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ORCIDSamuel Kaski
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- affiliation: Aalto University, Finland
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2020 – today
- 2024
[j103]Alexander Aushev, Thong Tran, Henri Pesonen, Andrew Howes, Samuel Kaski:
Likelihood-free inference in state-space models with unknown dynamics. Stat. Comput. 34(1): 27 (2024)- 2023
- [j102]Sebastiaan De Peuter
, Antti Oulasvirta, Samuel Kaski:
Toward AI assistants that let designers design. AI Mag. 44(1): 85-96 (2023) - [j101]Nitin Williams, A. Ojanperä, Felix Siebenhühner, Benedetta Toselli, Satu Palva, Gabriele Arnulfo, Samuel Kaski, J. Matias Palva:
The influence of inter-regional delays in generating large-scale brain networks of phase synchronization. NeuroImage 279: 120318 (2023) - [j100]Zhirong Yang, Yuwei Chen, Denis Sedov, Samuel Kaski, Jukka Corander:
Stochastic cluster embedding. Stat. Comput. 33(1): 12 (2023) - [c151]Mustafa Mert Çelikok, Pierre-Alexandre Murena, Samuel Kaski:
Teaching to Learn: Sequential Teaching of Learners with Internal States. AAAI 2023: 5939-5947 - [c150]Sebastiaan De Peuter, Samuel Kaski:
Zero-Shot Assistance in Sequential Decision Problems. AAAI 2023: 11551-11559 - [c149]Ossi Räisä, Joonas Jälkö, Samuel Kaski, Antti Honkela:
Noise-Aware Statistical Inference with Differentially Private Synthetic Data. AISTATS 2023: 3620-3643 - [c148]Petrus Mikkola, Julien Martinelli, Louis Filstroff, Samuel Kaski:
Multi-Fidelity Bayesian Optimization with Unreliable Information Sources. AISTATS 2023: 7425-7454 - [c147]Ayush Bharti, Masha Naslidnyk, Oscar Key, Samuel Kaski, François-Xavier Briol:
Optimally-weighted Estimators of the Maximum Mean Discrepancy for Likelihood-Free Inference. ICML 2023: 2289-2312 - [c146]Ali Khoshvishkaie, Petrus Mikkola, Pierre-Alexandre Murena, Samuel Kaski:
Cooperative Bayesian Optimization for Imperfect Agents. ECML/PKDD (1) 2023: 475-490 - [c145]Alex Hämäläinen, Mustafa Mert Çelikok, Samuel Kaski:
Differentiable user models. UAI 2023: 798-808 - [i109]Robert Tyler Loftin, Mustafa Mert Çelikok, Herke van Hoof, Samuel Kaski, Frans A. Oliehoek:
Uncoupled Learning of Differential Stackelberg Equilibria with Commitments. CoRR abs/2302.03438 (2023) - [i108]Alexander Aushev, Aini Putkonen, Gregoire Clarte, Suyog Chandramouli, Luigi Acerbi, Samuel Kaski, Andrew Howes:
Online simulator-based experimental design for cognitive model selection. CoRR abs/2303.02227 (2023) - [i107]Alexander V. Nikitin, Letizia Iannucci, Samuel Kaski:
TSGM: A Flexible Framework for Generative Modeling of Synthetic Time Series. CoRR abs/2305.11567 (2023) - [i106]Julien Martinelli, Ayush Bharti, S. T. John, Armi Tiihonen, Sabina Sloman, Louis Filstroff, Samuel Kaski:
Cost-aware learning of relevant contextual variables within Bayesian optimization. CoRR abs/2305.14120 (2023) - [i105]Daolang Huang, Ayush Bharti, Amauri H. Souza, Luigi Acerbi, Samuel Kaski:
