1 citations · 3 across the 7 of their papers we have counts for
8 papers
S2Act: Simple Spiking Actor
Ugur Akcal, Seung Hyun Kim, Mikihisa Yuasa +6
Spiking neural networks (SNNs) and biologically-inspired learning mechanisms are attractive in mobile robotics, where the size and performance of onboard neural network policies ar…
Towards Efficient Large Scale Spatial-Temporal Time Series Forecasting via Improved Inverted Transformers
Jiarui Sun, Chin-Chia Michael Yeh, