Kaski, Samuel

135 publications

NeurIPS 2025 A Principle of Targeted Intervention for Multi-Agent Reinforcement Learning Anjie Liu, Jianhong Wang, Samuel Kaski, Jun Wang, Mengyue Yang

NeurIPS 2025 ALINE: Joint Amortization for Bayesian Inference and Active Data Acquisition Daolang Huang, Xinyi Wen, Ayush Bharti, Samuel Kaski, Luigi Acerbi

AISTATS 2025 Amortized Probabilistic Conditioning for Optimization, Simulation and Inference Paul Edmund Chang, Nasrulloh Ratu Bagus Satrio Loka, Daolang Huang, Ulpu Remes, Samuel Kaski, Luigi Acerbi

AISTATS 2025 Cost-Aware Simulation-Based Inference Ayush Bharti, Daolang Huang, Samuel Kaski, Francois-Xavier Briol

CVPR 2025 From AlexNet to Transformers: Measuring the Non-Linearity of Deep Neural Networks with Affine Optimal Transport Quentin Bouniot, Ievgen Redko, Anton Mallasto, Charlotte Laclau, Oliver Struckmeier, Karol Arndt, Markus Heinonen, Ville Kyrki, Samuel Kaski

ICLR 2025 Generalization and Distributed Learning of GFlowNets Tiago Silva, Amauri H Souza, Omar Rivasplata, Vikas Garg, Samuel Kaski, Diego Mesquita

ICLRW 2025 Molecular Property Prediction Using Pretrained-BERT and Bayesian Active Learning: A Data-Efficient Approach to Drug Design Muhammad Arslan Masood, Samuel Kaski, Tianyu Cui

ICLRW 2025 Multi-Modal Representation Learning for Molecules Muhammad Arslan Masood, Markus Heinonen, Samuel Kaski

ICLR 2025 PABBO: Preferential Amortized Black-Box Optimization Xinyu Zhang, Daolang Huang, Samuel Kaski, Julien Martinelli

UAI 2025 Privacy-Preserving Neural Processes for Probabilistic User Modeling Amir Sonee, Haripriya Harikumar, Alex Hämäläinen, Lukas Prediger, Samuel Kaski

UAI 2025 Proxy-Informed Bayesian Transfer Learning with Unknown Sources Sabina J. Sloman, Julien Martinelli, Samuel Kaski

NeurIPS 2025 Robust and Computation-Aware Gaussian Processes Marshal Arijona Sinaga, Julien Martinelli, Samuel Kaski

TMLR 2025 Video-Language Critic: Transferable Reward Functions for Language-Conditioned Robotics Minttu Alakuijala, Reginald McLean, Isaac Woungang, Nariman Farsad, Samuel Kaski, Pekka Marttinen, Kai Yuan

AISTATS 2025 What Ails Generative Structure-Based Drug Design: Expressivity Is Too Little or Too Much? Rafal Karczewski, Samuel Kaski, Markus Heinonen, Vikas K Garg

ICLR 2025 When Do GFlowNets Learn the Right Distribution? Tiago Silva, Rodrigo Barreto Alves, Eliezer de Souza da Silva, Amauri H Souza, Vikas Garg, Samuel Kaski, Diego Mesquita

NeurIPS 2024 Amortized Bayesian Experimental Design for Decision-Making Daolang Huang, Yujia Guo, Luigi Acerbi, Samuel Kaski

NeurIPSW 2024 Amortized Decision-Aware Bayesian Experimental Design Daolang Huang, Yujia Guo, Luigi Acerbi, Samuel Kaski

ICMLW 2024 Analyzing GFlowNets: Stability, Expressiveness, and Assessment Tiago Silva, Eliezer de Souza da Silva, Rodrigo Barreto Alves, Luiz Max Carvalho, Amauri H Souza, Samuel Kaski, Vikas Garg, Diego Mesquita

UAI 2024 Bayesian Active Learning in the Presence of Nuisance Parameters Sabina J. Sloman, Ayush Bharti, Julien Martinelli, Samuel Kaski

NeurIPSW 2024 Computation-Aware Robust Gaussian Processes Marshal Arijona Sinaga, Julien Martinelli, Samuel Kaski