Learning Robust Statistics for Simulation-based Inference under Model Misspecification. CoRR abs/2305.15871 (2023) - [i104]Trung Q. Trinh, Markus Heinonen, Luigi Acerbi, Samuel Kaski:
Input gradient diversity for neural network ensembles. CoRR abs/2306.02775 (2023) - [i103]Daolang Huang, Manuel Haussmann, Ulpu Remes, S. T. John, Grégoire Clarté, Kevin Sebastian Luck, Samuel Kaski, Luigi Acerbi:
Practical Equivariances via Relational Conditional Neural Processes. CoRR abs/2306.10915 (2023) - [i102]Lukas Prediger, Joonas Jälkö, Antti Honkela, Samuel Kaski:
Collaborative Learning From Distributed Data With Differentially Private Synthetic Twin Data. CoRR abs/2308.04755 (2023) - [i101]Tiago da Silva, Eliezer Silva, Adèle H. Ribeiro, António Góis, Dominik Heider, Samuel Kaski, Diego Mesquita:
Human-in-the-Loop Causal Discovery under Latent Confounding using Ancestral GFlowNets. CoRR abs/2309.12032 (2023) - [i100]Timur Garipov, Sebastiaan De Peuter, Ge Yang, Vikas K. Garg, Samuel Kaski, Tommi S. Jaakkola:
Compositional Sculpting of Iterative Generative Processes. CoRR abs/2309.16115 (2023) - [i99]Quentin Bouniot, Ievgen Redko, Anton Mallasto, Charlotte Laclau, Karol Arndt, Oliver Struckmeier, Markus Heinonen, Ville Kyrki, Samuel Kaski:
Understanding deep neural networks through the lens of their non-linearity. CoRR abs/2310.11439 (2023) - [i98]Sophie Wharrie, Samuel Kaski:
Causal Similarity-Based Hierarchical Bayesian Models. CoRR abs/2310.12595 (2023) - [i97]Sabina J. Sloman, Ayush Bharti, Samuel Kaski:
The Fundamental Dilemma of Bayesian Active Meta-learning. CoRR abs/2310.14968 (2023) - [i96]Manuel Haussmann, Tran Minh Son Le, Viivi Halla-aho, Samu Kurki, Jussi Leinonen, Miika Koskinen, Samuel Kaski, Harri Lähdesmäki:
Estimating treatment effects from single-arm trials via latent-variable modeling. CoRR abs/2311.03002 (2023) - 2022
- [j99]Dovydas Kiciatovas, Qingli Guo, Miika Kailas, Henri Pesonen, Jukka Corander, Samuel Kaski, Esa Pitkänen, Ville Mustonen:
Identification of multiplicatively acting modulatory mutational signatures in cancer. BMC Bioinform. 23(1): 522 (2022) - [j98]Alexander Aushev, Henri Pesonen, Markus Heinonen, Jukka Corander, Samuel Kaski:
Likelihood-free inference with deep Gaussian processes. Comput. Stat. Data Anal. 174: 107529 (2022) - [j97]Iiris Sundin, Alexey Voronov, Haoping Xiao, Kostas Papadopoulos, Esben Jannik Bjerrum, Markus Heinonen, Atanas Patronov, Samuel Kaski, Ola Engkvist:
Human-in-the-loop assisted de novo molecular design. J. Cheminformatics 14(1): 86 (2022) - [j96]Lukas Prediger, Niki A. Loppi, Samuel Kaski, Antti Honkela:
d3p - A Python Package for Differentially-Private Probabilistic Programming. Proc. Priv. Enhancing Technol. 2022(2): 407-425 (2022) - [j95]Betül Güvenç Paltun, Samuel Kaski, Hiroshi Mamitsuka:
