14 citations · 21 across the 4 of their papers we have counts for
5 papers
Form follows Function: Text-to-Text Conditional Graph Generation based on Functional Requirements
Peter A. Zachares, Vahan Hovhannisyan, Alan Mosca +1
This work focuses on the novel problem setting of generating graphs conditioned on a description of the graph's functional requirements in a downstream task. We pose the problem as…
Tweedie Moment Projected Diffusions For Inverse Problems
Benjamin Boys, Mark Girolami, Jakiw Pidstrigach +3
Diffusion generative models unlock new possibilities for inverse problems as they allow for the incorporation of strong empirical priors in scientific inference. Recently, diffusio…
A Hybrid Model for Forecasting Short-Term Electricity Demand
Maria Eleni Athanasopoulou, Justina Deveikyte, Alan Mosca +2
Currently the UK Electric market is guided by load (demand) forecasts published every thirty minutes by the regulator. A key factor in predicting demand is weather conditions, with…
Deep Incremental Boosting
Alan Mosca, George D Magoulas
This paper introduces Deep Incremental Boosting, a new technique derived from AdaBoost, specifically adapted to work with Deep Learning methods, that reduces the required training…
Adapting Resilient Propagation for Deep Learning
Alan Mosca, George D. Magoulas
The Resilient Propagation (Rprop) algorithm has been very popular for backpropagation training of multilayer feed-forward neural networks in various applications. The standard Rpro…