Aapo Hyvärinen

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

Achievements

+12 more ↓

🧭 Keyword Pioneer 🌈 Renaissance Researcher (8) 🌉 Interdisciplinary Bridge 🗺️ Taxonomy Completionist (19) 🐣 Hot Topic Early Bird

🐣 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