Harri Lahdesmaki
17 papers · 2016–2025 · 5 venues · across top CS/AI venues
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Achievements
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🐣 Hot Topic Early Bird 🌍 Conference Polyglot · Silver 🏃 Academic Marathon · Sprint 🌉 Interdisciplinary Bridge · Bronze 🗺️ Taxonomy Completionist (22)
🧬
Topic Evolution
🤝
Dynamic Duo
(10)
🗃️
Keyword Collector
(69)
💎
Century Club · Bronze
🔥
Unstoppable · Bronze
Top co-authors
Research topics
Machine Learning
(14)
Deep Learning
(12)
Artificial Intelligence
(10)
Models
(9)
Core Methods
(8)
Optimization & Theory
(7)
Bayesian & Probabilistic · Artificial Intelligence
(6)
Architectures
(4)
Core AI
(4)
Bayesian & Probabilistic · Machine Learning
(2)
Healthcare & Medicine
(1)
Reinforcement Learning
(1)
Applications
(1)
Clinical
(1)
Learning Paradigms
(1)
Keywords
gaussian process
(6)
variational inference
(5)
variational autoencoder
(5)
bayesian neural network
(3)
amortized inference
(3)
ordinary differential equation
(3)
latent variable model
(2)
point process
(2)
multiple shooting
(2)
latent space
(2)
bayesian inference
(2)
graph neural network
(2)
dynamical system
(2)
generative model
(2)
partial differential equation
(2)
non-stationary modeling
(1)
nonparametric modeling
(1)
kl divergence
(1)
model-based reinforcement learning
(1)
gaussian processes
(1)
Papers
Bayesian Basis Function Approximation for Scalable Gaussian Process Priors in Deep Generative Models
ICML 2025
E(3)-equivariant models cannot learn chirality: Field-based molecular generation
ICLR 2025
High-Dimensional Bayesian Optimisation with Gaussian Process Prior Variational Autoencoders
ICLR 2025
Learning Spatiotemporal Dynamical Systems from Point Process Observations
ICLR 2025
Estimating treatment effects from single-arm trials via latent-variable modeling
AISTATS 2024
Latent variable model for high-dimensional point process with structured missingness
ICML 2024
Latent Neural ODEs with Sparse Bayesian Multiple Shooting
ICLR 2023
Learning Space-Time Continuous Latent Neural PDEs from Partially Observed States
NeurIPS 2023
Variational multiple shooting for Bayesian ODEs with Gaussian processes
UAI 2022
Continuous-time Model-based Reinforcement Learning
ICML 2021
Latent Gaussian process with composite likelihoods and numerical quadrature
AISTATS 2021
Learning continuous-time PDEs from sparse data with graph neural networks
ICLR 2021
Longitudinal Variational Autoencoder
AISTATS 2021
Deep learning with differential Gaussian process flows
AISTATS 2019
ODE2VAE: Deep generative second order ODEs with Bayesian neural networks
NeurIPS 2019
Learning unknown ODE models with Gaussian processes
ICML 2018
Non-Stationary Gaussian Process Regression with Hamiltonian Monte Carlo
AISTATS 2016