DIVERSE: Bayesian Data IntegratiVE Learning for Precise Drug ResponSE Prediction. IEEE ACM Trans. Comput. Biol. Bioinform. 19(4): 2197-2207 (2022) - [c144]Daniel Augusto de Souza, Diego Mesquita, Samuel Kaski, Luigi Acerbi:
Parallel MCMC Without Embarrassing Failures. AISTATS 2022: 1786-1804 - [c143]Alexander V. Nikitin, S. T. John, Arno Solin, Samuel Kaski:
Non-separable Spatio-temporal Graph Kernels via SPDEs. AISTATS 2022: 10640-10660 - [c142]Mustafa Mert Çelikok, Frans A. Oliehoek, Samuel Kaski:
Best-Response Bayesian Reinforcement Learning with Bayes-adaptive POMDPs for Centaurs. AAMAS 2022: 235-243 - [c141]Tung Thanh Vuong, Salvatore Andolina, Giulio Jacucci, Pedram Daee, Khalil Klouche, Mats Sjöberg, Tuukka Ruotsalo, Samuel Kaski:
EntityBot: Actionable Entity Recommendations for Everyday Digital Task. CHI Extended Abstracts 2022: 208:1-208:4 - [c140]Ayush Bharti, Louis Filstroff, Samuel Kaski:
Approximate Bayesian Computation with Domain Expert in the Loop. ICML 2022: 1893-1905 - [c139]Trung Q. Trinh, Markus Heinonen, Luigi Acerbi, Samuel Kaski:
Tackling covariate shift with node-based Bayesian neural networks. ICML 2022: 21751-21775 - [c138]Alexander V. Nikitin, Samuel Kaski:
Human-in-the-Loop Large-Scale Predictive Maintenance of Workstations. KDD 2022: 3682-3690 - [c137]Tianyu Cui, Yogesh Kumar, Pekka Marttinen, Samuel Kaski:
Deconfounded Representation Similarity for Comparison of Neural Networks. NeurIPS 2022 - [c136]Amauri H. Souza, Diego Mesquita, Samuel Kaski, Vikas Garg:
Provably expressive temporal graph networks. NeurIPS 2022 - [c135]Yogesh Verma, Samuel Kaski, Markus Heinonen, Vikas Garg:
Modular Flows: Differential Molecular Generation. NeurIPS 2022 - [c134]Pashupati Hegde, Çagatay Yildiz, Harri Lähdesmäki, Samuel Kaski, Markus Heinonen:
Variational multiple shooting for Bayesian ODEs with Gaussian processes. UAI 2022: 790-799 - [e4]Giulio Jacucci, Samuel Kaski, Cristina Conati, Simone Stumpf, Tuukka Ruotsalo, Krzysztof Gajos:
IUI 2022: 27th International Conference on Intelligent User Interfaces, Helsinki, Finland, March 22 - 25, 2022. ACM 2022, ISBN 978-1-4503-9144-3 [contents] - [e3]Giulio Jacucci, Samuel Kaski, Cristina Conati, Simone Stumpf, Tuukka Ruotsalo, Krzysztof Gajos:
IUI 2022: 27th International Conference on Intelligent User Interfaces, Helsinki, Finland, March 22 - 25, 2022 - Companion Volume. ACM 2022, ISBN 978-1-4503-9145-0 [contents] - [i95]Ayush Bharti, Louis Filstroff, Samuel Kaski:
Approximate Bayesian Computation with Domain Expert in the Loop. CoRR abs/2201.12090 (2022) - [i94]Tianyu Cui, Yogesh Kumar, Pekka Marttinen, Samuel Kaski:
Deconfounded Representation Similarity for Comparison of Neural Networks. CoRR abs/2202.00095 (2022) - [i93]Sebastiaan De Peuter, Samuel Kaski:
Zero-Shot Assistance in Novel Decision Problems. CoRR abs/2202.07364 (2022) - [i92]Daniel Augusto de Souza, Diego Mesquita, Samuel Kaski, Luigi Acerbi:
Parallel MCMC Without Embarrassing Failures. CoRR abs/2202.11154 (2022) - [i91]Mustafa Mert Çelikok, Frans A. Oliehoek, Samuel Kaski:
Best-Response Bayesian Reinforcement Learning with Bayes-adaptive POMDPs for Centaurs. CoRR abs/2204.01160 (2022) - [i90]Ossi Räisä, Joonas Jälkö, Samuel Kaski, Antti Honkela:
Noise-Aware Statistical Inference with Differentially Private Synthetic Data. CoRR abs/2205.14485 (2022) - [i89]Trung Q. Trinh, Markus Heinonen, Luigi Acerbi, Samuel Kaski:
Tackling covariate shift with node-based Bayesian neural networks. CoRR abs/2206.02435 (2022) - [i88]Alexander V. Nikitin, Samuel Kaski:
Human-in-the-Loop Large-Scale Predictive Maintenance of Workstations. CoRR abs/2206.11574 (2022) - [i87]Daolang Huang, Louis Filstroff, Petrus Mikkola, Runkai Zheng, Samuel Kaski:
Bayesian Optimization Augmented with Actively Elicited Expert Knowledge. CoRR abs/2208.08742 (2022) - [i86]Amauri H. Souza, Diego Mesquita, Samuel Kaski, Vikas Garg:
Provably expressive temporal graph networks. CoRR abs/2209.15059 (2022) - [i85]Yogesh Verma, Samuel Kaski, Markus Heinonen, Vikas Garg:
Modular Flows: Differential Molecular Generation. CoRR abs/2210.06032 (2022) - [i84]Petrus Mikkola, Julien Martinelli, Louis Filstroff, Samuel Kaski:
Multi-Fidelity Bayesian Optimization with Unreliable Information Sources. CoRR abs/2210.13937 (2022) - [i83]Joonas Jälkö, Lukas Prediger, Antti Honkela, Samuel Kaski:
DPVIm: Differentially Private Variational Inference Improved. CoRR abs/2210.15961 (2022) - [i82]Alex Hämäläinen, Mustafa Mert Çelikok, Samuel Kaski:
Differentiable User Models. CoRR abs/2211.16277 (2022) - 2021
- [j94]Betül Güvenç Paltun, Hiroshi Mamitsuka, Samuel Kaski:
Improving drug response prediction by integrating multiple data sources: matrix factorization, kernel and network-based approaches. Briefings Bioinform. 22(1): 346-359 (2021) - [j93]Betül Güvenç Paltun, Samuel Kaski, Hiroshi Mamitsuka:
Machine learning approaches for drug combination therapies. Briefings Bioinform. 22(6) (2021) - [j92]Joonas Jälkö, Eemil Lagerspetz, Jari Haukka, Sasu Tarkoma, Antti Honkela, Samuel Kaski:
Privacy-preserving data sharing via probabilistic modeling. Patterns 2(7): 100271 (2021) - [j91]Giulio Jacucci, Pedram Daee, Tung Thanh Vuong, Salvatore Andolina, Khalil Klouche, Mats Sjöberg, Tuukka Ruotsalo, Samuel Kaski:
Entity Recommendation for Everyday Digital Tasks. ACM Trans. Comput. Hum. Interact. 28(5): 29:1-29:41 (2021) - [c133]Anton Mallasto, Markus Heinonen, Samuel Kaski:
Bayesian Inference for Optimal Transport with Stochastic Cost. ACML 2021: 1601-1616 - [c132]Antti Keurulainen, Isak Westerlund, Ariel Kwiatkowski, Samuel Kaski, Alexander Ilin:
Behaviour-Conditioned Policies for Cooperative Reinforcement Learning Tasks. ICANN (4) 2021: 493-504 - [c131]Antti Keurulainen, Isak Westerlund, Samuel Kaski, Alexander Ilin:
Learning to Assist Agents by Observing Them. ICANN (4) 2021: 519-530 - [c130]Tejas Kulkarni, Joonas Jälkö, Antti Koskela, Samuel Kaski, Antti Honkela:
