See my publications on my Google Scholar page.

Journal publications:

[JMLR, 2024] ‘Experimental Design for Causal Effect Identification’ just accepted to appear in Journal of Machine Learning Research (JMLR) special issue for ICML&NeurIPS outstanding papers.

[TMLR, 2023] ‘A Free Lunch with Influence Functions? An Empirical Eval- uation of Influence Functions for Average Treatment Effect Estimation’

[JMLR, 2021] ‘A Recursive Markov Boundary-Based Approach to Causal Structure Learning’

Conference publications:

[NeurIPS, 2024] ‘Fast Proxy Experiment Design for Causal Effect Identification’ to appear at NeurIPS 2024.

[ICML, 2024, SPOTLIGHT] ‘Triple changes estimator for targeted policies’

[NeurIPs, 2023] ‘Causal effect identification in uncertain causal networks’

[NeurIPS, 2023] ‘Causal imitability under context-specific independence relations’

[ICML, 2022, ORALOutstanding paper runner up award] ‘Minimm-cost Intervention Design for Causal Effect Identification’.

[AAAI, 2022] ‘Learning Bayesian Networks in the Presence of Structural Side Information’

[NeurIPS, 2021] ‘Recursive Causal Structure Learning in the Presence of Latent Variables and Selection Bias’.

Workshop Publications:

[NeurIPS, 2023 – workshop on Optimal Transport and Machine Learning (OTML)] ‘Causal Discovery via Monotone Triangular Transport Maps’

Under Review:

[JMLR, 2024] ‘Recursive Causal Discovery’