Divyat Mahajan

Publication Activity (10 Years)

Years Active: 2019-2024
Publications (10 Years): 21

Top Topics

Empirical Analysis

Latent Variables

Model Selection

Conditionally Independent

Top Venues

Publications

Tejas Kasetty, Divyat Mahajan, Gintare Karolina Dziugaite, Alexandre Drouin, Dhanya Sridhar
Evaluating Interventional Reasoning Capabilities of Large Language Models. CoRR (2024)
Divyat Mahajan, Ioannis Mitliagkas, Brady Neal, Vasilis Syrgkanis
Empirical Analysis of Model Selection for Heterogeneous Causal Effect Estimation. ICLR (2024)
Sébastien Lachapelle, Divyat Mahajan, Ioannis Mitliagkas, Simon Lacoste-Julien
Additive Decoders for Latent Variables Identification and Cartesian-Product Extrapolation. CoRR (2023)
Sébastien Lachapelle, Divyat Mahajan, Ioannis Mitliagkas, Simon Lacoste-Julien
Additive Decoders for Latent Variables Identification and Cartesian-Product Extrapolation. NeurIPS (2023)
Kartik Ahuja, Divyat Mahajan, Yixin Wang, Yoshua Bengio
Interventional Causal Representation Learning. ICML (2023)
Sébastien Lachapelle, Tristan Deleu, Divyat Mahajan, Ioannis Mitliagkas, Yoshua Bengio, Simon Lacoste-Julien, Quentin Bertrand
Synergies between Disentanglement and Sparsity: Generalization and Identifiability in Multi-Task Learning. ICML (2023)
Divyat Mahajan, Ioannis Mitliagkas, Brady Neal, Vasilis Syrgkanis
Empirical Analysis of Model Selection for Heterogenous Causal Effect Estimation. CoRR (2022)
Kartik Ahuja, Yixin Wang, Divyat Mahajan, Yoshua Bengio
Interventional Causal Representation Learning. CoRR (2022)
Kartik Ahuja, Divyat Mahajan, Vasilis Syrgkanis, Ioannis Mitliagkas
Towards efficient representation identification in supervised learning. CLeaR (2022)
Sébastien Lachapelle, Tristan Deleu, Divyat Mahajan, Ioannis Mitliagkas, Yoshua Bengio, Simon Lacoste-Julien, Quentin Bertrand
Synergies Between Disentanglement and Sparsity: a Multi-Task Learning Perspective. CoRR (2022)
Kartik Ahuja, Divyat Mahajan, Vasilis Syrgkanis, Ioannis Mitliagkas
Towards efficient representation identification in supervised learning. CoRR (2022)
Ramaravind Kommiya Mothilal, Divyat Mahajan, Chenhao Tan, Amit Sharma
Towards Unifying Feature Attribution and Counterfactual Explanations: Different Means to the Same End. AIES (2021)
Divyat Mahajan, Shruti Tople, Amit Sharma
Domain Generalization using Causal Matching. ICML (2021)
Yanbo Xu, Divyat Mahajan, Liz Manrao, Amit Sharma, Emre Kiciman
Split-Treatment Analysis to Rank Heterogeneous Causal Effects for Prospective Interventions. WSDM (2021)
Divyat Mahajan, Shruti Tople, Amit Sharma
The Connection between Out-of-Distribution Generalization and Privacy of ML Models. CoRR (2021)
Divyat Mahajan, Shruti Tople, Amit Sharma
Domain Generalization using Causal Matching. CoRR (2020)
Yanbo Xu, Divyat Mahajan, Liz Manrao, Amit Sharma, Emre Kiciman
Split-Treatment Analysis to Rank Heterogeneous Causal Effects for Prospective Interventions. CoRR (2020)
Ramaravind Kommiya Mothilal, Divyat Mahajan, Chenhao Tan, Amit Sharma
Towards Unifying Feature Attribution and Counterfactual Explanations: Different Means to the Same End. CoRR (2020)
Varun Khare, Divyat Mahajan, Homanga Bharadhwaj, Vinay Kumar Verma, Piyush Rai
A Generative Framework for Zero-Shot Learning with Adversarial Domain Adaptation. WACV (2020)
Divyat Mahajan, Chenhao Tan, Amit Sharma
Preserving Causal Constraints in Counterfactual Explanations for Machine Learning Classifiers. CoRR (2019)
Varun Khare, Divyat Mahajan, Homanga Bharadhwaj, Vinay Kumar Verma, Piyush Rai
A Generative Framework for Zero-Shot Learning with Adversarial Domain Adaptation. CoRR (2019)