2025
[ICLR] Stochastic variance-reduced Gaussian variational inference on the Bures-Wasserstein manifold
Luu H P H, Yu H, Williams B, Hartmann M, Klami A
International Conference on Learning Representations 2025
ARXIV
[AISTATS] Noise-Aware Differentially Private Variational Inference
Alrawajfeh T, Jälkö J, Honkela A
International Conference on Artificial Intelligence and Statistics 2025
ARXIV
[AISTATS] A Bias-Variance Decomposition for Ensembles over Multiple Synthetic Datasets
Räisä O, Honkela A
International Conference on Artificial Intelligence and Statistics 2025
ARXIV
[AISTATS] Amortized Probabilistic Conditioning for Optimization, Simulation and Inference
Chang P E, Loka N, Huang D, Remes U, Kaski S, Acerbi L
International Conference on Artificial Intelligence and Statistics 2025
ARXIV | CODE
[Journal] Self-adaptation of ultrasound sensing networks
Gharib S, Iablonskyi D, Mustonen J, Korsimaa J, Salminen P, Korkmaz B N, Weber M, Salmi A, Klami A
Mechanical Systems and Signal Processing 2025
LINK
2024
[NeurIPS] Non-geodesically-convex optimization in the Wasserstein space
Luu H P H, Yu H, Williams B, Mikkola P, Hartmann M, Puolamäki K, Klami A
Advances in Neural Information Processing Systems 2024
ARXIV
[NeurIPS] Preferential Normalizing Flows
Mikkola P, Acerbi L, Klami A
Advances in Neural Information Processing Systems 2024
ARXIV | CODE
[NeurIPS] Amortized Bayesian Experimental Design for Decision-Making
Huang D, Guo Y, Acerbi L, Kaski S
Advances in Neural Information Processing Systems 2024
ARXIV | CODE
[NeurIPS] Improving robustness to corruptions with multiplicative weight perturbations
Trinh T, Heinonen M, Acerbi L, Kaski S
Advances in Neural Information Processing Systems 2024
ARXIV | CODE
[NeurIPS] Noise-Aware Differentially Private Regression via Meta-Learning
Räisä O, Markou S, Ashman M, Bruinsma W P, Tobaben M, Honkela A, Turner R E
Advances in Neural Information Processing Systems 2024
ARXIV | CODE
[NeurIPS] Provable benefits of annealing for estimating normalizing constants: Importance Sampling,
Noise-Contrastive Estimation, and beyond
Chehab O, Hyvärinen A, Risteski A
Advances in Neural Information Processing Systems 2024
ARXIV | CODE
[NeurIPS] LoRANN: Low-Rank Matrix Factorization for Approximate Nearest Neighbor Search
Jääsaari E, Hyvönen V, Roos T
Advances in Neural Information Processing Systems 2024
ARXIV | CODE
[UAI] Faster Perfect Sampling of Bayesian Network Structures
Harviainen J, Koivisto M
Conference on Uncertainty in Artificial Intelligence 2024
LINK
[ICML] Causal Representation Learning Made Identifiable by Grouping of Observational Variables
Morioka H, Hyvarinen A
International Conference on Machine Learning 2024
ARXIV | CODE
[ICML] Estimating the Permanent by Nesting Importance Sampling
Harviainen J, Koivisto M
International Conference on Machine Learning 2024
LINK
[ICLR] Input-gradient space particle inference for neural network ensembles
Trinh T, Heinonen M, Acerbi L, Kaski S
International Conference on Learning Representations 2024
ARXIV | CODE
[AISTATS] Riemannian Laplace Approximation with the Fisher Metric
Yu H, Hartmann M, Williams B, Girolami M, Klami A
International Conference on Artificial Intelligence and Statistics 2024
ARXIV | CODE
[AISTATS] Identifiable Feature Learning for Spatial Data with Nonlinear ICA
Hälvä H, So J, Turner R E, Hyvärinen A
International Conference on Artificial Intelligence and Statistics 2024
ARXIV
[AISTATS] Error bounds for any regression model using Gaussian processes with gradient information
Savvides R, Luu H P H, Puolamäki K
International Conference on Artificial Intelligence and Statistics 2024
LINK | CODE
[JMLR] A Multilabel Classification Framework for Approximate Nearest Neighbor Search
Hyvönen V, Jääsaari E, Roos T
Journal of Machine Learning Research 2024
LINK
[JAIR] Approximate counting of linear extensions in practice
Talvitie T, Koivisto M
