Ahuja, Kartik

38 publications

ICML 2025 Compositional Risk Minimization Divyat Mahajan, Mohammad Pezeshki, Charles Arnal, Ioannis Mitliagkas, Kartik Ahuja, Pascal Vincent

ICLR 2025 DRoP: Distributionally Robust Data Pruning Artem M Vysogorets, Kartik Ahuja, Julia Kempe

ICLRW 2025 Unveiling Simplicities of Attention: Adaptive Long-Context Head Identification Konstantin Donhauser, Charles Arnal, Mohammad Pezeshki, Vivien Cabannes, David Lopez-Paz, Kartik Ahuja

NeurIPSW 2024 Compositional Risk Minimization Divyat Mahajan, Mohammad Pezeshki, Ioannis Mitliagkas, Kartik Ahuja, Pascal Vincent

ICLR 2024 Context Is Environment Sharut Gupta, Stefanie Jegelka, David Lopez-Paz, Kartik Ahuja

AISTATS 2024 Multi-Domain Causal Representation Learning via Weak Distributional Invariances Kartik Ahuja, Amin Mansouri, Yixin Wang

ICMLW 2024 On Provable Length and Compositional Generalization Kartik Ahuja, Amin Mansouri

CLeaR 2024 On the Identifiability of Quantized Factors Vitória Barin-Pacela, Kartik Ahuja, Simon Lacoste-Julien, Pascal Vincent

ICMLW 2023 A Closer Look at In-Context Learning Under Distribution Shifts Kartik Ahuja, David Lopez-Paz

NeurIPSW 2023 Context Is Environment Sharut Gupta, David Lopez-Paz, Stefanie Jegelka, Kartik Ahuja

NeurIPSW 2023 Context Is Environment Sharut Gupta, David Lopez-Paz, Stefanie Jegelka, Kartik Ahuja

TMLR 2023 Empirical Study on Optimizer Selection for Out-of-Distribution Generalization Hiroki Naganuma, Kartik Ahuja, Shiro Takagi, Tetsuya Motokawa, Rio Yokota, Kohta Ishikawa, Ikuro Sato, Ioannis Mitliagkas

ICMLW 2023 Identifiability of Discretized Latent Coordinate Systems via Density Landmarks Detection Vitória Barin-Pacela, Kartik Ahuja, Simon Lacoste-Julien, Pascal Vincent

ICMLW 2023 Identifiability of Discretized Latent Coordinate Systems via Density Landmarks Detection Vitória Barin-Pacela, Kartik Ahuja, Simon Lacoste-Julien, Pascal Vincent

ICML 2023 Interventional Causal Representation Learning Kartik Ahuja, Divyat Mahajan, Yixin Wang, Yoshua Bengio

NeurIPS 2023 Locally Invariant Explanations: Towards Stable and Unidirectional Explanations Through Local Invariant Learning Amit Dhurandhar, Karthikeyan Natesan Ramamurthy, Kartik Ahuja, Vijay Arya

ICML 2023 Model Ratatouille: Recycling Diverse Models for Out-of-Distribution Generalization Alexandre Rame, Kartik Ahuja, Jianyu Zhang, Matthieu Cord, Leon Bottou, David Lopez-Paz

NeurIPSW 2023 Multi-Domain Causal Representation Learning via Weak Distributional Invariances Kartik Ahuja, Amin Mansouri, Yixin Wang

NeurIPS 2023 Reusable Slotwise Mechanisms Trang Nguyen, Amin Mansouri, Kanika Madan, Khuong Duy Nguyen, Kartik Ahuja, Dianbo Liu, Yoshua Bengio

TMLR 2023 WOODS: Benchmarks for Out-of-Distribution Generalization in Time Series Jean-Christophe Gagnon-Audet, Kartik Ahuja, Mohammad Javad Darvishi Bayazi, Pooneh Mousavi, Guillaume Dumas, Irina Rish

ICML 2023 Why Does Throwing Away Data Improve Worst-Group Error? Kamalika Chaudhuri, Kartik Ahuja, Martin Arjovsky, David Lopez-Paz

AISTATS 2022 Finding Valid Adjustments Under Non-Ignorability with Minimal DAG Knowledge Abhin Shah, Karthikeyan Shanmugam, Kartik Ahuja

NeurIPSW 2022 Empirical Study on Optimizer Selection for Out-of-Distribution Generalization Hiroki Naganuma, Kartik Ahuja, Ioannis Mitliagkas, Shiro Takagi, Tetsuya Motokawa, Rio Yokota, Kohta Ishikawa, Ikuro Sato

NeurIPSW 2022 FL Games: A Federated Learning Framework for Distribution Shifts Sharut Gupta, Kartik Ahuja, Mohammad Havaei, Niladri Chatterjee, Yoshua Bengio

NeurIPSW 2022 Interventional Causal Representation Learning Kartik Ahuja, Yixin Wang, Divyat Mahajan, Yoshua Bengio

NeurIPSW 2022 Interventional Causal Representation Learning Kartik Ahuja, Yixin Wang, Divyat Mahajan, Yoshua Bengio

NeurIPSW 2022 Object-Centric Causal Representation Learning Amin Mansouri, Jason Hartford, Kartik Ahuja, Yoshua Bengio

ICLR 2022 Properties from Mechanisms: An Equivariance Perspective on Identifiable Representation Learning Kartik Ahuja, Jason Hartford, Yoshua Bengio

CLeaR 2022 Towards Efficient Representation Identification in Supervised Learning Kartik Ahuja, Divyat Mahajan, Vasilis Syrgkanis, Ioannis Mitliagkas

NeurIPS 2022 Weakly Supervised Representation Learning with Sparse Perturbations Kartik Ahuja, Jason S Hartford, Yoshua Bengio

AISTATS 2021 Linear Regression Games: Convergence Guarantees to Approximate Out-of-Distribution Solutions Kartik Ahuja, Karthikeyan Shanmugam, Amit Dhurandhar

NeurIPS 2021 Adversarial Feature Desensitization Pouya Bashivan, Reza Bayat, Adam Ibrahim, Kartik Ahuja, Mojtaba Faramarzi, Touraj Laleh, Blake Richards, Irina Rish

ICML 2021 Can Subnetwork Structure Be the Key to Out-of-Distribution Generalization? Dinghuai Zhang, Kartik Ahuja, Yilun Xu, Yisen Wang, Aaron Courville

UAI 2021 Conditionally Independent Data Generation Kartik Ahuja, Prasanna Sattigeri, Karthikeyan Shanmugam, Dennis Wei, Karthikeyan Natesan Ramamurthy, Murat Kocaoglu

ICLR 2021 Empirical or Invariant Risk Minimization? a Sample Complexity Perspective Kartik Ahuja, Jun Wang, Amit Dhurandhar, Karthikeyan Shanmugam, Kush R. Varshney

NeurIPS 2021 Invariance Principle Meets Information Bottleneck for Out-of-Distribution Generalization Kartik Ahuja, Ethan Caballero, Dinghuai Zhang, Jean-Christophe Gagnon-Audet, Yoshua Bengio, Ioannis Mitliagkas, Irina Rish

ICML 2020 Invariant Risk Minimization Games Kartik Ahuja, Karthikeyan Shanmugam, Kush Varshney, Amit Dhurandhar

NeurIPS 2017 DPSCREEN: Dynamic Personalized Screening Kartik Ahuja, William Zame, Mihaela van der Schaar