Eszter Vértes

Publication Activity (10 Years)

Years Active: 2018-2023
Publications (10 Years): 12

Top Topics

Discriminative Methods

Boltzmann Machine

Top Venues

Publications

Jannik Kossen, Catalina Cangea, Eszter Vértes, Andrew Jaegle, Viorica Patraucean, Ira Ktena, Nenad Tomasev, Danielle Belgrave
Active Acquisition for Multimodal Temporal Data: A Challenging Decision-Making Task. Trans. Mach. Learn. Res. 2023 (2023)
Jacob C. Walker, Eszter Vértes, Yazhe Li, Gabriel Dulac-Arnold, Ankesh Anand, Théophane Weber, Jessica B. Hamrick
Investigating the role of model-based learning in exploration and transfer. CoRR (2023)
Jacob C. Walker, Eszter Vértes, Yazhe Li, Gabriel Dulac-Arnold, Ankesh Anand, Theophane Weber, Jessica B. Hamrick
Investigating the Role of Model-Based Learning in Exploration and Transfer. ICML (2023)
Angelos Filos, Eszter Vértes, Zita Marinho, Gregory Farquhar, Diana Borsa, Abram L. Friesen, Feryal Behbahani, Tom Schaul, André Barreto, Simon Osindero
Model-Value Inconsistency as a Signal for Epistemic Uncertainty. ICML (2022)
Jannik Kossen, Catalina Cangea, Eszter Vértes, Andrew Jaegle, Viorica Patraucean, Ira Ktena, Nenad Tomasev, Danielle Belgrave
Active Acquisition for Multimodal Temporal Data: A Challenging Decision-Making Task. CoRR (2022)
Ankesh Anand, Jacob C. Walker, Yazhe Li, Eszter Vértes, Julian Schrittwieser, Sherjil Ozair, Theophane Weber, Jessica B. Hamrick
Procedural generalization by planning with self-supervised world models. ICLR (2022)
Ankesh Anand, Jacob Walker, Yazhe Li, Eszter Vértes, Julian Schrittwieser, Sherjil Ozair, Théophane Weber, Jessica B. Hamrick
Procedural Generalization by Planning with Self-Supervised World Models. CoRR (2021)
Angelos Filos, Eszter Vértes, Zita Marinho, Gregory Farquhar, Diana Borsa, Abram L. Friesen, Feryal Behbahani, Tom Schaul, André Barreto, Simon Osindero
Model-Value Inconsistency as a Signal for Epistemic Uncertainty. CoRR (2021)
Eszter Vértes, Maneesh Sahani
A neurally plausible model learns successor representations in partially observable environments. CoRR (2019)
Eszter Vértes, Maneesh Sahani
A neurally plausible model learns successor representations in partially observable environments. NeurIPS (2019)
Eszter Vértes, Maneesh Sahani
Flexible and accurate inference and learning for deep generative models. CoRR (2018)
Eszter Vértes, Maneesh Sahani
Flexible and accurate inference and learning for deep generative models. NeurIPS (2018)