Harri Lhdesmki
Publication record assembled from the DBLP archive of ranked conferences.
Papers indexed
17
Venues
6
Active years
2003–2025
Best venue rank
A*
Where they publish
Papers
17 indexed papers, newest first.
| Year | Venue | Title | Authors |
|---|---|---|---|
| 2025 | ICLR | E(3)-equivariant models cannot learn chirality: Field-based molecular generation. | Alexandru Dumitrescu, Dani Korpela, Markus Heinonen, Yogesh Verma, Valerii Iakovlev, Vikas Garg, Harri Lhdesmki |
| 2025 | ICLR | Learning Spatiotemporal Dynamical Systems from Point Process Observations. | Valerii Iakovlev, Harri Lhdesmki |
| 2025 | ICLR | High-Dimensional Bayesian Optimisation with Gaussian Process Prior Variational Autoencoders. | Siddharth Ramchandran, Manuel Haussmann, Harri Lhdesmki |
| 2025 | ICML | Bayesian Basis Function Approximation for Scalable Gaussian Process Priors in Deep Generative Models. | Mehmet Yigit Balik, Maksim Sinelnikov, Priscilla Ong, Harri Lhdesmki |
| 2024 | AISTATS | 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 Lhdesmki |
| 2024 | ICML | Latent variable model for high-dimensional point process with structured missingness. | Maksim Sinelnikov, Manuel Haussmann, Harri Lhdesmki |
| 2023 | ICLR | Latent Neural ODEs with Sparse Bayesian Multiple Shooting. | Valerii Iakovlev, agatay Yildiz, Markus Heinonen, Harri Lhdesmki |
| 2022 | ICMLA | A Variational Autoencoder for Heterogeneous Temporal and Longitudinal Data. | Mine gretir, Siddharth Ramchandran, Dimitrios Papatheodorou, Harri Lhdesmki |
| 2022 | UAI | Variational multiple shooting for Bayesian ODEs with Gaussian processes. | Pashupati Hegde, agatay Yildiz, Harri Lhdesmki, Samuel Kaski, Markus Heinonen |
| 2021 | AISTATS | Latent Gaussian process with composite likelihoods and numerical quadrature. | Siddharth Ramchandran, Miika Koskinen, Harri Lhdesmki |
| 2021 | AISTATS | Longitudinal Variational Autoencoder. | Siddharth Ramchandran, Gleb Tikhonov, Kalle Kujanp, Miika Koskinen, Harri Lhdesmki |
| 2021 | ICLR | Learning continuous-time PDEs from sparse data with graph neural networks. | Valerii Iakovlev, Markus Heinonen, Harri Lhdesmki |
| 2021 | ICML | Continuous-time Model-based Reinforcement Learning. | agatay Yildiz, Markus Heinonen, Harri Lhdesmki |
| 2019 | AISTATS | Deep learning with differential Gaussian process flows. | Pashupati Hegde, Markus Heinonen, Harri Lhdesmki, Samuel Kaski |
| 2018 | ICML | Learning unknown ODE models with Gaussian processes. | Markus Heinonen, agatay Yildiz, Henrik Mannerstrm, Jukka Intosalmi, Harri Lhdesmki |
| 2016 | AISTATS | Non-Stationary Gaussian Process Regression with Hamiltonian Monte Carlo. | Markus Heinonen, Henrik Mannerstrm, Juho Rousu, Samuel Kaski, Harri Lhdesmki |
| 2003 | SDM | Detecting Periodicity in Nonideal Datasets. | Ronald K. Pearson, Harri Lhdesmki, Heikki Huttunen, Olli Yli-Harja |