Aahlad Manas Puli

38 papers A* 9A 2Journal 23Unranked 3

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	Attention and Compression is all you need for Controllably Efficient Language Models. CoRR Jatin Prakash, Aahlad Manas Puli, Rajesh Ranganath
2025	J	`jnl`	Black Box Causal Inference: Effect Estimation via Meta Prediction. CoRR Lucius E. J. Bynum, Aahlad Manas Puli, Diego Herrero-Quevedo, Nhi Nguyen, Carlos Fernandez-Granda, Kyunghyun Cho, Rajesh Ranganath
2025	—	`conf`	Learning Is Not A Race: Improving Retrieval in Language Models via Equal Learning. EMNLP (Findings) Wanqian Yang, Aahlad Manas Puli, Rajesh Ranganath
2025	J	`jnl`	Let the Experts Speak: Improving Survival Prediction & Calibration via Mixture-of-Experts Heads. CoRR Todd Morrill, Aahlad Manas Puli, Murad Megjhani, Soojin Park, Richard S. Zemel
2024	A*	`conf`	Contrasting with Symile: Simple Model-Agnostic Representation Learning for Unlimited Modalities. NeurIPS Adriel Saporta, Aahlad Manas Puli, Mark Goldstein, Rajesh Ranganath
2024	J	`jnl`	Contrasting with Symile: Simple Model-Agnostic Representation Learning for Unlimited Modalities. CoRR Adriel Saporta, Aahlad Manas Puli, Mark Goldstein, Rajesh Ranganath
2024	A*	`conf`	Explanations that reveal all through the definition of encoding. NeurIPS Aahlad Manas Puli, Nhi Nguyen, Rajesh Ranganath
2024	J	`jnl`	Explanations that reveal all through the definition of encoding. CoRR Aahlad Manas Puli, Nhi Nguyen, Rajesh Ranganath
2024	J	`jnl`	Nuisances via Negativa: Adjusting for Spurious Correlations via Data Augmentation. Trans. Mach. Learn. Res. Aahlad Manas Puli, Nitish Joshi, Yoav Wald, He He, Rajesh Ranganath
2024	J	`jnl`	Robust Anomaly Detection for Particle Physics Using Multi-Background Representation Learning. CoRR Abhijith Gandrakota, Lily H. Zhang, Aahlad Manas Puli, Kyle Cranmer, Jennifer Ngadiuba, Rajesh Ranganath, Nhan Tran
2024	J	`jnl`	Robust anomaly detection for particle physics using multi-background representation learning. Mach. Learn. Sci. Technol. Abhijith Gandrakota, Lily H. Zhang, Aahlad Manas Puli, Kyle Cranmer, Jennifer Ngadiuba, Rajesh Ranganath, Nhan Tran
2024	—	`—`	Unlocking AI outside the training distribution: Generalization, Causality, and Coronary Risk Modeling Aahlad Manas Puli
2023	J	`jnl`	A dynamic risk score for early prediction of cardiogenic shock using machine learning. CoRR Yuxuan Hu, Albert Lui, Mark Goldstein, Mukund Sudarshan, Andrea Tinsay, Cindy Tsui, Samuel Maidman, John Medamana, Neil Jethani, Aahlad Manas Puli, Vuthy Nguy, Yindalon Aphinyanaphongs, Nicholas Kiefer, Nathaniel Smilowitz, James Horowitz, Tania Ahuja, Glenn I. Fishman, Judith Hochman, Stuart Katz, Samuel Bernard, Rajesh Ranganath
2023	J	`jnl`	Beyond Distribution Shift: Spurious Features Through the Lens of Training Dynamics. Trans. Mach. Learn. Res. Nihal Murali, Aahlad Manas Puli, Ke Yu, Rajesh Ranganath, Kayhan Batmanghelich
2023	A	`conf`	DIET: Conditional independence testing with marginal dependence measures of residual information. AISTATS Mukund Sudarshan, Aahlad Manas Puli, Wesley Tansey, Rajesh Ranganath
2023	A*	`conf`	Don't blame Dataset Shift! Shortcut Learning due to Gradients and Cross Entropy. NeurIPS Aahlad Manas Puli, Lily H. Zhang, Yoav Wald, Rajesh Ranganath
2023	J	`jnl`	Don't blame Dataset Shift! Shortcut Learning due to Gradients and Cross Entropy. CoRR Aahlad Manas Puli, Lily H. Zhang, Yoav Wald, Rajesh Ranganath
