← authors · overview

• Learning Large-Scale Bayesian Networks with the sparsebn Package
  2017
• DAGs with NO TEARS: Continuous Optimization for Structure Learning
  2018
• Learning Sparse Nonparametric DAGs
  2019
• DYNOTEARS: Structure Learning from Time-Series Data
  2020
• A polynomial-time algorithm for learning nonparametric causal graphs
  2020
• Structure learning in polynomial time: Greedy algorithms, Bregman information, and exponential families
  2021
• Efficient Bayesian network structure learning via local Markov boundary search
  2021
• NOTMAD: Estimating Bayesian Networks with Sample-Specific Structures and Parameters
  2021
• Optimal estimation of Gaussian DAG models
  2022
• Optimizing NOTEARS Objectives via Topological Swaps
  2023
• Learning nonparametric latent causal graphs with unknown interventions
  2023
• Inconsistency of cross-validation for structure learning in Gaussian graphical models
  2023
• Greedy equivalence search for nonparametric graphical models
  2024
• Markov Equivalence and Consistency in Differentiable Structure Learning
  2024
• Breaking the curse of dimensionality in structured density estimation
  2024