8 citations · 13 across the 7 of their papers we have counts for
3 papers · 1 filter
Energy-Based Modelling for Discrete and Mixed Data via Heat Equations on Structured Spaces
Tobias Schröder, Zijing Ou, Yingzhen Li +1
Energy-based models (EBMs) offer a flexible framework for probabilistic modelling across various data domains. However, training EBMs on data in discrete or mixed state spaces pose…
Identifying Nonstationary Causal Structures with High-Order Markov Switching Models
Carles Balsells-Rodas, Yixin Wang, Pedro A. M. Mediano +1
Causal discovery in time series is a rapidly evolving field with a wide variety of applications in other areas such as climate science and neuroscience. Traditional approaches assu…
Training Discrete Energy-Based Models with Energy Discrepancy
Tobias Schröder, Zijing Ou, Yingzhen Li +1
Training energy-based models (EBMs) on discrete spaces is challenging because sampling over such spaces can be difficult. We propose to train discrete EBMs with energy discrepancy…