2023	J	`jnl`	Shortcut Learning Through the Lens of Early Training Dynamics. CoRR Nihal Murali, Aahlad Manas Puli, Ke Yu, Rajesh Ranganath, Kayhan Batmanghelich
2023	—	`conf`	When More is Less: Incorporating Additional Datasets Can Hurt Performance By Introducing Spurious Correlations. MLHC Rhys Compton, Lily H. Zhang, Aahlad Manas Puli, Rajesh Ranganath
2023	J	`jnl`	When More is Less: Incorporating Additional Datasets Can Hurt Performance By Introducing Spurious Correlations. CoRR Rhys Compton, Lily H. Zhang, Aahlad Manas Puli, Rajesh Ranganath
2022	J	`jnl`	DIET: Conditional independence testing with marginal dependence measures of residual information. CoRR Mukund Sudarshan, Aahlad Manas Puli, Wesley Tansey, Rajesh Ranganath
2022	—	`conf`	Learning Invariant Representations with Missing Data. CLeaR Mark Goldstein, Jörn-Henrik Jacobsen, Olina Chau, Adriel Saporta, Aahlad Manas Puli, Rajesh Ranganath, Andrew C. Miller
2022	J	`jnl`	New-Onset Diabetes Assessment Using Artificial Intelligence-Enhanced Electrocardiography. CoRR Neil Jethani, Aahlad Manas Puli, Hao Zhang, Leonid Garber, Lior Jankelson, Yindalon Aphinyanaphongs, Rajesh Ranganath
2022	J	`jnl`	Nuisances via Negativa: Adjusting for Spurious Correlations via Data Augmentation. CoRR Aahlad Manas Puli, Nitish Joshi, He He, Rajesh Ranganath
2022	A*	`conf`	Out-of-distribution Generalization in the Presence of Nuisance-Induced Spurious Correlations. ICLR Aahlad Manas Puli, Lily H. Zhang, Eric Karl Oermann, Rajesh Ranganath
2021	A	`conf`	CONTRA: Contrarian statistics for controlled variable selection. AISTATS Mukund Sudarshan, Aahlad Manas Puli, Lakshmi Subramanian, Sriram Sankararaman, Rajesh Ranganath
2021	J	`jnl`	Causal Estimation with Functional Confounders. CoRR Aahlad Manas Puli, Adler J. Perotte, Rajesh Ranganath
2021	A*	`conf`	Inverse-Weighted Survival Games. NeurIPS Xintian Han, Mark Goldstein, Aahlad Manas Puli, Thomas Wies, Adler J. Perotte, Rajesh Ranganath
2021	J	`jnl`	Inverse-Weighted Survival Games. CoRR Xintian Han, Mark Goldstein, Aahlad Manas Puli, Thomas Wies, Adler J. Perotte, Rajesh Ranganath
2021	J	`jnl`	Learning Invariant Representations with Missing Data. CoRR Mark Goldstein, Jörn-Henrik Jacobsen, Olina Chau, Adriel Saporta, Aahlad Manas Puli, Rajesh Ranganath, Andrew C. Miller
2021	J	`jnl`	Predictive Modeling in the Presence of Nuisance-Induced Spurious Correlations. CoRR Aahlad Manas Puli, Lily H. Zhang, Eric K. Oermann, Rajesh Ranganath
2021	J	`jnl`	X-CAL: Explicit Calibration for Survival Analysis. CoRR Mark Goldstein, Xintian Han, Aahlad Manas Puli, Adler J. Perotte, Rajesh Ranganath
2020	A*	`conf`	Causal Estimation with Functional Confounders. NeurIPS Aahlad Manas Puli, Adler J. Perotte, Rajesh Ranganath
2020	A*	`conf`	General Control Functions for Causal Effect Estimation from IVs. NeurIPS Aahlad Manas Puli, Rajesh Ranganath
2020	A*	`conf`	X-CAL: Explicit Calibration for Survival Analysis. NeurIPS Mark Goldstein, Xintian Han, Aahlad Manas Puli, Adler J. Perotte, Rajesh Ranganath
2019	J	`jnl`	Generalized Control Functions via Variational Decoupling. CoRR Aahlad Manas Puli, Rajesh Ranganath
2018	A*	`conf`	Removing Hidden Confounding by Experimental Grounding. NeurIPS Nathan Kallus, Aahlad Manas Puli, Uri Shalit
2018	J	`jnl`	Removing Hidden Confounding by Experimental Grounding. CoRR Nathan Kallus, Aahlad Manas Puli, Uri Shalit