| 2022 | UAI | Greedy relaxations of the sparsest permutation algorithm. | Wai-Yin Lam, Bryan Andrews, Joseph D. Ramsey |
| 2021 | EDM | Affect, Support and Personal Factors: Multimodal Causal Models of One-on-one Coaching. | Lujie Karen Chen, Joseph D. Ramsey, Artur Dubrawski |
| 2019 | KDD | Learning High-dimensional Directed Acyclic Graphs with Mixed Data-types. | Bryan Andrews, Joseph D. Ramsey, Gregory F. Cooper |
| 2018 | UAI | Causal Discovery with Linear Non-Gaussian Models under Measurement Error: Structural Identifiability Results. | Kun Zhang, Mingming Gong, Joseph D. Ramsey, Kayhan Batmanghelich, Peter Spirtes, Clark Glymour |
| 2016 | KDD | Causal Clustering for 1-Factor Measurement Models. | Erich Kummerfeld, Joseph D. Ramsey |
| 2016 | UAI | Measurement Error and Causal Discovery. | Richard Scheines, Joseph D. Ramsey |
| 2008 | UAI | Causal discovery of linear acyclic models with arbitrary distributions. | Patrik O. Hoyer, Aapo Hyvrinen, Richard Scheines, Peter Spirtes, Joseph D. Ramsey, Gustavo Lacerda, Shohei Shimizu |
| 2008 | UAI | Discovering Cyclic Causal Models by Independent Components Analysis. | Gustavo Lacerda, Peter Spirtes, Joseph D. Ramsey, Patrik O. Hoyer |
| 2006 | UAI | Adjacency-Faithfulness and Conservative Causal Inference. | Joseph D. Ramsey, Jiji Zhang, Peter Spirtes |