Learning continuous-time PDEs from sparse data with graph neural networks. - Valerii Iakovlev; Markus Heinonen; Harri Lähdesmäki (ICLR, 2021)

Latent Neural ODEs with Sparse Bayesian Multiple Shooting. - Valerii Iakovlev; Çagatay Yildiz; Markus Heinonen; Harri Lähdesmäki (ICLR, 2023)

Learning Space-Time Continuous Latent Neural PDEs from Partially Observed States. - Valerii Iakovlev; Markus Heinonen; Harri Lähdesmäki (NeurIPS, 2023)

Learning Space-Time Continuous Neural PDEs from Partially Observed States. - Valerii Iakovlev; Markus Heinonen; Harri Lähdesmäki (CoRR, 2023)

Field-based Molecule Generation. - Alexandru Dumitrescu; Dani Korpela; Markus Heinonen; Yogesh Verma; Valerii Iakovlev; Vikas Garg 001; Harri Lähdesmäki (CoRR, 2024)

Modeling Randomly Observed Spatiotemporal Dynamical Systems. - Valerii Iakovlev; Harri Lähdesmäki (CoRR, 2024)

E(3)-equivariant models cannot learn chirality: Field-based molecular generation. - Alexandru Dumitrescu; Dani Korpela; Markus Heinonen; Yogesh Verma; Valerii Iakovlev; Vikas Garg 001; Harri Lähdesmäki (ICLR, 2025)

Learning Spatiotemporal Dynamical Systems from Point Process Observations. - Valerii Iakovlev; Harri Lähdesmäki (ICLR, 2025)