Harsh Parikh - RankMe

32 papers A* 1A 4C 1Journal 23Unranked 3

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Controllable Generative Sandbox for Causal Inference. CoRR Qi Zhang, Harsh Parikh, Ashley Naimi, Razieh Nabi, Christopher Kim, Timothy Lash
2026	J	`jnl`	Demystifying Prediction Powered Inference. CoRR Yilin Song, Dan M. Kluger, Harsh Parikh, Tian Gu
2026	J	`jnl`	TEA-Time: Transporting Effects Across Time. CoRR Harsh Parikh, Gabriel Levin-Konigsberg, Dominique Perrault-Joncas, Alexander Volfovsky
2026	J	`jnl`	Why are there many equally good models? An Anatomy of the Rashomon Effect. CoRR Harsh Parikh
2025	J	`jnl`	A Cautionary Tale on Integrating Studies with Disparate Outcome Measures for Causal Inference. CoRR Harsh Parikh, Trang Quynh Nguyen, Elizabeth A. Stuart, Kara E. Rudolph, Caleb H. Miles
2025	J	`jnl`	Data Fusion for Partial Identification of Causal Effects. CoRR Quinn Lanners, Cynthia Rudin, Alexander Volfovsky, Harsh Parikh
2025	A	`conf`	Graph Machine Learning based Doubly Robust Estimator for Network Causal Effects. AISTATS Seyedeh Baharan Khatami, Harsh Parikh, Haowei Chen, Sudeepa Roy, Babak Salimi
2025	J	`jnl`	Regularizing Extrapolation in Causal Inference. CoRR David Arbour, Harsh Parikh, Bijan Niknam, Elizabeth A. Stuart, Kara E. Rudolph, Avi Feller
2024	J	`jnl`	American sign language classification using deep learning. Int. J. Biom. Harsh Parikh, Nisarg Panchal, Vraj Patel, Ankit K. Sharma
2024	J	`jnl`	Graph Neural Network based Double Machine Learning Estimator of Network Causal Effects. CoRR Seyedeh Baharan Khatami, Harsh Parikh, Haowei Chen, Sudeepa Roy, Babak Salimi
2024	A	`conf`	Interpretable Causal Inference for Analyzing Wearable, Sensor, and Distributional Data. AISTATS Srikar Katta, Harsh Parikh, Cynthia Rudin, Alexander Volfovsky
2024	A	`conf`	Safe and Interpretable Estimation of Optimal Treatment Regimes. AISTATS Harsh Parikh, Quinn Lanners, Zade Akras, Sahar F. Zafar, M. Brandon Westover, Cynthia Rudin, Alexander Volfovsky
2024	J	`jnl`	Towards Generalizing Inferences from Trials to Target Populations. CoRR Melody Y. Huang, Sarah E. Robertson, Harsh Parikh
2024	J	`jnl`	Who Are We Missing? A Principled Approach to Characterizing the Underrepresented Population. CoRR Harsh Parikh, Rachael Ross, Elizabeth A. Stuart, Kara E. Rudolph
2023	J	`jnl`	A Double Machine Learning Approach to Combining Experimental and Observational Data. CoRR Marco Morucci, Vittorio Orlandi, Harsh Parikh, Sudeepa Roy, Cynthia Rudin, Alexander Volfovsky
2023	J	`jnl`	Estimating Trustworthy and Safe Optimal Treatment Regimes. CoRR Harsh Parikh, Quinn Lanners, Zade Akras, Sahar F. Zafar, M. Brandon Westover, Cynthia Rudin, Alexander Volfovsky
2023	J	`jnl`	From Feature Importance to Distance Metric: An Almost Exact Matching Approach for Causal Inference. CoRR Quinn Lanners, Harsh Parikh, Alexander Volfovsky, Cynthia Rudin, David Page
2023	J	`jnl`	Interpretable Causal Inference for Analyzing Wearable, Sensor, and Distributional Data. CoRR Srikar Katta, Harsh Parikh, Cynthia Rudin, Alexander Volfovsky
