Tomi Peltola

发表

Making Bayesian Predictive Models Interpretable: A Decision Theoretic Approach pdf

Aki Vehtari, Samuel Kaski, Homayun Afrabandpey, 2019, ArXiv.

Sparse Bayesian Linear Models: Computational Advances and Applications in Epidemiology

Tomi Peltola, 2014 .

Interactive user intent modeling for eliciting priors of a normal linear model

Samuel Kaski, Giulio Jacucci, Tomi Peltola, 2016 .

Local Interpretable Model-agnostic Explanations of Bayesian Predictive Models via Kullback-Leibler Projections pdf

Tomi Peltola, 2018, ArXiv.

Interactive AI with a Theory of Mind pdf

Pedram Daee, Tomi Peltola, Mustafa Mert Çelikok, 2019, ArXiv.

Probabilistic Expert Knowledge Elicitation of Feature Relevances in Sparse Linear Regression

Samuel Kaski, Pedram Daee, Tomi Peltola, 2017, IAL@PKDD/ECML.

Hierarchical Bayesian Survival Analysis and Projective Covariate Selection in Cardiovascular Event Risk Prediction

Aki Vehtari, Tomi Peltola, Veikko Salomaa, 2014, BMA@UAI.

Probabilistic Formulation of the Take The Best Heuristic pdf

Samuel Kaski, Jussi Jokinen, Tomi Peltola, 2019, CogSci.

Expectation Propagation for Likelihoods Depending on an Inner Product of Two Multivariate Random Variables

Aki Vehtari, Tomi Peltola, Pasi Jylänki, 2014, AISTATS.

Human-in-the-loop Active Covariance Learning for Improving Prediction in Small Data Sets

Samuel Kaski, Homayun Afrabandpey, Tomi Peltola, 2019, IJCAI.

User Modelling for Avoiding Overfitting in Interactive Knowledge Elicitation for Prediction

Aki Vehtari, Samuel Kaski, Pedram Daee, 2017, IUI.

Bayesian Variable Selection in Searching for Additive and Dominant Effects in Genome-Wide Data

Aki Vehtari, Tomi Peltola, Markus Perola, 2012, PloS one.

Improving genomics-based predictions for precision medicine through active elicitation of expert knowledge

Samuel Kaski, Chen He, Giulio Jacucci, 2017, Bioinform..

Artificial Intelligence for chemical risk assessment

Andrew Worth, Tomi Peltola, John Paul Gosling, 2020, Computational toxicology.

Machine Teaching of Active Sequential Learners

Pedram Daee, Tomi Peltola, Mustafa Mert Çelikok, 2019, NeurIPS.

Improving drug sensitivity predictions in precision medicine through active expert knowledge elicitation pdf

Samuel Kaski, Pedram Daee, Homayun Afrabandpey, 2017, ArXiv.

Knowledge elicitation via sequential probabilistic inference for high-dimensional prediction

Samuel Kaski, Pedram Daee, Tomi Peltola, 2016, Machine Learning.

Interactive Elicitation of Knowledge on Feature Relevance Improves Predictions in Small Data Sets

Samuel Kaski, Giulio Jacucci, Tomi Peltola, 2016, IUI.

Interactive Prior Elicitation of Feature Similarities for Small Sample Size Prediction

Samuel Kaski, Homayun Afrabandpey, Tomi Peltola, 2016, UMAP.

A decision-theoretic approach for model interpretability in Bayesian framework

Aki Vehtari, Samuel Kaski, Homayun Afrabandpey, 2019, Machine Learning.

Regression Analysis in Small-n-Large-p Using Interactive Prior Elicitation of Pairwise Similarities

Samuel Kaski, Homayun Afrabandpey, Tomi Peltola, 2016 .

Brain-to-brain hyperclassification reveals action-specific motor mapping of observed actions in humans

Aki Vehtari, Mikko Sams, Enrico Glerean, 2017, PloS one.

Metabolic diversity of progressive kidney disease in 325 patients with type 1 diabetes (the FinnDiane Study).

Kimmo Kaski, Tomi Peltola, Reino Laatikainen, 2012, Journal of proteome research.

Phenotype-driven identification of epithelial signalling clusters

Samuel Kaski, Tomi Peltola, Juha Klefström, 2018, Scientific Reports.