ICML 2024 Embarrassingly Parallel GFlowNets Tiago Silva, Luiz Max Carvalho, Amauri H Souza, Samuel Kaski, Diego Mesquita

AISTATS 2024 Estimating Treatment Effects from Single-Arm Trials via Latent-Variable Modeling Manuel Haussmann, Tran Minh Son Le, Viivi Halla-aho, Samu Kurki, Jussi Leinonen, Miika Koskinen, Samuel Kaski, Harri Lähdesmäki

ICMLW 2024 From AlexNet to Transformers: Measuring the Non-Linearity of Deep Neural Networks with Affine Optimal Transport Quentin Bouniot, Ievgen Redko, Anton Mallasto, Charlotte Laclau, Oliver Struckmeier, Karol Arndt, Markus Heinonen, Ville Kyrki, Samuel Kaski

NeurIPSW 2024 Human-Aided Discovery of Ancestral Graphs Tiago Silva, Eliezer de Souza da Silva, António Góis, Dominik Heider, Samuel Kaski, Diego Mesquita, Adele H Ribeiro

NeurIPS 2024 Improving Robustness to Corruptions with Multiplicative Weight Perturbations Trung Trinh, Markus Heinonen, Luigi Acerbi, Samuel Kaski

ICLR 2024 Input-Gradient Space Particle Inference for Neural Network Ensembles Trung Trinh, Markus Heinonen, Luigi Acerbi, Samuel Kaski

UAI 2024 Learning Relevant Contextual Variables Within Bayesian Optimization Julien Martinelli, Ayush Bharti, Armi Tiihonen, S. T. John, Louis Filstroff, Sabina J. Sloman, Patrick Rinke, Samuel Kaski

ICML 2024 Open Ad Hoc Teamwork with Cooperative Game Theory Jianhong Wang, Yang Li, Yuan Zhang, Wei Pan, Samuel Kaski

NeurIPS 2024 Preference Learning of Latent Decision Utilities with a Human-like Model of Preferential Choice Sebastiaan De Peuter, Shibei Zhu, Yujia Guo, Andrew Howes, Samuel Kaski

NeurIPS 2024 TSGM: A Flexible Framework for Generative Modeling of Synthetic Time Series Alexander Nikitin, Letizia Iannucci, Samuel Kaski

TMLR 2024 Targeted Active Learning for Bayesian Decision-Making Louis Filstroff, Iiris Sundin, Petrus Mikkola, Aleksei Tiulpin, Juuso Kylmäoja, Samuel Kaski

ICMLW 2023 Augmenting Bayesian Optimization with Preference-Based Expert Feedback Daolang Huang, Louis Filstroff, Petrus Mikkola, Runkai Zheng, Milica Todorovic, Samuel Kaski

ICMLW 2023 Bayesian Active Meta-Learning Under Prior Misspecification Sabina J. Sloman, Ayush Bharti, Samuel Kaski

MLHC 2023 Characterizing Personalized Effects of Family Information on Disease Risk Using Graph Representation Learning Sophie Wharrie, Zhiyu Yang, Andrea Ganna, Samuel Kaski

NeurIPS 2023 Compositional Sculpting of Iterative Generative Processes Timur Garipov, Sebastiaan De Peuter, Ge Yang, Vikas Garg, Samuel Kaski, Tommi Jaakkola

ECML-PKDD 2023 Cooperative Bayesian Optimization for Imperfect Agents Ali Khoshvishkaie, Petrus Mikkola, Pierre-Alexandre Murena, Samuel Kaski

TMLR 2023 DPVIm: Differentially Private Variational Inference Improved Joonas Jälkö, Lukas Prediger, Antti Honkela, Samuel Kaski

UAI 2023 Differentiable User Models Alex Hämäläinen, Mustafa Mert Çelikok, Samuel Kaski

NeurIPSW 2023 Learning Relevant Contextual Variables Within Bayesian Optimization Julien Martinelli, Ayush Bharti, Armi Tiihonen, Louis Filstroff, S. T. John, Sabina J. Sloman, Patrick Rinke, Samuel Kaski

