Neurosymbolic AI and ML
Enhancing Case-Based Reasoning with Neural Networks
David Leake, Zachary Wilkerson, Xiaomeng Ye, David J. Crandall
Compendium of Neurosymbolic Artificial Intelligence 2023
[paper]
Compendium of Neurosymbolic Artificial Intelligence 2023
[paper]
Generation and Evaluation of Creative Images from Limited Data: A Class-to-Class VAE Approach
Generating Counterfactual Images: Toward a C2C-VAE Approach
Ziwei Zhao, David Leake, Xiaomeng Ye, David Crandall
ICCBR Workshop on CBR for Explanation of Intelligent Systems 2022
[paper]
ICCBR Workshop on CBR for Explanation of Intelligent Systems 2022
[paper]
Controlling the Quality of Distillation in Response-Based Network Compression
Vibhas Vats, David Crandall
AAAI International Workshop on Practical Deep Learning in the Wild 2022
[paper]
AAAI International Workshop on Practical Deep Learning in the Wild 2022
[paper]
Genetic-GAN: Synthesizing images between two domains by genetic crossover
Bringing Case Based Reasoning to Deep Learning
David Leake, David Crandall
International Conference on Case-Based Reasoning Special Track on Challenges and Promises 2020
[paper]
International Conference on Case-Based Reasoning Special Track on Challenges and Promises 2020
[paper]
Stochastic Multiple Choice Learning for Training Diverse Deep Ensembles
Stefan Lee, Senthil Purushwalkam, Michael Cogswell, Viresh Ranjan, David Crandall, Dhruv Batra
NeurIPS 2016
[paper]
NeurIPS 2016
[paper]