4) noise-contrastive estimation (4) structural equation model (3) unsupervised learning (3) score matching (3) causal inference (3) variational inference (3) logistic regression (3) nonlinear independent component analysis (3) unnormalized model (3) probabilistic modeling (3) probabilistic model (2) partition function (2) probability density (2) parameter estimation (2)

Papers

Density Ratio Estimation with Conditional Probability Paths ICML 2025
Causal Representation Learning Made Identifiable by Grouping of Observational Variables ICML 2024
Identifiable Feature Learning for Spatial Data with Nonlinear ICA AISTATS 2024
Provable benefits of annealing for estimating normalizing constants: Importance Sampling, Noise-Contrastive Estimation, and beyond NIPS 2023
Connectivity-contrastive learning: Combining causal discovery and representation learning for multimodal data AISTATS 2023
The optimal noise in noise-contrastive learning is not what you think UAI 2022
Binary independent component analysis: a non-stationarity-based approach UAI 2022
Causal Autoregressive Flows AISTATS 2021
Disentangling Identifiable Features from Noisy Data with Structured Nonlinear ICA NIPS 2021
Shared Independent Component Analysis for Multi-Subject Neuroimaging NIPS 2021
Independent Innovation Analysis for Nonlinear Vector Autoregressive Process AISTATS 2021
Information criteria for non-normalized models JMLR 2021
ICE-BeeM: Identifiable Conditional Energy-Based Deep Models Based on Nonlinear ICA NIPS 2020
Relative gradient optimization of the Jacobian term in unsupervised deep learning NIPS 2020
Modeling Shared responses in Neuroimaging Studies through MultiView ICA NIPS 2020
Robust contrastive learning and nonlinear ICA in the presence of outliers UAI 2020
Hidden Markov Nonlinear ICA: Unsupervised Learning from Nonstationary Time Series UAI 2020
Variational Autoencoders and Nonlinear ICA: A Unifying Framework AISTATS 2020
Causal Discovery with General Non-Linear Relationships using Non-Linear ICA UAI 2019
Nonlinear ICA Using Auxiliary Variables and Generalized Contrastive Learning AISTATS 2019
Estimation of Non-Normalized Mixture Models AISTATS 2019
Neural Empirical Bayes JMLR 2019
Mode-Seeking Clustering and Density Ridge Estimation via Direct Estimation of Density-Derivative-Ratios JMLR 2018
Density Estimation in Infinite Dimensional Exponential Families JMLR 2017
SPLICE: Fully Tractable Hierarchical Extension of ICA with Pooling ICML 2017
Nonlinear ICA of Temporally Dependent Stationary Sources AISTATS 2017
Unsupervised Feature Extraction by Time-Contrastive Learning and Nonlinear ICA NIPS 2016
Estimating Dependency Structures for non-Gaussian Components with Linear and Energy Correlations AISTATS 2014
Pairwise Likelihood Ratios for Estimation of Non-Gaussian Structural Equation Models JMLR 2013
Noise-Contrastive Estimation of Unnormalized Statistical Models, with Applications to Natural Image Statistics JMLR 2012
Topographic Analysis of Correlated Components ACML 2012
DirectLiNGAM: A Direct Method for Learning a Linear Non-Gaussian Structural Equation Model JMLR 2011
A General Linear Non-Gaussian State-Space Model: Identifiability, Identification, and Applications ACML 2011
Structural equations and divisive normalization for energy-dependent component analysis NIPS 2011
Noise-contrastive estimation: A new estimation principle for unnormalized statistical models AISTATS 2010
Pairwise Measures of Causal Direction in Linear Non-Gaussian Acyclic Models ACML 2010
Estimation of a Structural Vector Autoregression Model Using Non-Gaussianity JMLR 2010
Emergence of conjunctive visual features by quadratic independent component analysis NIPS 2006
Estimation of Non-Normalized Statistical Models by Score Matching JMLR 2005