Florence Regol

According to our database, Florence Regol authored at least 15 papers between 2019 and 2023.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2023

Interacting Diffusion Processes for Event Sequence Forecasting.

Mai Zeng, Florence Regol, Mark Coates

CoRR, 2023

Jointly-Learned Exit and Inference for a Dynamic Neural Network : JEI-DNN.

Florence Regol, Joud Chataoui, Mark Coates

CoRR, 2023

Evaluation of Categorical Generative Models - Bridging the Gap Between Real and Synthetic Data.

Florence Regol, Anja Kroon, Mark Coates

Proceedings of the IEEE International Conference on Acoustics, 2023

Diffusing Gaussian Mixtures for Generating Categorical Data.

Florence Regol, Mark Coates

Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022

Node copying: A random graph model for effective graph sampling.

Florence Regol, Soumyasundar Pal, Jianing Sun, Yingxue Zhang, Yanhui Geng, Mark Coates

Signal Process., 2022

Contrastive Learning for Time Series on Dynamic Graphs.

Yitian Zhang, Florence Regol, Antonios Valkanas, Mark Coates

Proceedings of the 30th European Signal Processing Conference, 2022

Bag Graph: Multiple Instance Learning Using Bayesian Graph Neural Networks.

Soumyasundar Pal, Antonios Valkanas, Florence Regol, Mark Coates

Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

2021

Detection and Defense of Topological Adversarial Attacks on Graphs.

Yingxue Zhang, Florence Regol, Soumyasundar Pal, Sakif Khan, Liheng Ma, Mark Coates

Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

2020

Non Parametric Graph Learning for Bayesian Graph Neural Networks.

Soumyasundar Pal, Saber Malekmohammadi, Florence Regol, Yingxue Zhang, Yishi Xu, Mark Coates

Proceedings of the Thirty-Sixth Conference on Uncertainty in Artificial Intelligence, 2020

A Framework for Recommending Accurate and Diverse Items Using Bayesian Graph Convolutional Neural Networks.

Jianing Sun, Wei Guo, Dengcheng Zhang, Yingxue Zhang, Florence Regol, Yaochen Hu, Huifeng Guo, Ruiming Tang, Han Yuan, Xiuqiang He, Mark Coates

Proceedings of the KDD '20: The 26th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2020

Active Learning on Attributed Graphs via Graph Cognizant Logistic Regression and Preemptive Query Generation.

Florence Regol, Soumyasundar Pal, Yingxue Zhang, Mark Coates

Proceedings of the 37th International Conference on Machine Learning, 2020

Learning from Networks of Distributions.

Antonios Valkanas, Florence Regol, Mark Coates

Proceedings of the 54th Asilomar Conference on Signals, Systems, and Computers, 2020

2019

Bayesian Graph Convolutional Neural Networks using Node Copying.

Soumyasundar Pal, Florence Regol, Mark Coates

CoRR, 2019

Bayesian Graph Convolutional Neural Networks Using Non-Parametric Graph Learning.

Soumyasundar Pal, Florence Regol, Mark J. Coates

CoRR, 2019

Node Copying for Protection Against Graph Neural Network Topology Attacks.

Florence Regol, Soumyasundar Pal, Mark Coates

Proceedings of the 8th IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, 2019