People

Markus Heinonen

Academy Research Fellow
Academy Research Fellow
T313 Dept. Computer Science
Full researcher profile
https://research.aalto.fi/...
Email
[email protected]
Phone number
+358442942600

Research groups

  • Probabilistic Machine Learning, Academy Research Fellow
  • Professorship Lähdesmäki Harri, Academy Research Fellow

Publications

Continuous-Time Functional Diffusion Processes

Giulio Franzese, Giulio Corallo, Simone Rossi, Markus Heinonen, Maurizio Filippone, Pietro Michiardi 2024 Advances in Neural Information Processing Systems 36 (NeurIPS 2023)

Learning Space-Time Continuous Latent Neural PDEs from Partially Observed States

Valerii Iakovlev, Markus Heinonen, Harri Lähdesmäki 2024 Advances in Neural Information Processing Systems 36 (NeurIPS 2023)

Balancing Imbalanced Toxicity Models : Using MolBERT with Focal Loss

Muhammad Arslan Masood, Samuel Kaski, Hugo Ceulemans, Dorota Herman, Markus Heinonen 2024 AI in Drug Discovery - 1st International Workshop, AIDD 2024, Held in Conjunction with ICANN 2024, Proceedings

Towards Interpretable Models of Chemist Preferences for Human-in-the-Loop Assisted Drug Discovery

Yasmine Nahal, Markus Heinonen, Mikhail Kabeshov, Jon Paul Janet, Eva Nittinger, Ola Engkvist, Samuel Kaski 2024 AI in Drug Discovery - 1st International Workshop, AIDD 2024, Held in Conjunction with ICANN 2024, Proceedings

Input-gradient space particle inference for neural network ensembles

Trung Trinh, Markus Heinonen, Luigi Acerbi, Samuel Kaski 2024 The Twelfth International Conference on Learning Representations

ClimODE: Climate and Weather Forecasting with Physics-informed Neural ODEs

Yogesh Verma, Markus Heinonen, Vikas Garg 2024 The Twelfth International Conference on Learning Representations

TCRconv: predicting recognition between T cell receptors and epitopes using contextualized motifs

Emmi Jokinen, Alexandru Dumitrescu, Jani Huuhtanen, Vladimir Gligorijevic, Satu Mustjoki, Richard Bonneau, Markus Heinonen, Harri Lähdesmäki 2023 Bioinformatics

Chemistry-Based Modeling on Phenotype-Based Drug-Induced Liver Injury Annotation : From Public to Proprietary Data

Mohammad Moein, Markus Heinonen, Natalie Mesens, Ronnie Chamanza, Chidozie Amuzie, Yvonne Will, Hugo Ceulemans, Samuel Kaski, Dorota Herman 2023 Chemical Research in Toxicology

Incorporating functional summary information in Bayesian neural networks using a Dirichlet process likelihood approach

Vishnu Raj, Tianyu Cui, Markus Heinonen, Pekka Marttinen 2023 Proceedings of The 26th International Conference on Artificial Intelligence and Statistics (AISTATS) 2023

Generative Modelling with Inverse Heat Dissipation

Severi Rissanen, Markus Heinonen, Arno Solin 2023