NeurIPS 2023 Learning Robust Statistics for Simulation-Based Inference Under Model Misspecification Daolang Huang, Ayush Bharti, Amauri Souza, Luigi Acerbi, Samuel Kaski

NeurIPSW 2023 Leveraging Expert Feedback to Align Proxy and Ground Truth Rewards in Goal-Oriented Molecular Generation Julien Martinelli, Yasmine Nahal, Duong Lê, Ola Engkvist, Samuel Kaski

AISTATS 2023 Multi-Fidelity Bayesian Optimization with Unreliable Information Sources Petrus Mikkola, Julien Martinelli, Louis Filstroff, Samuel Kaski

AISTATS 2023 Noise-Aware Statistical Inference with Differentially Private Synthetic Data Ossi Räisä, Joonas Jälkö, Samuel Kaski, Antti Honkela

ICML 2023 Optimally-Weighted Estimators of the Maximum Mean Discrepancy for Likelihood-Free Inference Ayush Bharti, Masha Naslidnyk, Oscar Key, Samuel Kaski, Francois-Xavier Briol

NeurIPS 2023 Practical Equivariances via Relational Conditional Neural Processes Daolang Huang, Manuel Haussmann, Ulpu Remes, St John, Grégoire Clarté, Kevin Luck, Samuel Kaski, Luigi Acerbi

NeurIPSW 2023 Preferential Heteroscedastic Bayesian Optimization with Informative Noise Priors Marshal Arijona Sinaga, Julien Martinelli, Samuel Kaski

AAAI 2023 Teaching to Learn: Sequential Teaching of Learners with Internal States Mustafa Mert Çelikok, Pierre-Alexandre Murena, Samuel Kaski

AAAI 2023 Zero-Shot Assistance in Sequential Decision Problems Sebastiaan De Peuter, Samuel Kaski

AISTATS 2022 Non-Separable Spatio-Temporal Graph Kernels via SPDEs Alexander V. Nikitin, St John, Arno Solin, Samuel Kaski

AISTATS 2022 Parallel MCMC Without Embarrassing Failures Daniel A. De Souza, Diego Mesquita, Samuel Kaski, Luigi Acerbi

ICML 2022 Approximate Bayesian Computation with Domain Expert in the Loop Ayush Bharti, Louis Filstroff, Samuel Kaski

NeurIPS 2022 Deconfounded Representation Similarity for Comparison of Neural Networks Tianyu Cui, Yogesh Kumar, Pekka Marttinen, Samuel Kaski

NeurIPSW 2022 HAPNEST: An Efficient Tool for Generating Large-Scale Genetics Datasets from Limited Training Data Sophie Wharrie, Zhiyu Yang, Vishnu Raj, Remo Monti, Rahul Gupta, Ying Wang, Alicia Martin, Luke J O'Connor, Samuel Kaski, Pekka Marttinen, Pier Palamara, Christoph Lippert, Andrea Ganna

NeurIPS 2022 Modular Flows: Differential Molecular Generation Yogesh Verma, Samuel Kaski, Markus Heinonen, Vikas Garg

NeurIPSW 2022 Modular Flows: Differential Molecular Generation Yogesh Verma, Samuel Kaski, Markus Heinonen, Vikas Garg

NeurIPSW 2022 Modular Flows: Differential Molecular Generation Yogesh Verma, Samuel Kaski, Markus Heinonen, Vikas Garg

NeurIPSW 2022 More Trustworthy Bayesian Optimization of Materials Properties by Adding Human into the Loop Armi Tiihonen, Louis Filstroff, Petrus Mikkola, Emma Lehto, Samuel Kaski, Milica Todorović, Patrick Rinke

NeurIPSW 2022 Noise-Aware Statistical Inference with Differentially Private Synthetic Data Ossi Räisä, Joonas Jälkö, Samuel Kaski, Antti Honkela

NeurIPS 2022 Provably Expressive Temporal Graph Networks Amauri Souza, Diego Mesquita, Samuel Kaski, Vikas Garg

NeurIPSW 2022 Provably Expressive Temporal Graph Networks Amauri H Souza, Diego Mesquita, Samuel Kaski, Vikas Garg

ICML 2022 Tackling Covariate Shift with Node-Based Bayesian Neural Networks Trung Q Trinh, Markus Heinonen, Luigi Acerbi, Samuel Kaski

