Dhanya Sridhar

Orcid: 0009-0008-4150-456X

According to our database1, Dhanya Sridhar authored at least 28 papers between 2015 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

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PhD thesis 
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Links

On csauthors.net:

Bibliography

2024
Causal Representation Learning in Temporal Data via Single-Parent Decoding.
CoRR, 2024

Leveraging Structure Between Environments: Phylogenetic Regularization Incentivizes Disentangled Representations.
CoRR, 2024

Does learning the right latent variables necessarily improve in-context learning?
CoRR, 2024

Demystifying amortized causal discovery with transformers.
CoRR, 2024

Evaluating Interventional Reasoning Capabilities of Large Language Models.
CoRR, 2024

In-Context Learning Can Re-learn Forbidden Tasks.
CoRR, 2024

2023
Adjusting Machine Learning Decisions for Equal Opportunity and Counterfactual Fairness.
Trans. Mach. Learn. Res., 2023

2022
Identifiable Deep Generative Models via Sparse Decoding.
Trans. Mach. Learn. Res., 2022

Heterogeneous Supervised Topic Models.
Trans. Assoc. Comput. Linguistics, 2022

Causal Inference in Natural Language Processing: Estimation, Prediction, Interpretation and Beyond.
Trans. Assoc. Comput. Linguistics, 2022

Estimating Social Influence from Observational Data.
Proceedings of the 1st Conference on Causal Learning and Reasoning, 2022

On the Assumptions of Synthetic Control Methods.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

2021
Identifiable Variational Autoencoders via Sparse Decoding.
CoRR, 2021

Assessing the Effects of Friend-to-Friend Texting onTurnout in the 2018 US Midterm Elections.
Proceedings of the WWW '21: The Web Conference 2021, 2021

Causal Effects of Linguistic Properties.
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.
Proceedings of the 38th International Conference on Machine Learning, 2021

2020
Adapting Text Embeddings for Causal Inference.
Proceedings of the Thirty-Sixth Conference on Uncertainty in Artificial Intelligence, 2020

2019
Using Text Embeddings for Causal Inference.
CoRR, 2019

Equal Opportunity and Affirmative Action via Counterfactual Predictions.
CoRR, 2019

Estimating Causal Effects of Tone in Online Debates.
Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, 2019

2018
Learning Structured and Causal Probabilistic Models for Computational Science.
PhD thesis, 2018

Scalable Structure Learning for Probabilistic Soft Logic.
CoRR, 2018

A Structured Approach to Understanding Recovery and Relapse in AA.
Proceedings of the 2018 World Wide Web Conference on World Wide Web, 2018

Scalable Probabilistic Causal Structure Discovery.
Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence, 2018

2017
Using Noisy Extractions to Discover Causal Knowledge.
Proceedings of the 6th Workshop on Automated Knowledge Base Construction, 2017

2016
Adaptive Neighborhood Graph Construction for Inference in Multi-Relational Networks.
CoRR, 2016

A probabilistic approach for collective similarity-based drug-drug interaction prediction.
Bioinform., 2016

2015
Joint Models of Disagreement and Stance in Online Debate.
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


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