Journal of Artificial Intelligence Research 2024
LINK | CODE
[Journal] Prior knowledge elicitation: The past, present, and future
Mikkola P, Martin O A, Chandramouli S, Hartmann M, Abril Pla O, Thomas O, Pesonen H, Corander J,
Vehtari A, Kaski S, Bürkner P, Klami A
Bayesian Analysis 2024
LINK
2023
[NeurIPS] Practical equivariances via relational conditional neural processes
Huang D, Haussmann M, Remes U, John S, Clarté G, Luck K, Kaski S, Acerbi L
Advances in Neural Information Processing Systems 2023
ARXIV | CODE
[NeurIPS] Learning robust statistics for simulation-based inference under model misspecification
Huang D, Bharti A, Souza A, Acerbi L, Kaski S
Advances in Neural Information Processing Systems 2023
ARXIV | CODE
[UAI] Revisiting Bayesian network learning with small vertex cover
Harviainen J, Koivisto M
Uncertainty in Artificial Intelligence 2023
LINK
[UAI] On inference and learning with probabilistic generating circuits
Harviainen J, Ramaswamy V P, Koivisto M
Uncertainty in Artificial Intelligence 2023
LINK
[ICML] Estimating the contamination factor’s distribution in unsupervised anomaly detection
Perini L, Bürkner P, Klami A
International Conference on Machine Learning 2023
ARXIV | CODE
[AISTATS] Noise-aware statistical inference with differentially private synthetic data
Räisä O, Jälkö J, Kaski S, Honkela A
International Conference on Artificial Intelligence and Statistics 2023
ARXIV | CODE
[AISTATS] Connectivity-contrastive learning: Combining causal discovery and representation learning for
multimodal data
Morioka H, Hyvärinen A
International Conference on Artificial Intelligence and Statistics 2023
LINK | CODE
[AAAI] A faster practical approximation scheme for the permanent
Harviainen J, Koivisto M
Proceedings of the AAAI Conference on Artificial Intelligence 2023
LINK
[JMLR] Prior specification for Bayesian matrix factorization via prior predictive matching
da Silva E d S, Kuśmierczyk T, Hartmann M, Klami A
Journal of Machine Learning Research 2023
ARXIV | CODE
[Journal] Exploring uplift modeling with high class imbalance
Nyberg O, Klami A
Data Mining and Knowledge Discovery 2023
LINK | CODE
[Journal] Unsupervised representation learning of spontaneous MEG data with nonlinear ICA
Zhu Y, Parviainen T, Heinilä E, Parkkonen L, Hyvärinen A
NeuroImage 2023
LINK
[Journal] SLISEMAP: Supervised dimensionality reduction through local explanations
Björklund A, Mäkelä J, Puolamäki K
Machine Learning 2023
ARXIV | CODE
2022
[NeurIPS] Trustworthy Monte Carlo
Harviainen J, Koivisto M, Kaski P
Advances in Neural Information Processing Systems 2022
LINK
[NeurIPS] A multilabel classification framework for approximate nearest neighbor search
Hyvönen V, Jääsaari E, Roos T
Advances in Neural Information Processing Systems 2022
ARXIV | CODE
[UAI] The optimal noise in noise-contrastive learning is not what you think
Chehab O, Gramfort A, Hyvärinen A
Uncertainty in Artificial Intelligence 2022
ARXIV | CODE
[UAI] Binary independent component analysis: a non-stationarity-based approach
Hyttinen A, Pacela V B, Hyvärinen A
Uncertainty in Artificial Intelligence 2022
ARXIV | CODE
[ICML] Tackling covariate shift with node-based Bayesian neural networks
Trinh T Q, Heinonen M, Acerbi L, Kaski S
International Conference on Machine Learning 2022
ARXIV | CODE
[AISTATS] Parallel MCMC without embarrassing failures
De Souza D A, Mesquita D, Kaski S, Acerbi L
International Conference on Artificial Intelligence and Statistics 2022
ARXIV | CODE
[AISTATS] Lagrangian manifold Monte Carlo on Monge patches
Hartmann M, Girolami M, Klami A
International Conference on Artificial Intelligence and Statistics 2022
ARXIV | CODE
[Journal] Strong pathogen competition in neonatal gut colonisation
Mäklin T, Thorpe H A, Pöntinen A K, Gladstone R A, Shao Y, Pesonen M, McNally A, Johnsen P J,
Samuelsen Ø, Lawley T D, Honkela A, Corander J
Nature Communications 2022
