Mark Hobbs

Publication Activity (10 Years)

Years Active: 2020-2024
Publications (10 Years): 8

Top Topics

Machine Learning

Supervised Classification

Top Venues

Canadian Conference on AI

Publications

Greg Lee, Aishwarya Vaishali Sathyamurthi, Mark Hobbs
Predicting Major Donor Prospects Using Machine Learning. ICAART (2) (2024)
Saurabh Deshpande, Hussein Rappel, Mark Hobbs, Stéphane P. A. Bordas, Jakub Lengiewicz
Gaussian process regression + deep neural network autoencoder for probabilistic surrogate modeling in nonlinear mechanics of solids. CoRR (2024)
Greg Lee, Ajith Kumar Veera Raghavan, Mark Hobbs
Adding Time and Subject Line Features to the Donor Journey. ICAART (2) (2023)
Greg Lee, Ajith Kumar Veera Raghavan, Mark Hobbs
Effects of Feature Types on Donor Journey. ICAART (Revised Selected Paper) (2023)
Greg Lee, Jordan Pippy, Mark Hobbs
Optimizing the Feature Set for Machine Learning Charitable Predictions. AI (2022)
Mark Hobbs, Hussein Rappel, Tim J. Dodwell
A probabilistic peridynamic framework with an application to the study of the statistical size effect. CoRR (2022)
Greg Lee, Ajith Kumar Veera Raghavan, Mark Hobbs
Machine Learning the Donor Journey. Canadian Conference on AI (2020)
Greg Lee, Ajith Kumar Veera Raghavan, Mark Hobbs
Improving the Donor Journey with Convolutional and Recurrent Neural Networks. ICMLA (2020)