Siddarth Srinivasan

20 papers A* 3A 3B 1Journal 11Unranked 1

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	The Prosocial Ranking Challenge: Reducing Polarization on Social Media without Sacrificing Engagement. CoRR Jonathan Stray, Ian Baker, George Beknazar-Yuzbashev, Ceren Budak, Julia Kamin, Kylan Rutherford, Mateusz Stalinski, Tin Acosta, Chris Bailey, Michael S. Bernstein, Mark Brandt, Amy Bruckman, Anshuman Chhabra, Soham De, Kayla Duskin, Sara Fish, Beth Goldberg, Andy Guess, Dylan Hadfield-Menell, Muhammad Haroon, Safwan Hossain, Michael Inzlicht, Gauri Jain, Yanchen Jiang, Alexander P. Landry, Yph Lelkes, Hongfan Lu, Peter Mason, Jennifer McCoy, Smitha Milli, Paul Resnick, Emily Saltz, Martin Saveski, Lisa Schirch, Max Spohn, Siddarth Srinivasan, Alexis Tatore, Luke Thorburn, Joshua A. Tucker, Robb Willer, Magdalena Wojcieszak, Manuel Wüthrich, Sylvan Zheng
2025	A*	`conf`	Self-Resolving Prediction Markets for Unverifiable Outcomes. EC Siddarth Srinivasan, Ezra Karger, Yiling Chen
2025	J	`jnl`	Tell Me Why: Incentivizing Explanations. CoRR Siddarth Srinivasan, Ezra Karger, Michiel Bakker, Yiling Chen
2025	J	`jnl`	WOMAC: A Mechanism For Prediction Competitions. CoRR Siddarth Srinivasan, Tao Lin, Connacher Murphy, Anish Thilagar, Yiling Chen, Ezra Karger
2023	J	`jnl`	Self-Resolving Prediction Markets for Unverifiable Outcomes. CoRR Siddarth Srinivasan, Ezra Karger, Yiling Chen
2022	—	`—`	Quantum-inspired Machine Learning with Hidden Quantum Markov Models and Tensor Networks Siddarth Srinivasan
2021	J	`jnl`	Auctions and Prediction Markets for Scientific Peer Review. CoRR Siddarth Srinivasan, Jamie Morgenstern
2021	A*	`conf`	Learning Deep Features in Instrumental Variable Regression. ICLR Liyuan Xu, Yutian Chen, Siddarth Srinivasan, Nando de Freitas, Arnaud Doucet, Arthur Gretton
2021	A	`conf`	Quantum Tensor Networks, Stochastic Processes, and Weighted Automata. AISTATS Sandesh Adhikary, Siddarth Srinivasan, Jacob Miller, Guillaume Rabusseau, Byron Boots
2020	A	`conf`	Expressiveness and Learning of Hidden Quantum Markov Models. AISTATS Sandesh Adhikary, Siddarth Srinivasan, Geoffrey J. Gordon, Byron Boots
2020	J	`jnl`	Learning Deep Features in Instrumental Variable Regression. CoRR Liyuan Xu, Yutian Chen, Siddarth Srinivasan, Nando de Freitas, Arnaud Doucet, Arthur Gretton
2020	J	`jnl`	Quantum Tensor Networks, Stochastic Processes, and Weighted Automata. CoRR Siddarth Srinivasan, Sandesh Adhikary, Jacob Miller, Guillaume Rabusseau, Byron Boots
2019	J	`jnl`	Expressiveness and Learning of Hidden Quantum Markov Models. CoRR Sandesh Adhikary, Siddarth Srinivasan, Geoffrey J. Gordon, Byron Boots
2019	J	`jnl`	Learning Quantum Graphical Models using Constrained Gradient Descent on the Stiefel Manifold. CoRR Sandesh Adhikary, Siddarth Srinivasan, Byron Boots
2018	—	`conf`	A Simple and Effective Approach to the Story Cloze Test. NAACL-HLT (2) Siddarth Srinivasan, Richa Arora, Mark O. Riedl
2018	J	`jnl`	A Simple and Effective Approach to the Story Cloze Test. CoRR Siddarth Srinivasan, Richa Arora, Mark O. Riedl
2018	B	`conf`	Expressing Coherent Personality with Incremental Acquisition of Multimodal Behaviors. RO-MAN Pedro Mota, Maike Paetzel, Andrea Fox, Aida Amini, Siddarth Srinivasan, James Kennedy
2018	A	`conf`	Learning Hidden Quantum Markov Models. AISTATS Siddarth Srinivasan, Geoffrey J. Gordon, Byron Boots
2018	A*	`conf`	Learning and Inference in Hilbert Space with Quantum Graphical Models. NeurIPS Siddarth Srinivasan, Carlton Downey, Byron Boots
2018	J	`jnl`	Learning and Inference in Hilbert Space with Quantum Graphical Models. CoRR Siddarth Srinivasan, Carlton Downey, Byron Boots