Probabilistic Machine Learning

Research output

Research output per year 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025

• 196 Article
• 149 Conference article in proceedings
• 19 Doctoral Thesis
• 10 Paper
• 45 More
  • 7 Chapter
  • 6 Book
  • 6 Conference article
  • 4 Abstract
  • 3 Meeting Abstract
  • 3 Letter
  • 2 Anthology
  • 2 Poster
  • 2 Review Article
  • 2 Other contribution
  • 2 Patent
  • 2 Working paper
  • 1 Foreword / postscript
  • 1 Comment/debate
  • 1 Editorial
  • 1 Special issue

Research output per year

Research output per year

Search results

• 2022

  Evidential Turing Processes

  Kandemir, M., Akgül, A., Haussmann, M. & Unal, G., 2022, p. 1-16. 16 p.

  Research output: Contribution to conference › Paper › Scientific › peer-review

  Open Access

  • Domains 100%
  • Classes 100%
  • Deep Learning 50%
  • Classifier 50%
  • Probability 50%
  5 Citations (Scopus)

• Fantasizing with Dual GPs in Bayesian Optimization and Active Learning

  Chang, P., Verma, P., John, T., Picheny, V., Moss, H. & Solin, A., 2022.

  Research output: Contribution to conference › Paper › Scientific › peer-review

  Open Access

  • Gaussian Process 100%
  • Optimization 100%
  • Functions 100%
  • Active Learning 100%
  • Learning 100%

• Joint Point Process Model for Counterfactual Treatment–Outcome Trajectories Under Policy Interventions

  Hizli, C., John, T., Juuti, A., Saarinen, T., Pietiläinen, K. & Marttinen, P., 2022.

  Research output: Contribution to conference › Paper › Scientific › peer-review

  Open Access

  • Process Model 100%
  • Treatment 100%
  • Continuous Time 20%
  • Models 20%
  • Algorithms 20%

• Targeted Causal Elicitation

  Ibrahim, N., John, T., Guo, Z. & Kaski, S., 2022.

  Research output: Contribution to conference › Paper › Scientific › peer-review

  Open Access

  • Models 100%
  • Elicitation 100%
  • Domains 50%
  • User 50%
  • Optimization 50%

• Towards Improved Learning in Gaussian Processes: The Best of Two Worlds

  Li, R., John, T. & Solin, A., 2022.

  Research output: Contribution to conference › Paper › Scientific › peer-review

  Open Access

  • Inference 100%
  • Gaussian Process 100%
  • Learning 100%
  • Approximates 60%
  • Marginal Likelihood 40%
• 2021

  Evolving-Graph Gaussian Processes

  Blanco-Mulero, D., Heinonen, M. & Kyrki, V., Jul 2021. 6 p.

  Research output: Contribution to conference › Paper › Scientific › peer-review

  Open Access

  File

  • Gaussian Process 100%
  • Models 16%
  • Domains 16%
  • Application 16%
  • Connectivity 16%
  69 Downloads (Pure)
• 2019

  Interactive AI with a Theory of Mind

  Çelikok, M. M., Peltola, T., Daee, P. & Kaski, S., 2019. 6 p.

  Research output: Contribution to conference › Paper › Scientific › peer-review

  • Artificial Intelligence 100%
  • User 100%
  • Models 33%
  • Armed 33%
  • User Modeling 33%
• 2018

  Deep Transfer Learning of Representations for Differentially Private Learning

  Niinimäki, T., Heikkilä, M. A., Kaski, S. & Honkela, A., 2018.

  Research output: Contribution to conference › Paper › Scientific › peer-review

• Efficient Convex Completion of Coupled Tensors using Coupled Nuclear Norms

  Wimalawarne, K. & Mamitsuka, H., 2018, p. 6902-6910. 9 p.

  Research output: Contribution to conference › Paper › Scientific › peer-review

  • Nuclear Norm 100%
  • Models 66%
  • Simulation 33%
  • Optimization 33%
  3 Citations (Scopus)
• 2017

  ELFI, a software package for likelihood-free inference

  Lintusaari, J., Vuollekoski, H., Kangasrääsiö, A., Skyten, K., Järvenpää, M., Gutmann, M., Vehtari, A., Corander, J. & Kaski, S., 2017.

  Research output: Contribution to conference › Paper › Scientific