LINK
[Journal] Dynamics of retinotopic spatial attention revealed by multifocal MEG
Kurki I, Hyvärinen A, Henriksson L
NeuroImage 2022
LINK
[Journal] Visual data exploration as a statistical testing procedure: Within-view and between-view multiple
comparisons
Savvides R, Henelius A, Oikarinen E, Puolamäki K
IEEE Transactions on Visualization and Computer Graphics 2022
LINK | CODE
[Journal] Robust regression via error tolerance
Björklund A, Henelius A, Oikarinen E, Kallonen K, Puolamäki K
Data Mining and Knowledge Discovery 2022
LINK
2021
[NeurIPS] Shared independent component analysis for multi-subject neuroimaging
Richard H, Ablin P, Thirion B, Gramfort A, Hyvärinen A
Advances in Neural Information Processing Systems 2021
ARXIV | CODE
[NeurIPS] Disentangling identifiable features from noisy data with structured nonlinear ICA
Hälvä H, Le Corff S, Lehéricy L, So J, Zhu Y, Gassiat E, Hyvärinen A
Advances in Neural Information Processing Systems 2021
ARXIV | CODE
[NeurIPS] Approximating the permanent with deep rejection sampling
Harviainen J, Röyskö A, Koivisto M
Advances in Neural Information Processing Systems 2021
ARXIV | CODE
[ICML] Differentially private Bayesian inference for generalized linear models
Kulkarni T, Jälkö J, Koskela A, Kaski S, Honkela A
International Conference on Machine Learning 2021
ARXIV
[AISTATS] Tight differential privacy for discrete-valued mechanisms and for the subsampled Gaussian mechanism
using fft
Koskela A, Jälkö J, Prediger L, Honkela A
International Conference on Artificial Intelligence and Statistics 2021
ARXIV
[AISTATS] Causal autoregressive flows
Khemakhem I, Monti R, Leech R, Hyvärinen A
International Conference on Artificial Intelligence and Statistics 2021
ARXIV | CODE
[AISTATS] Independent innovation analysis for nonlinear vector autoregressive process
Morioka H, Hälvä H, Hyvärinen A
International Conference on Artificial Intelligence and Statistics 2021
ARXIV | CODE
[JMLR] Information criteria for non-normalized models
Matsuda T, Uehara M, Hyvärinen A
Journal of Machine Learning Research 2021
ARXIV
[JMLR] Guided visual exploration of relations in data sets
Puolamäki K, Oikarinen E, Henelius A
Journal of Machine Learning Research 2021
LINK
[Journal] Direction matters: On influence-preserving graph summarization and max-cut principle for directed
graphs
Xu W, Niu G, Hyvärinen A, Sugiyama M
Neural Computation 2021
ARXIV
[Journal] Machine-learning models to replicate large-eddy simulations of air pollutant concentrations along
boulevard-type streets
Lange M, Suominen H, Kurppa M, Järvi L, Oikarinen E, Savvides R, Puolamäki K
Geoscientific Model Development 2021
LINK
[Journal] Detecting virtual concept drift of regressors without ground truth values
Oikarinen E, Tiittanen H, Henelius A, Puolamäki K
Data Mining and Knowledge Discovery 2021
LINK
[Journal] Gradient-based training and pruning of radial basis function networks with an application in
materials physics
Määttä J, Bazaliy V, Kimari J, Djurabekova F, Nordlund K, Roos T
Neural Networks 2021
LINK | CODE
2020
[NeurIPS] Dynamic allocation of limited memory resources in reinforcement learning
Patel N, Acerbi L, Pouget A
Advances in Neural Information Processing Systems 2020
ARXIV | CODE
[NeurIPS] Variational Bayesian Monte Carlo with noisy likelihoods
Acerbi L
Advances in Neural Information Processing Systems 2020
ARXIV | CODE
[NeurIPS] Relative gradient optimization of the jacobian term in unsupervised deep learning
Gresele L, Fissore G, Javaloy A, Schölkopf B, Hyvärinen A
Advances in Neural Information Processing Systems 2020
ARXIV | CODE
[NeurIPS] Modeling shared responses in neuroimaging studies through multiview ica
Richard H, Gresele L, Hyvärinen A, Thirion B, Gramfort A, Ablin P
Advances in Neural Information Processing Systems 2020
ARXIV | CODE
[NeurIPS] Ice-beem: Identifiable conditional energy-based deep models based on nonlinear ica
