Zenna Tavares

According to our database, Zenna Tavares authored at least 13 papers between 2017 and 2025.

Collaborative distances:

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

2025

ExoPredicator: Learning Abstract Models of Dynamic Worlds for Robot Planning.

Yichao Liang, Dat Nguyen, Cambridge Yang, Tianyang Li, Joshua B. Tenenbaum, Carl Edward Rasmussen, Adrian Weller, Zenna Tavares, Tom Silver, Kevin Ellis

CoRR, September, 2025

Assessing Adaptive World Models in Machines with Novel Games.

Lance Ying, Katherine M. Collins, Prafull Sharma, Cédric Colas, Kaiya Ivy Zhao, Adrian Weller, Zenna Tavares, Phillip Isola, Samuel J. Gershman, Jacob Andreas, Thomas L. Griffiths, François Chollet, Kelsey R. Allen, Joshua B. Tenenbaum

CoRR, July, 2025

2024

NeuroAI for AI Safety.

Patrick J. Mineault, Niccoló Zanichelli, Joanne Zichen Peng, Anton Arkhipov, Eli Bingham, Julian Jara-Ettinger, Emily Mackevicius, Adam H. Marblestone, Marcelo Mattar, Andrew Payne, Sophia Sanborn, Karen Schroeder, Zenna Tavares, Andreas S. Tolias

CoRR, 2024

Combining Induction and Transduction for Abstract Reasoning.

Wen-Ding Li, Keya Hu, Carter Larsen, Yuqing Wu, Simon Alford, Caleb Woo, Spencer M. Dunn, Hao Tang, Michelangelo Naim, Dat Nguyen, Wei-Long Zheng, Zenna Tavares, Yewen Pu, Kevin Ellis

CoRR, 2024

How does the primate brain combine generative and discriminative computations in vision?

Benjamin Peters, James J. DiCarlo, Todd M. Gureckis, Ralf Haefner, Leyla Isik, Joshua B. Tenenbaum, Talia Konkle, Thomas Naselaris, Kimberly L. Stachenfeld, Zenna Tavares, Doris Tsao, Ilker Yildirim, Nikolaus Kriegeskorte

CoRR, 2024

MetaCOG: A Heirarchical Probabilistic Model for Learning Meta-Cognitive Visual Representations.

Marlene Berke, Zhangir Azerbayev, Mario Belledonne, Zenna Tavares, Julian Jara-Ettinger

Proceedings of the Uncertainty in Artificial Intelligence, 2024

2023

Combining Functional and Automata Synthesis to Discover Causal Reactive Programs.

Ria Das, Joshua B. Tenenbaum, Armando Solar-Lezama, Zenna Tavares

Proc. ACM Program. Lang., January, 2023

2021

A Language for Counterfactual Generative Models.

Zenna Tavares, James Koppel, Xin Zhang, Ria Das, Armando Solar-Lezama

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

2020

Synthesizing Programmatic Policies that Inductively Generalize.

Jeevana Priya Inala, Osbert Bastani, Zenna Tavares, Armando Solar-Lezama

Proceedings of the 8th International Conference on Learning Representations, 2020

2019

The Random Conditional Distribution for Higher-Order Probabilistic Inference.

Zenna Tavares, Xin Zhang, Edgar Minaysan, Javier Burroni, Rajesh Ranganath, Armando Solar-Lezama

CoRR, 2019

Soft Constraints for Inference with Declarative Knowledge.

Zenna Tavares, Javier Burroni, Edgar Minaysan, Armando Solar-Lezama, Rajesh Ranganath

CoRR, 2019

Predicate Exchange: Inference with Declarative Knowledge.

Zenna Tavares, Javier Burroni, Edgar Minasyan, Armando Solar-Lezama, Rajesh Ranganath

Proceedings of the 36th International Conference on Machine Learning, 2019

2017

Mental Representations as Distribution-Sensitive Data Structures.

Zenna Tavares, Armando Solar-Lezama

Proceedings of the 2017 AAAI Spring Symposia, 2017