NeurIPSW 2022 Targeted Causal Elicitation Nazaal Ibrahim, S. T. John, Zhigao Guo, Samuel Kaski

UAI 2022 Variational Multiple Shooting for Bayesian ODEs with Gaussian Processes Pashupati Hegde, Çağatay Yıldız, Harri Lähdesmäki, Samuel Kaski, Markus Heinonen

ACML 2021 Bayesian Inference for Optimal Transport with Stochastic Cost Anton Mallasto, Markus Heinonen, Samuel Kaski

NeurIPS 2021 De-Randomizing MCMC Dynamics with the Diffusion Stein Operator Zheyang Shen, Markus Heinonen, Samuel Kaski

ICML 2021 Differentially Private Bayesian Inference for Generalized Linear Models Tejas Kulkarni, Joonas Jälkö, Antti Koskela, Samuel Kaski, Antti Honkela

UAI 2021 Federated Stochastic Gradient Langevin Dynamics Khaoula Mekkaoui, Diego Mesquita, Paul Blomstedt, Samuel Kaski

NeurIPSW 2021 Likelihood-Free Inference in State-Space Models with Unknown Dynamics Alexander Aushev, Thong Anh Tran, Henri Pesonen, Andrew Howes, Samuel Kaski

MLJ 2020 A Decision-Theoretic Approach for Model Interpretability in Bayesian Framework Homayun Afrabandpey, Tomi Peltola, Juho Piironen, Aki Vehtari, Samuel Kaski

AISTATS 2020 Learning Spectrograms with Convolutional Spectral Kernels Zheyang Shen, Markus Heinonen, Samuel Kaski

NeurIPSW 2020 Likelihood-Free Inference with Deep Gaussian Processes Alexander Aushev, Henri Pesonen, Markus Heinonen, Jukka Corander, Samuel Kaski

ICML 2020 Projective Preferential Bayesian Optimization Petrus Mikkola, Milica Todorović, Jari Järvi, Patrick Rinke, Samuel Kaski

NeurIPS 2020 Rethinking Pooling in Graph Neural Networks Diego Mesquita, Amauri Souza, Samuel Kaski

AAAI 2020 Scalable Probabilistic Matrix Factorization with Graph-Based Priors Jonathan Strahl, Jaakko Peltonen, Hiroshi Mamitsuka, Samuel Kaski

ICML 2019 Active Learning for Decision-Making from Imbalanced Observational Data Iiris Sundin, Peter Schulam, Eero Siivola, Aki Vehtari, Suchi Saria, Samuel Kaski

ECML-PKDD 2019 Deep Convolutional Gaussian Processes Kenneth Blomqvist, Samuel Kaski, Markus Heinonen

AISTATS 2019 Deep Learning with Differential Gaussian Process Flows Pashupati Hegde, Markus Heinonen, Harri Lähdesmäki, Samuel Kaski

MLJ 2019 Distributed Bayesian Matrix Factorization with Limited Communication Xiangju Qin, Paul Blomstedt, Eemeli Leppäaho, Pekka Parviainen, Samuel Kaski

UAI 2019 Embarrassingly Parallel MCMC Using Deep Invertible Transformations Diego Mesquita, Paul Blomstedt, Samuel Kaski

AISTATS 2019 Harmonizable Mixture Kernels with Variational Fourier Features Zheyang Shen, Markus Heinonen, Samuel Kaski

IJCAI 2019 Human-in-the-Loop Active Covariance Learning for Improving Prediction in Small Data Sets Homayun Afrabandpey, Tomi Peltola, Samuel Kaski

NeurIPS 2019 Machine Teaching of Active Sequential Learners Tomi Peltola, Mustafa Mert Çelikok, Pedram Daee, Samuel Kaski

IJCAI 2019 Scalable Bayesian Non-Linear Matrix Completion Xiangju Qin, Paul Blomstedt, Samuel Kaski

MLOSS 2018 ELFI: Engine for Likelihood-Free Inference Jarno Lintusaari, Henri Vuollekoski, Antti Kangasrääsiö, Kusti Skytén, Marko Järvenpää, Pekka Marttinen, Michael U. Gutmann, Aki Vehtari, Jukka Corander, Samuel Kaski

