Search Results for author: Benjie Wang

Found 9 papers, 6 papers with code

Neural Structure Learning with Stochastic Differential Equations

no code implementations6 Nov 2023 Benjie Wang, Joel Jennings, Wenbo Gong

Unfortunately, most existing structure learning approaches assume that the underlying process evolves in discrete-time and/or observations occur at regular time intervals.

Variational Inference

Provable Preimage Under-Approximation for Neural Networks (Full Version)

1 code implementation5 May 2023 Xiyue Zhang, Benjie Wang, Marta Kwiatkowska

Neural network verification mainly focuses on local robustness properties, which can be checked by bounding the image (set of outputs) of a given input set.

Compositional Probabilistic and Causal Inference using Tractable Circuit Models

1 code implementation17 Apr 2023 Benjie Wang, Marta Kwiatkowska

Probabilistic circuits (PCs) are a class of tractable probabilistic models, which admit efficient inference routines depending on their structural properties.

Causal Inference

Bayesian Network Models of Causal Interventions in Healthcare Decision Making: Literature Review and Software Evaluation

no code implementations28 Nov 2022 Artem Velikzhanin, Benjie Wang, Marta Kwiatkowska

After describing the search methodology, the selected research papers are briefly reviewed, with the view to identify publicly available models and datasets that are well suited to analysis using the causal interventional analysis software tool developed in Wang B, Lyle C, Kwiatkowska M (2021).

Decision Making

Robustness Guarantees for Credal Bayesian Networks via Constraint Relaxation over Probabilistic Circuits

1 code implementation11 May 2022 Hjalmar Wijk, Benjie Wang, Marta Kwiatkowska

In many domains, worst-case guarantees on the performance (e. g., prediction accuracy) of a decision function subject to distributional shifts and uncertainty about the environment are crucial.

Tractable Uncertainty for Structure Learning

no code implementations29 Apr 2022 Benjie Wang, Matthew Wicker, Marta Kwiatkowska

Bayesian structure learning allows one to capture uncertainty over the causal directed acyclic graph (DAG) responsible for generating given data.

Provable Guarantees on the Robustness of Decision Rules to Causal Interventions

1 code implementation19 May 2021 Benjie Wang, Clare Lyle, Marta Kwiatkowska

Robustness of decision rules to shifts in the data-generating process is crucial to the successful deployment of decision-making systems.

Decision Making

Statistically Robust Neural Network Classification

1 code implementation10 Dec 2019 Benjie Wang, Stefan Webb, Tom Rainforth

The SRR provides a distinct and complementary measure of robust performance, compared to natural and adversarial risk.

Classification General Classification

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