Papers
2,306 papers found
Hierarchical Attentive Recurrent Tracking
Adam Kosiorek, Alex Bewley, Ingmar Posner
Adaptive Skip Intervals: Temporal Abstraction for Recurrent Dynamical Models
Alexander Neitz, Giambattista Parascandolo, Stefan Bauer et al.
Compact Representation of Uncertainty in Clustering
Craig Greenberg, Nicholas Monath, Ari Kobren et al.
Invariant Representations without Adversarial Training
Daniel Moyer, Shuyang Gao, Rob Brekelmans et al.
A Unified Framework for Extensive-Form Game Abstraction with Bounds
Christian Kroer, Tuomas Sandholm
Learning Abstract Options
Matthew Riemer, Miao Liu, Gerald Tesauro
Language as an Abstraction for Hierarchical Deep Reinforcement Learning
YiDing Jiang, Shixiang (Shane) Gu, Kevin P. Murphy et al.
Text-Based Interactive Recommendation via Constraint-Augmented Reinforcement Learning
Ruiyi Zhang, Tong Yu, Yilin Shen et al.
Abstraction based Output Range Analysis for Neural Networks
Pavithra Prabhakar, Zahra Rahimi Afzal
Gradient Information for Representation and Modeling
Jie Ding, Robert Calderbank, Vahid Tarokh
Transfer Anomaly Detection by Inferring Latent Domain Representations
Atsutoshi Kumagai, Tomoharu Iwata, Yasuhiro Fujiwara
Reinforcement Learning with Convex Constraints
Sobhan Miryoosefi, Kianté Brantley, Hal Daume III et al.
Inherent Tradeoffs in Learning Fair Representations
Han Zhao, Geoff Gordon
Variational Temporal Abstraction
Taesup Kim, Sungjin Ahn, Yoshua Bengio
Are Disentangled Representations Helpful for Abstract Visual Reasoning?
Sjoerd van Steenkiste, Francesco Locatello, Jürgen Schmidhuber et al.
Learning by Abstraction: The Neural State Machine
Drew Hudson, Christopher D. Manning
Abstract Reasoning with Distracting Features
Kecheng Zheng, Zheng-Jun Zha, Wei Wei
Deep reconstruction of strange attractors from time series
William Gilpin
Learning abstract structure for drawing by efficient motor program induction
Lucas Tian, Kevin Ellis, Marta Kryven et al.
Learning About Objects by Learning to Interact with Them
Martin Lohmann, Jordi Salvador, Aniruddha Kembhavi et al.
Evaluating and Rewarding Teamwork Using Cooperative Game Abstractions
Tom Yan, Christian Kroer, Alexander Peysakhovich
Neural Star Domain as Primitive Representation
Yuki Kawana, Yusuke Mukuta, Tatsuya Harada
Learning Agent Representations for Ice Hockey
Guiliang Liu, Oliver Schulte, Pascal Poupart et al.
Temporally Abstract Partial Models
Khimya Khetarpal, Zafarali Ahmed, Gheorghe Comanici et al.
Learning Markov State Abstractions for Deep Reinforcement Learning
Cameron Allen, Neev Parikh, Omer Gottesman et al.