2023	—	`conf`	Synthetic Controls as Balancing Scores. Tiny Papers @ ICLR Harsh Parikh
2023	A	`conf`	Variable importance matching for causal inference. UAI Quinn Lanners, Harsh Parikh, Alexander Volfovsky, Cynthia Rudin, David Page
2022	J	`jnl`	Are Synthetic Control Weights Balancing Score? CoRR Harsh Parikh
2022	J	`jnl`	Evaluating Causal Inference Methods. CoRR Harsh Parikh, Carlos Varjao, Louise Xu, Eric Tchetgen Tchetgen
2022	J	`jnl`	MALTS: Matching After Learning to Stretch. J. Mach. Learn. Res. Harsh Parikh, Cynthia Rudin, Alexander Volfovsky
2022	A*	`conf`	Validating Causal Inference Methods. ICML Harsh Parikh, Carlos Varjao, Louise Xu, Eric Tchetgen Tchetgen
2022	J	`jnl`	Why Interpretable Causal Inference is Important for High-Stakes Decision Making for Critically Ill Patients and How To Do It. CoRR Harsh Parikh, Kentaro Hoffman, Haoqi Sun, Wendong Ge, Jin Jing, Rajesh Amerineni, Lin Liu, Jimeng Sun, Sahar F. Zafar, Aaron Struck, Alexander Volfovsky, Cynthia Rudin, M. Brandon Westover
2021	J	`jnl`	Detecting Treatment Effect Modifiers in Social Networks. CoRR Amir Gilad, Harsh Parikh, Babak Salimi, Sudeepa Roy
2020	—	`conf`	Causal Relational Learning. SIGMOD Conference Babak Salimi, Harsh Parikh, Moe Kayali, Lise Getoor, Sudeepa Roy, Dan Suciu
2020	J	`jnl`	Causal Relational Learning. CoRR Babak Salimi, Harsh Parikh, Moe Kayali, Sudeepa Roy, Lise Getoor, Dan Suciu
2018	J	`jnl`	MALTS: Matching After Learning to Stretch. CoRR Harsh Parikh, Cynthia Rudin, Alexander Volfovsky
2016	C	`conf`	Control of a Modular Multilevel Converter STATCOM under internal and external unbalances. IECON Georgios Tsolaridis, Epameinondas Kontos, Harsh Parikh, Ruben M. Sanchez-Loeches, Remus Teodorescu, Sanjay K. Chaudhary
2015	J	`jnl`	Computational prediction of origin of replication in bacterial genomes using correlated entropy measure (CEM). Biosyst. Harsh Parikh, Apoorvi Singh, Annangarachari Krishnamachari, Kushal Shah
2015	—	`conf`	Investigating the "Wisdom of Crowds" at Scale. UIST (Adjunct Volume) Alok Shankar Mysore, Vikas S. Yaligar, Imanol Arrieta Ibarra, Camelia Simoiu, Sharad Goel, Ramesh Arvind, Chiraag Sumanth, Arvind Srikantan, Bhargav HS, Mayank Pahadia, Tushar Dobha, Atif Ahmed, Mani Shankar, Himani Agarwal, Rajat Agarwal, Sai Anirudh-Kondaveeti, Shashank Arun-Gokhale, Aayush Attri, Arpita Chandra, Yogitha Chilukur, Sharath Dharmaji, Deepak Garg, Naman Gupta, Paras Gupta, Glincy Mary Jacob, Siddharth Jain, Shashank Joshi, Tarun Khajuria, Sameeksha Khillan, Sandeep Konam, Praveen Kumar-Kolla, Sahil Loomba, Rachit Madan, Akshansh Maharaja, Vidit Mathur, Bharat Munshi, Mohammed Nawazish, Venkata Neehar-Kurukunda, Venkat Nirmal-Gavarraju, Sonali Parashar, Harsh Parikh, Avinash Paritala, Amit Patil, Rahul Phatak, Mandar Pradhan, Abhilasha Ravichander, Krishna Sangeeth, Sreecharan Sankaranarayanan, Vibhor Sehgal, Ashrith Sheshan, Suprajha Shibiraj, Aditya Singh, Anjali Singh, Prashant Sinha, Pushkin Soni, Bipin Thomas, Kasyap Varma-Dattada, Sukanya Venkataraman, Pulkit Verma, Ishan Yelurwar