Estimating Causal Effects with Ancestral Graph Markov Models. - Daniel Malinsky; Peter Spirtes (Probabilistic Graphical Models, 2016)

Estimating bounds on causal effects in high-dimensional and possibly confounded systems. - Daniel Malinsky; Peter Spirtes (Int. J. Approx. Reason., 2017)

Causal Structure Learning from Multivariate Time Series in Settings with Unmeasured Confounding. - Daniel Malinsky; Peter Spirtes (CD@KDD, 2018)

Causal Learning for Partially Observed Stochastic Dynamical Systems. - Søren Wengel Mogensen; Daniel Malinsky; Niels Richard Hansen (UAI, 2018)

Intervening on structure. - Daniel Malinsky (Synth., 2018)

A Potential Outcomes Calculus for Identifying Conditional Path-Specific Effects. - Daniel Malinsky; Ilya Shpitser; Thomas S. Richardson 001 (AISTATS, 2019)

Learning the Structure of a Nonstationary Vector Autoregression. - Daniel Malinsky; Peter Spirtes (AISTATS, 2019)

Learning Optimal Fair Policies. - Razieh Nabi; Daniel Malinsky; Ilya Shpitser (ICML, 2019)

Causal Inference Under Interference And Network Uncertainty. - Rohit Bhattacharya; Daniel Malinsky; Ilya Shpitser (UAI, 2019)

Differentiable Causal Discovery Under Unmeasured Confounding. - Rohit Bhattacharya; Tushar Nagarajan; Daniel Malinsky; Ilya Shpitser (AISTATS, 2021)

Optimal Training of Fair Predictive Models. - Razieh Nabi; Daniel Malinsky; Ilya Shpitser (CLeaR, 2022)

Causal inference with outcome-dependent missingness and self-censoring. - Jacob M. Chen; Daniel Malinsky; Rohit Bhattacharya (UAI, 2023)

Corrigendum to "Estimating bounds on causal effects in high-dimensional and possibly confounded systems" [Int. J. Approx. Reason. 88 (2017) 371-384]. - Daniel Malinsky; Peter Spirtes (Int. J. Approx. Reason., 2025)

AI as an intervention: improving clinical outcomes relies on a causal approach to AI development and validation. - Shalmali Joshi; Iñigo Urteaga; Wouter A. C. van Amsterdam; George Hripcsak; Pierre A. Elias; Benjamin R. C. Amor; Noémie Elhadad; James C. Fackler; Mark P. Sendak; Jenna Wiens; Kaivalya Deshpande; Yoav Wald; et al. (J. Am. Medical Informatics Assoc., 2025)

Explaining the Behavior of Black-Box Prediction Algorithms with Causal Learning. - Numair Sani; Daniel Malinsky; Ilya Shpitser (Trans. Mach. Learn. Res., 2025)

Bridging Prediction and Intervention Problems in Social Systems. - Lydia T. Liu; Inioluwa Deborah Raji; Angela Zhou; Luke Guerdan; Jessica Hullman; Daniel Malinsky; Bryan Wilder; Simone Zhang; Hammaad Adam; Amanda Coston; Benjamin Laufer; Ezinne Nwankwo; et al. (CoRR, 2025)