Summary of An Explainablefair Framework For Prediction Of Substance Use Disorder Treatment Completion, by Mary M. Lucas et al.
An ExplainableFair Framework for Prediction of Substance Use Disorder Treatment Completionby Mary M. Lucas, Xiaoyang…
Summary of Countarfactuals — Generating Plausible Model-agnostic Counterfactual Explanations with Adversarial Random Forests, by Susanne Dandl et al.
CountARFactuals – Generating plausible model-agnostic counterfactual explanations with adversarial random forestsby Susanne Dandl, Kristin Blesch,…
Summary of Leveraging Interpolation Models and Error Bounds For Verifiable Scientific Machine Learning, by Tyler Chang and Andrew Gillette and Romit Maulik
Leveraging Interpolation Models and Error Bounds for Verifiable Scientific Machine Learningby Tyler Chang, Andrew Gillette,…
Summary of Machine Learning in Proton Exchange Membrane Water Electrolysis — Part I: a Knowledge-integrated Framework, by Xia Chen et al.
Machine Learning in Proton Exchange Membrane Water Electrolysis – Part I: A Knowledge-Integrated Frameworkby Xia…
Summary of Machine Learning Augmented Diagnostic Testing to Identify Sources Of Variability in Test Performance, by Christopher J. Banks et al.
Machine learning augmented diagnostic testing to identify sources of variability in test performanceby Christopher J.…
Summary of Cryptographic Hardness Of Score Estimation, by Min Jae Song
Cryptographic Hardness of Score Estimationby Min Jae SongFirst submitted to arxiv on: 4 Apr 2024CategoriesMain:…
Summary of Knowledge Distillation-based Model Extraction Attack Using Gan-based Private Counterfactual Explanations, by Fatima Ezzeddine et al.
Knowledge Distillation-Based Model Extraction Attack using GAN-based Private Counterfactual Explanationsby Fatima Ezzeddine, Omran Ayoub, Silvia…
Summary of On the Theoretical Expressive Power and the Design Space Of Higher-order Graph Transformers, by Cai Zhou et al.
On the Theoretical Expressive Power and the Design Space of Higher-Order Graph Transformersby Cai Zhou,…
Summary of Anova-boosting For Random Fourier Features, by Daniel Potts and Laura Weidensager
ANOVA-boosting for Random Fourier Featuresby Daniel Potts, Laura WeidensagerFirst submitted to arxiv on: 3 Apr…
Summary of Data-driven Goal Recognition Design For General Behavioral Agents, by Robert Kasumba et al.
Data-Driven Goal Recognition Design for General Behavioral Agentsby Robert Kasumba, Guanghui Yu, Chien-Ju Ho, Sarah…