Khemakhem I, Monti R, Kingma D, Hyvärinen A
Advances in Neural Information Processing Systems 2020
ARXIV | CODE
[NeurIPS] Towards scalable bayesian learning of causal dags
Viinikka J, Hyttinen A, Pensar J, Koivisto M
Advances in Neural Information Processing Systems 2020
ARXIV | CODE
[UAI] Sensor placement for spatial Gaussian processes with integral observations
Longi K, Rajani C, Sillanpää T, Mäkinen J, Rauhala T, Salmi A, Hæggström E, Klami A
Conference on Uncertainty in Artificial Intelligence 2020
LINK | CODE
[UAI] Flexible prior elicitation via the prior predictive distribution
Hartmann M, Agiashvili G, Bürkner P, Klami A
Conference on Uncertainty in Artificial Intelligence 2020
ARXIV
[UAI] Hidden markov nonlinear ica: Unsupervised learning from nonstationary time series
Hälvä H, Hyvärinen A
Conference on Uncertainty in Artificial Intelligence 2020
ARXIV | CODE
[UAI] Robust contrastive learning and nonlinear ICA in the presence of outliers
Sasaki H, Takenouchi T, Monti R, Hyvärinen A
Conference on Uncertainty in Artificial Intelligence 2020
ARXIV
[UAI] Causal discovery with general non-linear relationships using non-linear ica
Monti R P, Zhang K, Hyvärinen A
Uncertainty in Artificial Intelligence 2020
ARXIV
[UAI] Layering-mcmc for structure learning in bayesian networks
Viinikka J, Koivisto M
Conference on Uncertainty in Artificial Intelligence 2020
LINK | CODE
[UAI] Exact sampling of directed acyclic graphs from modular distributions
Talvitie T, Vuoksenmaa A, Koivisto M
Uncertainty in Artificial Intelligence 2020
LINK | CODE
[AISTATS] Learning rate adaptation for differentially private learning
Koskela A, Honkela A
International Conference on Artificial Intelligence and Statistics 2020
ARXIV | CODE
[AISTATS] Computing tight differential privacy guarantees using fft
Koskela A, Jälkö J, Honkela A
International Conference on Artificial Intelligence and Statistics 2020
ARXIV
[AISTATS] Variational autoencoders and nonlinear ica: A unifying framework
Khemakhem I, Kingma D, Monti R, Hyvärinen A
International Conference on Artificial Intelligence and Statistics 2020
ARXIV | CODE
[AAAI] Correcting predictions for approximate Bayesian inference
Kuśmierczyk T, Sakaya J, Klami A
Proceedings of the AAAI Conference on Artificial Intelligence 2020
ARXIV
[AAAI] Error-correcting and verifiable parallel inference in graphical models
Karimi N, Kaski P, Koivisto M
Proceedings of the AAAI Conference on Artificial Intelligence 2020
LINK | CODE
[AAAI] A Bayesian approach for estimating causal effects from observational data
Pensar J, Talvitie T, Hyttinen A, Koivisto M
Proceedings of the AAAI Conference on Artificial Intelligence 2020
LINK
[Journal] Unbiased and efficient log-likelihood estimation with inverse binomial sampling
van Opheusden B, Acerbi L, Ma W J
PLoS Computational Biology 2020
LINK | CODE
[Journal] The role of sensory uncertainty in simple contour integration
Zhou Y, Acerbi L, Ma W J
PLoS Computational Biology 2020
LINK
[Journal] Multiscale cloud detection in remote sensing images using a dual convolutional neural network
Luotamo M, Metsämäki S, Klami A
IEEE Transactions on Geoscience and Remote Sensing 2020
LINK
[Journal] Brain activity reflects the predictability of word sequences in listened continuous speech
Koskinen M, Kurimo M, Gross J, Hyvärinen A, Hari R
NeuroImage 2020
LINK
[Journal] Nonlinear ICA of fMRI reveals primitive temporal structures linked to rest, task, and behavioral
traits
Morioka H, Calhoun V, Hyvärinen A
NeuroImage 2020
LINK
[Journal] Interactive visual data exploration with subjective feedback: an information-theoretic approach
Puolamäki K, Oikarinen E, Kang B, Lijffijt J, De Bie T
Data Mining and Knowledge Discovery 2020
ARXIV | CODE
[Journal] Nonlinear dimensionality reduction for clustering
Sotiris Tasoulis, Nicos G. Pavlidis, Teemu Roos
Pattern Recognition 2020
LINK