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Found 13 papers, 2 papers with code
Training LayoutLM from Scratch for Efficient Named-Entity Recognition in the Insurance Domain
Generic pre-trained neural networks may struggle to produce good results in specialized domains like finance and insurance.
Oops, I Sampled it Again: Reinterpreting Confidence Intervals in Few-Shot Learning
The predominant method for computing confidence intervals (CI) in few-shot learning (FSL) is based on sampling the tasks with replacement, i. e.\ allowing the same samples to appear in multiple tasks.
Time-changed normalizing flows for accurate SDE modeling
The generative paradigm has become increasingly important in machine learning and deep learning models.
Measuring and Mitigating Biases in Motor Insurance Pricing
The non-life insurance sector operates within a highly competitive and tightly regulated framework, confronting a pivotal juncture in the formulation of pricing strategies.
Geometry-preserving Lie Group Integrators For Differential Equations On The Manifold Of Symmetric Positive Definite Matrices
The application of Euclidean methods to integrate differential equations lying on such objects does not respect the geometry of the manifold, which can cause many numerical issues.
Evaluation of importance estimators in deep learning classifiers for Computed Tomography
Interestingly, there was a critical discrepancy between model-centric (fidelity) and human-centric (ROC and DSC) evaluation.
Model Transparency and Interpretability : Survey and Application to the Insurance Industry
The use of models, even if efficient, must be accompanied by an understanding at all levels of the process that transforms data (upstream and downstream).
Collaborative Insurance Sustainability and Network Structure
In this paper, describe and analyse such a P2P product, with some reciprocal risk sharing contracts.
Some Remarks on Replicated Simulated Annealing
Recently authors have introduced the idea of training discrete weights neural networks using a mix between classical simulated annealing and a replica ansatz known from the statistical physics literature.
Interpretabilité des modèles : état des lieux des méthodes et application à l'assurance
Models users must ensure that models do not discriminate against and that it is also possible to explain its result.
Towards an Intrinsic Definition of Robustness for a Classifier
The robustness of classifiers has become a question of paramount importance in the past few years.
Improving Accuracy of Nonparametric Transfer Learning via Vector Segmentation
Transfer learning using deep neural networks as feature extractors has become increasingly popular over the past few years.
Associative Memories to Accelerate Approximate Nearest Neighbor Search
In its canonical version, the complexity of the search is linear with both the dimension and the cardinal of the collection of vectors the search is performed in.