Differentially Private Bayesian Inference for Generalized Linear Models. ICML 2021: 5838-5849 - [c129]Alexander V. Nikitin, Samuel Kaski:
Decision Rule Elicitation for Domain Adaptation. IUI 2021: 244-248 - [c128]Zheyang Shen, Markus Heinonen, Samuel Kaski:
De-randomizing MCMC dynamics with the diffusion Stein operator. NeurIPS 2021: 17507-17517 - [c127]Vuong Thanh Tung, Salvatore Andolina, Giulio Jacucci, Pedram Daee, Khalil Klouche, Mats Sjöberg, Tuukka Ruotsalo, Samuel Kaski:
EntityBot: Supporting Everyday Digital Tasks with Entity Recommendations. RecSys 2021: 753-756 - [c126]Khaoula el Mekkaoui, Diego Mesquita, Paul Blomstedt, Samuel Kaski:
Federated stochastic gradient Langevin dynamics. UAI 2021: 1703-1712 - [i81]Alexander V. Nikitin, Samuel Kaski:
Decision Rule Elicitation for Domain Adaptation. CoRR abs/2102.11539 (2021) - [i80]Lukas Prediger, Niki A. Loppi, Samuel Kaski, Antti Honkela:
d3p - A Python Package for Differentially-Private Probabilistic Programming. CoRR abs/2103.11648 (2021) - [i79]Betül Güvenç Paltun, Samuel Kaski, Hiroshi Mamitsuka:
DIVERSE: bayesian Data IntegratiVE learning for precise drug ResponSE prediction. CoRR abs/2104.00520 (2021) - [i78]Anton Mallasto, Karol Arndt, Markus Heinonen, Samuel Kaski, Ville Kyrki:
Affine Transport for Sim-to-Real Domain Adaptation. CoRR abs/2105.11739 (2021) - [i77]Louis Filstroff, Iiris Sundin, Petrus Mikkola, Aleksei Tiulpin, Juuso Kylmäoja, Samuel Kaski:
Targeted Active Learning for Bayesian Decision-Making. CoRR abs/2106.04193 (2021) - [i76]Pashupati Hegde, Çagatay Yildiz, Harri Lähdesmäki, Samuel Kaski, Markus Heinonen:
Bayesian inference of ODEs with Gaussian processes. CoRR abs/2106.10905 (2021) - [i75]Sebastiaan De Peuter, Antti Oulasvirta, Samuel Kaski:
Toward AI Assistants That Let Designers Design. CoRR abs/2107.13074 (2021) - [i74]Zhirong Yang, Yuwei Chen, Denis Sedov, Samuel Kaski, Jukka Corander:
Stochastic Cluster Embedding. CoRR abs/2108.08003 (2021) - [i73]Antti Keurulainen, Isak Westerlund, Ariel Kwiatkowski, Samuel Kaski, Alexander Ilin:
Behaviour-conditioned policies for cooperative reinforcement learning tasks. CoRR abs/2110.01266 (2021) - [i72]Antti Keurulainen, Isak Westerlund, Samuel Kaski, Alexander Ilin:
Learning to Assist Agents by Observing Them. CoRR abs/2110.01311 (2021) - [i71]Zheyang Shen, Markus Heinonen, Samuel Kaski:
De-randomizing MCMC dynamics with the diffusion Stein operator. CoRR abs/2110.03768 (2021) - [i70]Tejas Kulkarni, Joonas Jälkö, Samuel Kaski, Antti Honkela:
Locally Differentially Private Bayesian Inference. CoRR abs/2110.14426 (2021) - [i69]Alexander Aushev, Thong Tran, Henri Pesonen, Andrew Howes, Samuel Kaski:
Likelihood-Free Inference in State-Space Models with Unknown Dynamics. CoRR abs/2111.01555 (2021) - [i68]Alexander V. Nikitin, S. T. John, Arno Solin, Samuel Kaski:
Non-separable Spatio-temporal Graph Kernels via SPDEs. CoRR abs/2111.08524 (2021) - 2020
- [j90]Tuukka Ruotsalo, Giulio Jacucci, Samuel Kaski:
