Improved bounds and inference on optimal regimes

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Improved bounds and inference on optimal regimes

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Spectral Estimators for High-Dimensional Matrix Inference

OASIS: An integrated optimisation framework for activity scheduling

Bridging Bayesian and Minimax Mean Square Error Estimation via Wasserstein Distributionally Robust Optimization

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Filtered data and eigenfunction estimators for statistical inference of multiscale and interacting diffusion processes

Self-Exciting Point Processes: Identification and Control

Multi-Level Monte Carlo Methods for Uncertainty Quantification and Risk-Averse Optimisation

Sparsely Observed Functional Time Series: Theory and Applications

Unbiased Monte Carlo cluster updates with autoregressive neural networks

The KDD 2021 Workshop on Causal Discovery (CD2021)

Cumulants of Hawkes Processes are Robust to Observation Noise

Learning Linear Non-Gaussian Causal Models in the Presence of Latent Variables