Dhanya Sridhar

48 papers A* 7A 2Journal 33Unranked 5

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	A Compression Perspective on Simplicity Bias. CoRR Tom Marty, Eric Elmoznino, Léo Gagnon, Tejas Kasetty, Mizu Nishikawa-Toomey, Sarthak Mittal, Guillaume Lajoie, Dhanya Sridhar
2026	J	`jnl`	Causality is Key for Interpretability Claims to Generalise. CoRR Shruti Joshi, Aaron Mueller, David A. Klindt, Wieland Brendel, Patrik Reizinger, Dhanya Sridhar
2026	J	`jnl`	Who Guards the Guardians? The Challenges of Evaluating Identifiability of Learned Representations. CoRR Shruti Joshi, Théo Saulus, Wieland Brendel, Philippe Brouillard, Dhanya Sridhar, Patrik Reizinger
2025	J	`jnl`	Demystifying amortized causal discovery with transformers. Trans. Mach. Learn. Res. Francesco Montagna, Max Cairney-Leeming, Dhanya Sridhar, Francesco Locatello
2025	A*	`conf`	Does learning the right latent variables necessarily improve in-context learning? ICML Sarthak Mittal, Eric Elmoznino, Léo Gagnon, Sangnie Bhardwaj, Guillaume Lajoie, Dhanya Sridhar
2025	J	`jnl`	From Isolation to Entanglement: When Do Interpretability Methods Identify and Disentangle Known Concepts? CoRR Aaron Mueller, Andrew Lee, Shruti Joshi, Ekdeep Singh Lubana, Dhanya Sridhar, Patrik Reizinger
2025	J	`jnl`	Identifiable Steering via Sparse Autoencoding of Multi-Concept Shifts. CoRR Shruti Joshi, Andrea Dittadi, Sébastien Lachapelle, Dhanya Sridhar
2025	A*	`conf`	In-Context Learning and Occam's Razor. ICML Eric Elmoznino, Tom Marty, Tejas Kasetty, Léo Gagnon, Sarthak Mittal, Mahan Fathi, Dhanya Sridhar, Guillaume Lajoie
2025	J	`jnl`	Next-Token Prediction Should be Ambiguity-Sensitive: A Meta-Learning Perspective. CoRR Léo Gagnon, Eric Elmoznino, Sarthak Mittal, Tom Marty, Tejas Kasetty, Dhanya Sridhar, Guillaume Lajoie
2025	J	`jnl`	Sparsity regularization via tree-structured environments for disentangled representations. Trans. Mach. Learn. Res. Elliot Layne, Jason S. Hartford, Sébastien Lachapelle, Mathieu Blanchette, Dhanya Sridhar
2025	—	`conf`	The Landscape of Causal Discovery Data: Grounding Causal Discovery in Real-World Applications. CLeaR Philippe Brouillard, Chandler Squires, Jonas Wahl, Konrad K, Karen Sachs, Alexandre Drouin, Dhanya Sridhar
2024	J	`jnl`	Causal Representation Learning in Temporal Data via Single-Parent Decoding. CoRR Philippe Brouillard, Sébastien Lachapelle, Julia Kaltenborn, Yaniv Gurwicz, Dhanya Sridhar, Alexandre Drouin, Peer Nowack, Jakob Runge, David Rolnick
2024	J	`jnl`	Demystifying amortized causal discovery with transformers. CoRR Francesco Montagna, Max Cairney-Leeming, Dhanya Sridhar, Francesco Locatello
2024	J	`jnl`	Does learning the right latent variables necessarily improve in-context learning? CoRR Sarthak Mittal, Eric Elmoznino, Léo Gagnon, Sangnie Bhardwaj, Dhanya Sridhar, Guillaume Lajoie
2024	J	`jnl`	Evaluating Interventional Reasoning Capabilities of Large Language Models. CoRR Tejas Kasetty, Divyat Mahajan, Gintare Karolina Dziugaite, Alexandre Drouin, Dhanya Sridhar
2024	J	`jnl`	General Causal Imputation via Synthetic Interventions. CoRR Marco Jiralerspong, Thomas Jiralerspong, Vedant Shah, Dhanya Sridhar, Gauthier Gidel
2024	J	`jnl`	In-Context Learning Can Re-learn Forbidden Tasks. CoRR Sophie Xhonneux, David Dobre, Jian Tang, Gauthier Gidel, Dhanya Sridhar
2024	J	`jnl`	In-context learning and Occam's razor. CoRR Eric Elmoznino, Tom Marty, Tejas Kasetty, Léo Gagnon, Sarthak Mittal, Mahan Fathi, Dhanya Sridhar, Guillaume Lajoie
2024	J	`jnl`	Leveraging Structure Between Environments: Phylogenetic Regularization Incentivizes Disentangled Representations. CoRR Elliot Layne, Jason S. Hartford, Sébastien Lachapelle, Mathieu Blanchette, Dhanya Sridhar
2024	J	`jnl`	The Landscape of Causal Discovery Data: Grounding Causal Discovery in Real-World Applications. CoRR Philippe Brouillard, Chandler Squires, Jonas Wahl, Konrad P. Kording, Karen Sachs, Alexandre Drouin, Dhanya Sridhar