Interactive faceted query suggestion for exploratory search: Whole-session effectiveness and interaction engagement. J. Assoc. Inf. Sci. Technol. 71(7): 742-756 (2020) - [j89]Homayun Afrabandpey, Tomi Peltola, Juho Piironen, Aki Vehtari, Samuel Kaski:
A decision-theoretic approach for model interpretability in Bayesian framework. Mach. Learn. 109(9-10): 1855-1876 (2020) - [j88]Jukka Sirén, Samuel Kaski:
Local dimension reduction of summary statistics for likelihood-free inference. Stat. Comput. 30(3): 559-570 (2020) - [c125]Jonathan Strahl, Jaakko Peltonen, Hiroshi Mamitsuka, Samuel Kaski:
Scalable Probabilistic Matrix Factorization with Graph-Based Priors. AAAI 2020: 5851-5858 - [c124]Zheyang Shen, Markus Heinonen, Samuel Kaski:
Learning spectrograms with convolutional spectral kernels. AISTATS 2020: 3826-3836 - [c123]Tianyu Cui, Pekka Marttinen, Samuel Kaski:
Learning Global Pairwise Interactions with Bayesian Neural Networks. ECAI 2020: 1087-1094 - [c122]Tom Vander Aa, Xiangju Qin, Paul Blomstedt, Roel Wuyts, Wilfried Verachtert, Samuel Kaski:
A High-Performance Implementation of Bayesian Matrix Factorization with Limited Communication. ICCS (6) 2020: 3-16 - [c121]Petrus Mikkola, Milica Todorovic, Jari Järvi, Patrick Rinke, Samuel Kaski:
Projective Preferential Bayesian Optimization. ICML 2020: 6884-6892 - [c120]Diego P. P. Mesquita, Amauri H. Souza Jr., Samuel Kaski:
Rethinking pooling in graph neural networks. NeurIPS 2020 - [c119]Fabio Colella, Pedram Daee, Jussi Jokinen, Antti Oulasvirta, Samuel Kaski:
Human Strategic Steering Improves Performance of Interactive Optimization. UMAP 2020: 293-297 - [i67]Petrus Mikkola, Milica Todorovic, Jari Järvi, Patrick Rinke, Samuel Kaski:
Projective Preferential Bayesian Optimization. CoRR abs/2002.03113 (2020) - [i66]Tianyu Cui, Aki S. Havulinna, Pekka Marttinen, Samuel Kaski:
Informative Gaussian Scale Mixture Priors for Bayesian Neural Networks. CoRR abs/2002.10243 (2020) - [i65]Yuxin Sun, Benny Chain, Samuel Kaski, John Shawe-Taylor:
Correlated Feature Selection with Extended Exclusive Group Lasso. CoRR abs/2002.12460 (2020) - [i64]Tom Vander Aa, Xiangju Qin, Paul Blomstedt, Roel Wuyts, Wilfried Verachtert, Samuel Kaski:
A High-Performance Implementation of Bayesian Matrix Factorization with Limited Communication. CoRR abs/2004.02561 (2020) - [i63]Khaoula el Mekkaoui, Diego P. P. Mesquita, Paul Blomstedt, Samuel Kaski:
Variance reduction for distributed stochastic gradient MCMC. CoRR abs/2004.11231 (2020) - [i62]Fabio Colella, Pedram Daee, Jussi Jokinen, Antti Oulasvirta, Samuel Kaski:
Human Strategic Steering Improves Performance of Interactive Optimization. CoRR abs/2005.01291 (2020) - [i61]Alexander Aushev, Henri Pesonen, Markus Heinonen, Jukka Corander, Samuel Kaski:
Likelihood-Free Inference with Deep Gaussian Processes. CoRR abs/2006.10571 (2020) - [i60]Mikko A. Heikkilä, Antti Koskela, Kana Shimizu, Samuel Kaski, Antti Honkela:
