1 citations · 1 across the 9 of their papers we have counts for
9 papers
Learning Multi-Timescale Abstractions for Hierarchical Combinatorial Planning
Vivienne Huiling Wang, Tinghuai Wang, Joni Pajarinen
The combination of exponentially large action spaces, stochastic dynamics, and long-horizon decision-making under limited resources makes Sequential Stochastic Combinatorial Optimi…
Hierarchical Reinforcement Learning with Uncertainty-Guided Diffusional Subgoals
Vivienne Huiling Wang, Tinghuai Wang, Joni Pajarinen
Hierarchical reinforcement learning (HRL) learns to make decisions on multiple levels of temporal abstraction. A key challenge in HRL is that the low-level policy changes over time…
Vector-Quantized Vision Foundation Models for Object-Centric Learning
Rongzhen Zhao, Vivienne Wang, Juho Kannala +1
Object-Centric Learning (OCL) aggregates image or video feature maps into object-level feature vectors, termed \textit{slots}. It's self-supervision of reconstructing the input fro…
Grouped Discrete Representation for Object-Centric Learning
Rongzhen Zhao, Vivienne Wang, Juho Kannala +1
Object-Centric Learning (OCL) aims to discover objects in images or videos by reconstructing the input. Representative methods achieve this by reconstructing the input as its Varia…
Multi-Scale Fusion for Object Representation
Rongzhen Zhao, Vivienne Wang, Juho Kannala +1
Representing images or videos as object-level feature vectors, rather than pixel-level feature maps, facilitates advanced visual tasks. Object-Centric Learning (OCL) primarily achi…
Organized Grouped Discrete Representation for Object-Centric Learning
Rongzhen Zhao, Vivienne Wang, Juho Kannala +1
Object-Centric Learning (OCL) represents dense image or video pixels as sparse object features. Representative methods utilize discrete representation composed of Variational Autoe…
Grouped Discrete Representation Guides Object-Centric Learning
Rongzhen Zhao, Vivienne Wang, Juho Kannala +1
Similar to humans perceiving visual scenes as objects, Object-Centric Learning (OCL) can abstract dense images or videos into sparse object-level features. Transformer-based OCL ha…
Probabilistic Subgoal Representations for Hierarchical Reinforcement learning
Vivienne Huiling Wang, Tinghuai Wang, Wenyan Yang +2
In goal-conditioned hierarchical reinforcement learning (HRL), a high-level policy specifies a subgoal for the low-level policy to reach. Effective HRL hinges on a suitable subgoal…
State-Conditioned Adversarial Subgoal Generation
Vivienne Huiling Wang, Joni Pajarinen, Tinghuai Wang +1
Hierarchical reinforcement learning (HRL) proposes to solve difficult tasks by performing decision-making and control at successively higher levels of temporal abstraction. However…