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Xiaoting Shao

2 accepted papers

2021

Right for Better Reasons: Training Differentiable Models by Constraining their Influence Functions

AAAI 2021technical

Explaining black-box models such as deep neural networks is becoming increasingly important as it helps to boost trust and debugging. Popular forms of explanations map the features to a vector indicating their individual importance to a decision on the instance-level. They can then be used to preven…

Cited by 38SourcePDFScholar
2019

Random Sum-Product Networks: A Simple and Effective Approach to Probabilistic Deep Learning

UAI 2019poster

Sum-product networks (SPNs) are expressive probabilistic models with a rich set of exact and efficient inference routines. However, in order to guarantee exact inference, they require specific structural constraints, which complicate learning SPNs from data. Thereby, most SPN structure learners prop…