Dhanya Sridhar

According to our database, Dhanya Sridhar authored at least 30 papers between 2015 and 2024.

Collaborative distances:

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

2024

General Causal Imputation via Synthetic Interventions.

Marco Jiralerspong, Thomas Jiralerspong, Vedant Shah, Dhanya Sridhar, Gauthier Gidel

CoRR, 2024

In-context learning and Occam's razor.

Eric Elmoznino, Tom Marty, Tejas Kasetty, Léo Gagnon, Sarthak Mittal, Mahan Fathi, Dhanya Sridhar, Guillaume Lajoie

CoRR, 2024

Causal Representation Learning in Temporal Data via Single-Parent Decoding.

Philippe Brouillard, Sébastien Lachapelle, Julia Kaltenborn, Yaniv Gurwicz, Dhanya Sridhar, Alexandre Drouin, Peer Nowack, Jakob Runge, David Rolnick

CoRR, 2024

Leveraging Structure Between Environments: Phylogenetic Regularization Incentivizes Disentangled Representations.

Elliot Layne, Jason S. Hartford, Sébastien Lachapelle, Mathieu Blanchette, Dhanya Sridhar

CoRR, 2024

Does learning the right latent variables necessarily improve in-context learning?

Sarthak Mittal, Eric Elmoznino, Léo Gagnon, Sangnie Bhardwaj, Dhanya Sridhar, Guillaume Lajoie

CoRR, 2024

Demystifying amortized causal discovery with transformers.

Francesco Montagna, Max Cairney-Leeming, Dhanya Sridhar, Francesco Locatello

CoRR, 2024

Evaluating Interventional Reasoning Capabilities of Large Language Models.

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

CoRR, 2024

In-Context Learning Can Re-learn Forbidden Tasks.

Sophie Xhonneux, David Dobre, Jian Tang, Gauthier Gidel, Dhanya Sridhar

CoRR, 2024

2023

Adjusting Machine Learning Decisions for Equal Opportunity and Counterfactual Fairness.

Yixin Wang, Dhanya Sridhar, David M. Blei

Trans. Mach. Learn. Res., 2023

2022

Identifiable Deep Generative Models via Sparse Decoding.

Gemma E. Moran, Dhanya Sridhar, Yixin Wang, David M. Blei

Trans. Mach. Learn. Res., 2022

Heterogeneous Supervised Topic Models.

Dhanya Sridhar, Hal Daumé III, David M. Blei

Trans. Assoc. Comput. Linguistics, 2022

Causal Inference in Natural Language Processing: Estimation, Prediction, Interpretation and Beyond.

Amir Feder, Katherine A. Keith, Emaad Manzoor, Reid Pryzant, Dhanya Sridhar, Zach Wood-Doughty, Jacob Eisenstein, Justin Grimmer, Roi Reichart, Margaret E. Roberts, Brandon M. Stewart, Victor Veitch, Diyi Yang

Trans. Assoc. Comput. Linguistics, 2022

Estimating Social Influence from Observational Data.

Dhanya Sridhar, Caterina De Bacco, David M. Blei

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

On the Assumptions of Synthetic Control Methods.

Claudia Shi, Dhanya Sridhar, Vishal Misra, David M. Blei

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

2021

Identifiable Variational Autoencoders via Sparse Decoding.

Gemma E. Moran, Dhanya Sridhar, Yixin Wang, David M. Blei

CoRR, 2021

Assessing the Effects of Friend-to-Friend Texting onTurnout in the 2018 US Midterm Elections.

Aaron Schein, Keyon Vafa, Dhanya Sridhar, Victor Veitch, Jeffrey Quinn, James Moffet, David M. Blei, Donald P. Green

Proceedings of the WWW '21: The Web Conference 2021, 2021

Causal Effects of Linguistic Properties.

Reid Pryzant, Dallas Card, Dan Jurafsky, Victor Veitch, Dhanya Sridhar

Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2021

Valid Causal Inference with (Some) Invalid Instruments.

Jason S. Hartford, Victor Veitch, Dhanya Sridhar, Kevin Leyton-Brown

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

2020

Adapting Text Embeddings for Causal Inference.

Victor Veitch, Dhanya Sridhar, David M. Blei

Proceedings of the Thirty-Sixth Conference on Uncertainty in Artificial Intelligence, 2020

2019

Using Text Embeddings for Causal Inference.

Victor Veitch, Dhanya Sridhar, David M. Blei

CoRR, 2019

Equal Opportunity and Affirmative Action via Counterfactual Predictions.

Yixin Wang, Dhanya Sridhar, David M. Blei

CoRR, 2019

Estimating Causal Effects of Tone in Online Debates.

Dhanya Sridhar, Lise Getoor

Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, 2019

2018

Learning Structured and Causal Probabilistic Models for Computational Science.

Dhanya Sridhar

PhD thesis, 2018

Scalable Structure Learning for Probabilistic Soft Logic.

Varun Embar, Dhanya Sridhar, Golnoosh Farnadi, Lise Getoor

CoRR, 2018

A Structured Approach to Understanding Recovery and Relapse in AA.

Yue Zhang, Arti Ramesh, Jennifer Golbeck, Dhanya Sridhar, Lise Getoor

Proceedings of the 2018 World Wide Web Conference on World Wide Web, 2018

Scalable Probabilistic Causal Structure Discovery.

Dhanya Sridhar, Jay Pujara, Lise Getoor

Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence, 2018

2017

Using Noisy Extractions to Discover Causal Knowledge.

Dhanya Sridhar, Jay Pujara, Lise Getoor

Proceedings of the 6th Workshop on Automated Knowledge Base Construction, 2017

2016

Adaptive Neighborhood Graph Construction for Inference in Multi-Relational Networks.

Shobeir Fakhraei, Dhanya Sridhar, Jay Pujara, Lise Getoor

CoRR, 2016

A probabilistic approach for collective similarity-based drug-drug interaction prediction.

Dhanya Sridhar, Shobeir Fakhraei, Lise Getoor

Bioinform., 2016

2015

Joint Models of Disagreement and Stance in Online Debate.

Dhanya Sridhar, James R. Foulds, Bert Huang, Lise Getoor, Marilyn A. Walker

Proceedings of the 53rd Annual Meeting of the Association for Computational Linguistics and the 7th International Joint Conference on Natural Language Processing of the Asian Federation of Natural Language Processing, 2015