MLJ 2018 Inverse Reinforcement Learning from Summary Data Antti Kangasrääsiö, Samuel Kaski

UAI 2018 Variational Zero-Inflated Gaussian Processes with Sparse Kernels Pashupati Hegde, Markus Heinonen, Samuel Kaski

ACML 2017 A Mutually-Dependent Hadamard Kernel for Modelling Latent Variable Couplings Sami Remes, Markus Heinonen, Samuel Kaski

NeurIPS 2017 Differentially Private Bayesian Learning on Distributed Data Mikko Heikkilä, Eemil Lagerspetz, Samuel Kaski, Kana Shimizu, Sasu Tarkoma, Antti Honkela

MLOSS 2017 GFA: Exploratory Analysis of Multiple Data Sources with Group Factor Analysis Eemeli Leppäaho, Muhammad Ammad-ud-din, Samuel Kaski

MLJ 2017 Knowledge Elicitation via Sequential Probabilistic Inference for High-Dimensional Prediction Pedram Daee, Tomi Peltola, Marta Soare, Samuel Kaski

AISTATS 2017 Localized Lasso for High-Dimensional Regression Makoto Yamada, Koh Takeuchi, Tomoharu Iwata, John Shawe-Taylor, Samuel Kaski

MLJ 2017 Multi-View Kernel Completion Sahely Bhadra, Samuel Kaski, Juho Rousu

NeurIPS 2017 Non-Stationary Spectral Kernels Sami Remes, Markus Heinonen, Samuel Kaski

IJCAI 2016 A Robust Convex Formulation for Ensemble Clustering Junning Gao, Makoto Yamada, Samuel Kaski, Hiroshi Mamitsuka, Shanfeng Zhu

MLJ 2016 Bayesian Multi-Tensor Factorization Suleiman A. Khan, Eemeli Leppäaho, Samuel Kaski

PGM 2016 Bayesian Networks for Variable Groups Pekka Parviainen, Samuel Kaski

JMLR 2016 Multiple Output Regression with Latent Noise Jussi Gillberg, Pekka Marttinen, Matti Pirinen, Antti J. Kangas, Pasi Soininen, Mehreen Ali, Aki S. Havulinna, Marjo-Riitta Järvelin, Mika Ala-Korpela, Samuel Kaski

AISTATS 2016 Non-Stationary Gaussian Process Regression with Hamiltonian Monte Carlo Markus Heinonen, Henrik Mannerström, Juho Rousu, Samuel Kaski, Harri Lähdesmäki

AISTATS 2015 Majorization-Minimization for Manifold Embedding Zhirong Yang, Jaakko Peltonen, Samuel Kaski

ECML-PKDD 2014 Bayesian Multi-View Tensor Factorization Suleiman A. Khan, Samuel Kaski

AAAI 2014 Optimal Neighborhood Preserving Visualization by Maximum Satisfiability Kerstin Bunte, Matti Järvisalo, Jeremias Berg, Petri Myllymäki, Jaakko Peltonen, Samuel Kaski

ICML 2014 Optimization Equivalence of Divergences Improves Neighbor Embedding Zhirong Yang, Jaakko Peltonen, Samuel Kaski

AISTATS 2014 Preface Samuel Kaski, Jukka Corander

JMLR 2013 Bayesian Canonical Correlation Analysis Arto Klami, Seppo Virtanen, Samuel Kaski

ICML 2013 Kernelized Bayesian Matrix Factorization Mehmet Gönen, Suleiman Khan, Samuel Kaski

ICML 2013 Scalable Optimization of Neighbor Embedding for Visualization Zhirong Yang, Jaakko Peltonen, Samuel Kaski

AISTATS 2012 Bayesian Group Factor Analysis Seppo Virtanen, Arto Klami, Suleiman Khan, Samuel Kaski

MLJ 2012 Focused Multi-Task Learning in a Gaussian Process Framework Gayle Leen, Jaakko Peltonen, Samuel Kaski

ECML-PKDD 2012 Unsupervised Inference of Auditory Attention from Biosensors Melih Kandemir, Arto Klami, Akos Vetek, Samuel Kaski