2023	J	`jnl`	Adjusting Machine Learning Decisions for Equal Opportunity and Counterfactual Fairness. Trans. Mach. Learn. Res. Yixin Wang, Dhanya Sridhar, David M. Blei
2022	J	`jnl`	Causal Inference in Natural Language Processing: Estimation, Prediction, Interpretation and Beyond. Trans. Assoc. Comput. Linguistics 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
2022	—	`conf`	Estimating Social Influence from Observational Data. CLeaR Dhanya Sridhar, Caterina De Bacco, David M. Blei
2022	J	`jnl`	Estimating Social Influence from Observational Data. CoRR Dhanya Sridhar, Caterina De Bacco, David M. Blei
2022	J	`jnl`	Heterogeneous Supervised Topic Models. Trans. Assoc. Comput. Linguistics Dhanya Sridhar, Hal Daumé III, David M. Blei
2022	J	`jnl`	Identifiable Deep Generative Models via Sparse Decoding. Trans. Mach. Learn. Res. Gemma E. Moran, Dhanya Sridhar, Yixin Wang, David M. Blei
2022	A	`conf`	On the Assumptions of Synthetic Control Methods. AISTATS Claudia Shi, Dhanya Sridhar, Vishal Misra, David M. Blei
2021	A*	`conf`	Assessing the Effects of Friend-to-Friend Texting onTurnout in the 2018 US Midterm Elections. WWW Aaron Schein, Keyon Vafa, Dhanya Sridhar, Victor Veitch, Jeffrey Quinn, James Moffet, David M. Blei, Donald P. Green
2021	—	`conf`	Causal Effects of Linguistic Properties. NAACL-HLT Reid Pryzant, Dallas Card, Dan Jurafsky, Victor Veitch, Dhanya Sridhar
2021	J	`jnl`	Causal Inference in Natural Language Processing: Estimation, Prediction, Interpretation and Beyond. CoRR 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
2021	J	`jnl`	Identifiable Variational Autoencoders via Sparse Decoding. CoRR Gemma E. Moran, Dhanya Sridhar, Yixin Wang, David M. Blei
2021	A*	`conf`	Valid Causal Inference with (Some) Invalid Instruments. ICML Jason S. Hartford, Victor Veitch, Dhanya Sridhar, Kevin Leyton-Brown
2020	A	`conf`	Adapting Text Embeddings for Causal Inference. UAI Victor Veitch, Dhanya Sridhar, David M. Blei
2020	J	`jnl`	Causal Effects of Linguistic Properties. CoRR Reid Pryzant, Dallas Card, Dan Jurafsky, Victor Veitch, Dhanya Sridhar
2020	J	`jnl`	Valid Causal Inference with (Some) Invalid Instruments. CoRR Jason S. Hartford, Victor Veitch, Dhanya Sridhar, Kevin Leyton-Brown
2019	J	`jnl`	Equal Opportunity and Affirmative Action via Counterfactual Predictions. CoRR Yixin Wang, Dhanya Sridhar, David M. Blei
2019	A*	`conf`	Estimating Causal Effects of Tone in Online Debates. IJCAI Dhanya Sridhar, Lise Getoor
2019	J	`jnl`	Estimating Causal Effects of Tone in Online Debates. CoRR Dhanya Sridhar, Lise Getoor
2019	J	`jnl`	Using Text Embeddings for Causal Inference. CoRR Victor Veitch, Dhanya Sridhar, David M. Blei
2018	A*	`conf`	A Structured Approach to Understanding Recovery and Relapse in AA. WWW Yue Zhang, Arti Ramesh, Jennifer Golbeck, Dhanya Sridhar, Lise Getoor
2018	—	`—`	Learning Structured and Causal Probabilistic Models for Computational Science. Dhanya Sridhar
2018	A*	`conf`	Scalable Probabilistic Causal Structure Discovery. IJCAI Dhanya Sridhar, Jay Pujara, Lise Getoor
2018	J	`jnl`	Scalable Structure Learning for Probabilistic Soft Logic. CoRR Varun Embar, Dhanya Sridhar, Golnoosh Farnadi, Lise Getoor
2017	—	`conf`	Using Noisy Extractions to Discover Causal Knowledge. AKBC@NIPS Dhanya Sridhar, Jay Pujara, Lise Getoor
2017	J	`jnl`	Using Noisy Extractions to Discover Causal Knowledge. CoRR Dhanya Sridhar, Jay Pujara, Lise Getoor
2016	J	`jnl`	A probabilistic approach for collective similarity-based drug-drug interaction prediction. Bioinform. Dhanya Sridhar, Shobeir Fakhraei, Lise Getoor
2016	J	`jnl`	Adaptive Neighborhood Graph Construction for Inference in Multi-Relational Networks. CoRR Shobeir Fakhraei, Dhanya Sridhar, Jay Pujara, Lise Getoor
2015	—	`conf`	Joint Models of Disagreement and Stance in Online Debate. ACL (1) Dhanya Sridhar, James R. Foulds, Bert Huang, Lise Getoor, Marilyn A. Walker