A positivity robust strategy to study effects of switching treatment

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This thesis aimed to estimate the effect of demographic and biomechanical preoperative variables on total shoulder arthroplasty (TSA) outcomes. To achieve this, various biomechanical variables were calculated using a clinical database comprising normal and ...

Causal inference in a sub-population involves identifying the causal effect of an intervention on a specific subgroup, which is distinguished from the whole population through the influence of systematic biases in the sampling process. However, ignoring th ...

The transition to sustainable energy demands a fundamental redesign of the electrical grid, especially at the distribution level. With the increasing deployment of distributed energy resources, the development of reliable models, accurate state estimation ...

Defeasibility in causal reasoning implies that the causal relationship between cause and effect can be strengthened or weakened. Namely, the causal strength between cause and effect should increase or decrease with the incorporation of strengthening argume ...

This paper focuses on parameter estimation and introduces a new method for lower bounding the Bayesian risk. The method allows for the use of virtually any information measure, including Rényi's α, φ-divergences, and Sibson's α-Mutual Information. The appr ...

This thesis presents a comprehensive theory of information-theoretic measures for characterizing the complexity and higher-order dependence structures of graphs. We introduce multivariate complexity and dependence measures for graphs within the framework o ...

An a posteriori error estimator based on an equilibrated flux reconstruction is proposed for defeaturing problems in the context of finite element discretizations. Defeaturing consists in the simplification of a geometry by removing features that are consi ...

Understanding narratives requires reasoning about the cause-and-effect relationships between events mentioned in the text. While existing foundation models yield impressive results in many NLP tasks requiring reasoning, it is unclear whether they understan ...

Universal inference enables the construction of confidence intervals and tests without regularity conditions by splitting the data into two parts and appealing to Markov's inequality. Previous investigations have shown that the cost of this generality is a ...

Many scientific systems are studied using computer codes that simulate the phenomena of interest. Computer simulation enables scientists to study a broad range of possible conditions, generating large quantities of data at a faster rate than the laboratory ...

Many decisions rely on how we evaluate potential outcomes and estimate their corresponding probabilities of occurrence. Outcome evaluation is subjective because it requires consulting internal preferences and is sensitive to context. In contrast, probabili ...

The combination of Global Navigation Satellite Systems (GNSS) and Inertial Navigation System (INS) has become the baseline of many vehicular applications. However, in challenging GNSS scenarios, classical GNSS/INS integration estimators are very sensitive ...

Seismic exposure of buildings presents difficult engineering challenges. The principles of seismic design involve structures that sustain damage and still protect inhabitants. Precise and accurate knowledge of the residual capacity of damaged structures is ...

A positivity robust strategy to study effects of switching treatment

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Multimodal Prediction Framework for Total Shoulder Arthroplasty Outcomes: Integrating Morphological, Musculoskeletal, Finite Element, and Bayesian Causal Models

s-ID: Causal Effect Identification in a Sub-Population

Estimation and control under uncertainty with application to power systems

Exploring Defeasibility in Causal Reasoning

Lower Bounds on the Bayesian Risk via Information Measures

An Information-Theoretic Framework for Multiplex Graphs

An equilibrated flux a posteriori error estimator for defeaturing problems

CRAB: Assessing the Strength of Causal Relationships Between Real-World Events

On the logic of collapsibility for causal effect measures

A note on universal inference

Statistical Emulation of Neural Simulators: Application to Neocortical L2/3 Large Basket Cells

Context effects on probability estimation

Tightly Coupled GNSS/INS Integration based on Robust M-Estimators

Data-Interpretation methodologies for Non-Linear Earthquake Response Predictions of Damaged Structures