Theodoros Damoulas
27 papers · 2018–2025 · 7 conferences · across top CS/AI conferences
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(7)
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(11)
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(27)
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Conferences
NIPS (11)
AISTATS (6)
ICML (5)
CLEAR (2)
IJCAI (1)
JMLR (1)
UAI (1)
Top co-authors
Keywords
gaussian process
(9)
variational inference
(8)
bayesian inference
(6)
causal abstraction
(3)
kernel methods
(3)
multi-task learning
(3)
causal inference
(3)
state-space model
(3)
structural causal model
(3)
interventional datum
(2)
causal discovery
(2)
bayesian optimization
(2)
probabilistic modeling
(2)
signature kernel
(2)
maximum mean discrepancy
(2)
time series
(2)
sparse approximation
(2)
robust inference
(2)
stochastic process
(2)
sequential datum
(2)
Papers
Federated Generalised Variational Inference: A Robust Probabilistic Federated Learning Framework
ICML 2025
Decision Making under the Exponential Family: Distributionally Robust Optimisation with Bayesian Ambiguity Sets
ICML 2025
Causally Abstracted Multi-armed Bandits
UAI 2024
Interventionally Consistent Surrogates for Complex Simulation Models
NIPS 2024
Physics-Informed Variational State-Space Gaussian Processes
NIPS 2024
Generating Origin-Destination Matrices in Neural Spatial Interaction Models
NIPS 2024
Causal Optimal Transport of Abstractions
CLEAR 2024
Quantifying Consistency and Information Loss for Causal Abstraction Learning
IJCAI 2023
Causal Entropy Optimization
AISTATS 2023
Jointly Learning Consistent Causal Abstractions Over Multiple Interventional Distributions
CLEAR 2023
Robust Bayesian Inference for Simulator-based Models via the MMD Posterior Bootstrap
AISTATS 2022
An Optimization-centric View on Bayes' Rule: Reviewing and Generalizing Variational Inference
JMLR 2022
Probabilistic Sequential Matrix Factorization
AISTATS 2021
Dynamic Causal Bayesian Optimization
NIPS 2021
Higher Order Kernel Mean Embeddings to Capture Filtrations of Stochastic Processes
NIPS 2021
Spatio-Temporal Variational Gaussian Processes
NIPS 2021
Transforming Gaussian Processes With Normalizing Flows
AISTATS 2021
Distribution Regression for Sequential Data
AISTATS 2021
SigGPDE: Scaling Sparse Gaussian Processes on Sequential Data
ICML 2021
Non-separable Non-stationary random fields
ICML 2020
Multi-task Causal Learning with Gaussian Processes
NIPS 2020
Generalised Bayesian Filtering via Sequential Monte Carlo
NIPS 2020
Structured Variational Inference in Continuous Cox Process Models
NIPS 2019
Multi-resolution Multi-task Gaussian Processes
NIPS 2019
Efficient Inference in Multi-task Cox Process Models
AISTATS 2019
Doubly Robust Bayesian Inference for Non-Stationary Streaming Data with $\beta$-Divergences
NIPS 2018
Spatio-temporal Bayesian On-line Changepoint Detection with Model Selection
ICML 2018