84 citations · 148 across the 5 of their papers we have counts for
5 papers
Simple Unsupervised Object-Centric Learning for Complex and Naturalistic Videos
Gautam Singh, Yi-Fu Wu, Sungjin Ahn
Unsupervised object-centric learning aims to represent the modular, compositional, and causal structure of a scene as a set of object representations and thereby promises to resolv…
Structured World Belief for Reinforcement Learning in POMDP
Gautam Singh, Skand Peri, Junghyun Kim +2
Object-centric world models provide structured representation of the scene and can be an important backbone in reinforcement learning and planning. However, existing approaches suf…
Robustifying Sequential Neural Processes
Jaesik Yoon, Gautam Singh, Sungjin Ahn
When tasks change over time, meta-transfer learning seeks to improve the efficiency of learning a new task via both meta-learning and transfer-learning. While the standard attentio…
SPACE: Unsupervised Object-Oriented Scene Representation via Spatial Attention and Decomposition
Zhixuan Lin, Yi-Fu Wu, Skand Vishwanath Peri +5
The ability to decompose complex multi-object scenes into meaningful abstractions like objects is fundamental to achieve higher-level cognition. Previous approaches for unsupervise…
Sequential Neural Processes
Gautam Singh, Jaesik Yoon, Youngsung Son +1
Neural Processes combine the strengths of neural networks and Gaussian processes to achieve both flexible learning and fast prediction in stochastic processes. However, a large cla…