Preserving Causal Constraints in Counterfactual Explanations for Machine Learning Classifiers. - Divyat Mahajan; Chenhao Tan; Amit Sharma 007 (CoRR, 2019)

A Generative Framework for Zero-Shot Learning with Adversarial Domain Adaptation. - Varun Khare; Divyat Mahajan; Homanga Bharadhwaj; Vinay Kumar Verma; Piyush Rai (WACV, 2020)

Towards Unifying Feature Attribution and Counterfactual Explanations: Different Means to the Same End. - Ramaravind Kommiya Mothilal; Divyat Mahajan; Chenhao Tan; Amit Sharma 007 (AIES, 2021)

Domain Generalization using Causal Matching. - Divyat Mahajan; Shruti Tople; Amit Sharma 007 (ICML, 2021)

Split-Treatment Analysis to Rank Heterogeneous Causal Effects for Prospective Interventions. - Yanbo Xu; Divyat Mahajan; Liz Manrao; Amit Sharma 007; Emre Kiciman (WSDM, 2021)

The Connection between Out-of-Distribution Generalization and Privacy of ML Models. - Divyat Mahajan; Shruti Tople; Amit Sharma 007 (CoRR, 2021)

Towards efficient representation identification in supervised learning. - Kartik Ahuja; Divyat Mahajan; Vasilis Syrgkanis; Ioannis Mitliagkas (CLeaR, 2022)

Empirical Analysis of Model Selection for Heterogenous Causal Effect Estimation. - Divyat Mahajan; Ioannis Mitliagkas; Brady Neal; Vasilis Syrgkanis (CoRR, 2022)

Synergies Between Disentanglement and Sparsity: a Multi-Task Learning Perspective. - Sébastien Lachapelle; Tristan Deleu; Divyat Mahajan; Ioannis Mitliagkas; Yoshua Bengio; Simon Lacoste-Julien; Quentin Bertrand (CoRR, 2022)

Interventional Causal Representation Learning. - Kartik Ahuja; Divyat Mahajan; Yixin Wang; Yoshua Bengio (ICML, 2023)

Synergies between Disentanglement and Sparsity: Generalization and Identifiability in Multi-Task Learning. - Sébastien Lachapelle; Tristan Deleu; Divyat Mahajan; Ioannis Mitliagkas; Yoshua Bengio; Simon Lacoste-Julien; Quentin Bertrand (ICML, 2023)

Additive Decoders for Latent Variables Identification and Cartesian-Product Extrapolation. - Sébastien Lachapelle; Divyat Mahajan; Ioannis Mitliagkas; Simon Lacoste-Julien (NeurIPS, 2023)

Empirical Analysis of Model Selection for Heterogeneous Causal Effect Estimation. - Divyat Mahajan; Ioannis Mitliagkas; Brady Neal; Vasilis Syrgkanis (ICLR, 2024)

Evaluating Interventional Reasoning Capabilities of Large Language Models. - Tejas Kasetty; Divyat Mahajan; Gintare Karolina Dziugaite; Alexandre Drouin; Dhanya Sridhar (CoRR, 2024)

Zero-Shot Learning of Causal Models. - Divyat Mahajan; Jannes Gladrow; Agrin Hilmkil; Cheng Zhang 005; Meyer Scetbon (CoRR, 2024)

Compositional Risk Minimization. - Divyat Mahajan; Mohammad Pezeshki; Ioannis Mitliagkas; Kartik Ahuja; Pascal Vincent (CoRR, 2024)

Learning to Defer for Causal Discovery with Imperfect Experts. - Oscar Clivio; Divyat Mahajan; Perouz Taslakian; Sara Magliacane; Ioannis Mitliagkas; Valentina Zantedeschi; Alexandre Drouin (CoRR, 2025)

Path-specific effects for pulse-oximetry guided decisions in critical care. - Kevin Zhang; Yonghan Jung; Divyat Mahajan; Karthikeyan Shanmugam; Shalmali Joshi (CoRR, 2025)