6 citations · 7 across the 3 of their papers we have counts for
4 papers
CountsDiff: A Diffusion Model on the Natural Numbers for Generation and Imputation of Count-Based Data
Renzo G. Soatto, Anders Hoel, Greycen Ren +5
Diffusion models have excelled at generative tasks for both continuous and token-based domains, but their application to discrete ordinal data remains underdeveloped. We present Co…
Position: Bayesian Deep Learning is Needed in the Age of Large-Scale AI
Theodore Papamarkou, Maria Skoularidou, Konstantina Palla +22
In the current landscape of deep learning research, there is a predominant emphasis on achieving high predictive accuracy in supervised tasks involving large image and language dat…
Bayesian Context Trees: Modelling and exact inference for discrete time series
Ioannis Kontoyiannis, Lambros Mertzanis, Athina Panotopoulou +2
We develop a new Bayesian modelling framework for the class of higher-order, variable-memory Markov chains, and introduce an associated collection of methodological tools for exact…
Modeling Tabular data using Conditional GAN
Lei Xu, Maria Skoularidou, Alfredo Cuesta-Infante +1
Modeling the probability distribution of rows in tabular data and generating realistic synthetic data is a non-trivial task. Tabular data usually contains a mix of discrete and con…