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cs.LG2023
Interacting Diffusion Processes for Event Sequence Forecasting
Mai Zeng, Florence Regol, Mark Coates
Neural Temporal Point Processes (TPPs) have emerged as the primary framework for predicting sequences of events that occur at irregular time intervals, but their sequential nature…
cs.LG2023
Jointly-Learned Exit and Inference for a Dynamic Neural Network : JEI-DNN
Florence Regol, Joud Chataoui, Mark Coates
Large pretrained models, coupled with fine-tuning, are slowly becoming established as the dominant architecture in machine learning. Even though these models offer impressive perfo…
cs.LG2023
Diffusing Gaussian Mixtures for Generating Categorical Data
Florence Regol, Mark Coates
Learning a categorical distribution comes with its own set of challenges. A successful approach taken by state-of-the-art works is to cast the problem in a continuous domain to tak…