Theodoros Damoulas
27 papers · 2018–2025 · 7 venues · across top CS/AI venues
Authors are matched by name, so researchers who share a name ("Yang Liu", "Wei Wang") appear as a single profile and their paper counts, venues and achievements are combined. How identity is handled.
Achievements
Jump to papers ↓+7 more ↓ Show less ↑
πΊοΈ Taxonomy Completionist (31) π Academic Marathon Β· Sprint π Conference Polyglot Β· Silver π Interdisciplinary Bridge Β· Silver π£ Hot Topic Early Bird
π¬
Deep Specialist
(14)
π
Keyword Champion
(2)
π
Trend Setter
π₯
Unstoppable Β· Bronze
β‘
Prolific Year Β· Productive
π
Century Club Β· Bronze
ποΈ
Keyword Collector
(99)
Top co-authors
Research topics
Machine Learning
(22)
Artificial Intelligence
(19)
Optimization & Theory
(18)
Bayesian & Probabilistic Β· Artificial Intelligence
(12)
Core AI
(7)
Learning Types
(7)
Bayesian & Probabilistic Β· Machine Learning
(6)
Core Methods
(6)
Deep Learning
(5)
Mathematics & Optimization
(5)
Data Science & Analytics
(4)
Methods
(4)
Models
(4)
Mathematics
(3)
Optimization
(3)
Keywords
gaussian process
(9)
variational inference
(9)
bayesian inference
(6)
causal inference
(4)
state space model
(4)
causal abstraction
(4)
structural causal model
(3)
multi-task learning
(3)
kernel methods
(3)
interventional data
(2)
sequential data
(2)
maximum mean discrepancy
(2)
probabilistic modeling
(2)
signature kernel
(2)
stochastic process
(2)
bayesian optimization
(2)
causal discovery
(2)
robust inference
(2)
time series
(2)
sparse approximation
(2)
Papers
Decision Making under the Exponential Family: Distributionally Robust Optimisation with Bayesian Ambiguity Sets
ICML 2025
Federated Generalised Variational Inference: A Robust Probabilistic Federated Learning Framework
ICML 2025
Causally Abstracted Multi-armed Bandits
UAI 2024
Causal Optimal Transport of Abstractions
CLeaR 2024
Generating Origin-Destination Matrices in Neural Spatial Interaction Models
NeurIPS 2024
Interventionally Consistent Surrogates for Complex Simulation Models
NeurIPS 2024
Physics-Informed Variational State-Space Gaussian Processes
NeurIPS 2024
Causal Entropy Optimization
AISTATS 2023
Jointly Learning Consistent Causal Abstractions Over Multiple Interventional Distributions
CLeaR 2023
Quantifying Consistency and Information Loss for Causal Abstraction Learning
IJCAI 2023
An Optimization-centric View on Bayes' Rule: Reviewing and Generalizing Variational Inference
JMLR 2022
Robust Bayesian Inference for Simulator-based Models via the MMD Posterior Bootstrap
AISTATS 2022
Distribution Regression for Sequential Data
AISTATS 2021
Dynamic Causal Bayesian Optimization
NeurIPS 2021
Higher Order Kernel Mean Embeddings to Capture Filtrations of Stochastic Processes
NeurIPS 2021
Probabilistic Sequential Matrix Factorization
AISTATS 2021
SigGPDE: Scaling Sparse Gaussian Processes on Sequential Data
ICML 2021
Spatio-Temporal Variational Gaussian Processes
NeurIPS 2021
Transforming Gaussian Processes With Normalizing Flows
AISTATS 2021
Generalised Bayesian Filtering via Sequential Monte Carlo
NeurIPS 2020
Multi-task Causal Learning with Gaussian Processes
NeurIPS 2020
Non-separable Non-stationary random fields
ICML 2020
Efficient Inference in Multi-task Cox Process Models
AISTATS 2019
Multi-resolution Multi-task Gaussian Processes
NeurIPS 2019
Structured Variational Inference in Continuous Cox Process Models
NeurIPS 2019
Doubly Robust Bayesian Inference for Non-Stationary Streaming Data with Ξ²-Divergences
NeurIPS 2018
Spatio-temporal Bayesian On-line Changepoint Detection with Model Selection
ICML 2018