Differentially private cross-silo federated learning. CoRR abs/2007.05553 (2020) - [i59]Mustafa Mert Çelikok, Pierre-Alexandre Murena, Samuel Kaski:
Teaching to Learn: Sequential Teaching of Agents with Inner States. CoRR abs/2009.06227 (2020) - [i58]Razane Tajeddine, Joonas Jälkö, Samuel Kaski, Antti Honkela:
Privacy-preserving Data Sharing on Vertically Partitioned Data. CoRR abs/2010.09293 (2020) - [i57]Anton Mallasto, Markus Heinonen, Samuel Kaski:
Bayesian Inference for Optimal Transport with Stochastic Cost. CoRR abs/2010.09327 (2020) - [i56]Diego P. P. Mesquita, Amauri H. Souza Jr., Samuel Kaski:
Rethinking pooling in graph neural networks. CoRR abs/2010.11418 (2020) - [i55]Trung Q. Trinh, Samuel Kaski, Markus Heinonen:
Scalable Bayesian neural networks by layer-wise input augmentation. CoRR abs/2010.13498 (2020) - [i54]Tejas Kulkarni, Joonas Jälkö, Antti Koskela, Samuel Kaski, Antti Honkela:
Differentially Private Bayesian Inference for Generalized Linear Models. CoRR abs/2011.00467 (2020) - [i53]Charles W. L. Gadd, Markus Heinonen, Harri Lähdesmäki, Samuel Kaski:
Sample-efficient reinforcement learning using deep Gaussian processes. CoRR abs/2011.01226 (2020)
2010 – 2019
- 2019
- [j87]Teppo Mikael Niinimäki, Mikko A. Heikkilä, Antti Honkela, Samuel Kaski:
Representation transfer for differentially private drug sensitivity prediction. Bioinform. 35(14): i218-i224 (2019) - [j86]Héctor Climente-González, Chloé-Agathe Azencott, Samuel Kaski, Makoto Yamada:
Block HSIC Lasso: model-free biomarker detection for ultra-high dimensional data. Bioinform. 35(14): i427-i435 (2019) - [j85]Markus Heinonen, Maria Osmala, Henrik Mannerström, Janne Wallenius, Samuel Kaski, Juho Rousu, Harri Lähdesmäki:
Bayesian metabolic flux analysis reveals intracellular flux couplings. Bioinform. 35(14): i548-i557 (2019) - [j84]Jussi Gillberg, Pekka Marttinen, Hiroshi Mamitsuka, Samuel Kaski:
Modelling G×E with historical weather information improves genomic prediction in new environments. Bioinform. 35(20): 4045-4052 (2019) - [j83]Antti Kangasrääsiö, Jussi P. P. Jokinen, Antti Oulasvirta, Andrew Howes, Samuel Kaski:
Parameter Inference for Computational Cognitive Models with Approximate Bayesian Computation. Cogn. Sci. 43(6) (2019) - [j82]Giulio Jacucci, Oswald Barral, Pedram Daee, Markus Wenzel, Baris Serim, Tuukka Ruotsalo, Patrik Pluchino, Jonathan Freeman, Luciano Gamberini, Samuel Kaski, Benjamin Blankertz:
Integrating neurophysiologic relevance feedback in intent modeling for information retrieval. J. Assoc. Inf. Sci. Technol. 70(9): 917-930 (2019) - [j81]Xiangju Qin, Paul Blomstedt, Eemeli Leppäaho, Pekka Parviainen, Samuel Kaski:
Distributed Bayesian matrix factorization with limited communication. Mach. Learn. 108(10): 1805-1830 (2019) - [c118]Pashupati Hegde, Markus Heinonen, Harri Lähdesmäki, Samuel Kaski:
Deep learning with differential Gaussian process flows. AISTATS 2019: 1812-1821 - [c117]