ICML 2011 Bayesian CCA via Group Sparsity Seppo Virtanen, Arto Klami, Samuel Kaski

ECML-PKDD 2011 Focused Multi-Task Learning Using Gaussian Processes Gayle Leen, Jaakko Peltonen, Samuel Kaski

AISTATS 2011 Generative Modeling for Maximizing Precision and Recall in Information Visualization Jaakko Peltonen, Samuel Kaski

MLJ 2011 Introduction to the Special Issue on Mining and Learning with Graphs S. V. N. Vishwanathan, Samuel Kaski, Jennifer Neville, Stefan Wrobel

UAI 2010 Bayesian Exponential Family Projections for Coupled Data Sources Arto Klami, Seppo Virtanen, Samuel Kaski

ECML-PKDD 2010 Graphical Multi-Way Models Ilkka Huopaniemi, Tommi Suvitaival, Matej Oresic, Samuel Kaski

MLJ 2010 Infinite Factorization of Multiple Non-Parametric Views Simon Rogers, Arto Klami, Janne Sinkkonen, Mark A. Girolami, Samuel Kaski

JMLR 2010 Information Retrieval Perspective to Nonlinear Dimensionality Reduction for Data Visualization Jarkko Venna, Jaakko Peltonen, Kristian Nybo, Helena Aidos, Samuel Kaski

ECML-PKDD 2010 Variational Bayesian Mixture of Robust CCA Models Jaakko Viinikanoja, Arto Klami, Samuel Kaski

MLJ 2009 Latent Grouping Models for User Preference Prediction Eerika Savia, Kai Puolamäki, Samuel Kaski

ICCVW 2009 Learning to Rank Images from Eye Movements Kitsuchart Pasupa, Craig Saunders, Sándor Szedmák, Arto Klami, Samuel Kaski, Steve R. Gunn

ECML-PKDD 2009 Two-Way Analysis of High-Dimensional Collinear Data Ilkka Huopaniemi, Tommi Suvitaival, Janne Nikkilä, Matej Oresic, Samuel Kaski

ICML 2008 Learning to Learn Implicit Queries from Gaze Patterns Kai Puolamäki, Antti Ajanki, Samuel Kaski

AISTATS 2007 Information Retrieval by Inferring Implicit Queries from Eye Movements David R. Hardoon, John Shawe-Taylor, Antti Ajanki, Kai Puolamäki, Samuel Kaski

ICML 2007 Local Dependent Components Arto Klami, Samuel Kaski

AISTATS 2007 Nonlinear Dimensionality Reduction as Information Retrieval Jarkko Venna, Samuel Kaski

ICML 2005 Expectation Maximization Algorithms for Conditional Likelihoods Jarkko Salojärvi, Kai Puolamäki, Samuel Kaski

ECML-PKDD 2005 On Discriminative Joint Density Modeling Jarkko Salojärvi, Kai Puolamäki, Samuel Kaski

UAI 2005 Two-Way Latent Grouping Model for User Preference Prediction Eerika Savia, Kai Puolamäki, Janne Sinkkonen, Samuel Kaski

ECML-PKDD 2004 Associative Clustering Janne Sinkkonen, Janne Nikkilä, Leo Lahti, Samuel Kaski

ICML 2004 Sequential Information Bottleneck for Finite Data Jaakko Peltonen, Janne Sinkkonen, Samuel Kaski

ICML 2003 Informative Discriminant Analysis Samuel Kaski, Jaakko Peltonen

ECML-PKDD 2003 Visualizations for Assessing Convergence and Mixing of MCMC Jarkko Venna, Samuel Kaski, Jaakko Peltonen

NeCo 2002 Clustering Based on Conditional Distributions in an Auxiliary Space Janne Sinkkonen, Samuel Kaski

ECML-PKDD 2002 Discriminative Clustering: Optimal Contingency Tables by Learning Metrics Janne Sinkkonen, Samuel Kaski, Janne Nikkilä

NeCo 1997 Self-Organized Formation of Various Invariant-Feature Filters in the Adaptive-Subspace SOM Teuvo Kohonen, Samuel Kaski, Harri Lappalainen