Divyat Mahajan

According to our database, Divyat Mahajan authored at least 16 papers between 2019 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Compositional Risk Minimization.

Divyat Mahajan, Mohammad Pezeshki, Ioannis Mitliagkas, Kartik Ahuja, Pascal Vincent

CoRR, 2024

Zero-Shot Learning of Causal Models.

Divyat Mahajan, Jannes Gladrow, Agrin Hilmkil, Cheng Zhang, Meyer Scetbon

CoRR, 2024

Evaluating Interventional Reasoning Capabilities of Large Language Models.

Tejas Kasetty, Divyat Mahajan, Gintare Karolina Dziugaite, Alexandre Drouin, Dhanya Sridhar

CoRR, 2024

Empirical Analysis of Model Selection for Heterogeneous Causal Effect Estimation.

Divyat Mahajan, Ioannis Mitliagkas, Brady Neal, Vasilis Syrgkanis

Proceedings of the Twelfth International Conference on Learning Representations, 2024

2023

Additive Decoders for Latent Variables Identification and Cartesian-Product Extrapolation.

Sébastien Lachapelle, Divyat Mahajan, Ioannis Mitliagkas, Simon Lacoste-Julien

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 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

Proceedings of the International Conference on Machine Learning, 2023

Interventional Causal Representation Learning.

Kartik Ahuja, Divyat Mahajan, Yixin Wang, Yoshua Bengio

Proceedings of the International Conference on Machine Learning, 2023

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

Empirical Analysis of Model Selection for Heterogenous Causal Effect Estimation.

Divyat Mahajan, Ioannis Mitliagkas, Brady Neal, Vasilis Syrgkanis

CoRR, 2022

Towards efficient representation identification in supervised learning.

Kartik Ahuja, Divyat Mahajan, Vasilis Syrgkanis, Ioannis Mitliagkas

Proceedings of the 1st Conference on Causal Learning and Reasoning, 2022

2021

The Connection between Out-of-Distribution Generalization and Privacy of ML Models.

Divyat Mahajan, Shruti Tople, Amit Sharma

CoRR, 2021

Split-Treatment Analysis to Rank Heterogeneous Causal Effects for Prospective Interventions.

Yanbo Xu, Divyat Mahajan, Liz Manrao, Amit Sharma, Emre Kiciman

Proceedings of the WSDM '21, 2021

Domain Generalization using Causal Matching.

Divyat Mahajan, Shruti Tople, Amit Sharma

Proceedings of the 38th International Conference on Machine Learning, 2021

Towards Unifying Feature Attribution and Counterfactual Explanations: Different Means to the Same End.

Ramaravind Kommiya Mothilal, Divyat Mahajan, Chenhao Tan, Amit Sharma

Proceedings of the AIES '21: AAAI/ACM Conference on AI, 2021

2020

A Generative Framework for Zero-Shot Learning with Adversarial Domain Adaptation.

Varun Khare, Divyat Mahajan, Homanga Bharadhwaj, Vinay Kumar Verma, Piyush Rai

Proceedings of the IEEE Winter Conference on Applications of Computer Vision, 2020

2019

Preserving Causal Constraints in Counterfactual Explanations for Machine Learning Classifiers.

Divyat Mahajan, Chenhao Tan, Amit Sharma

CoRR, 2019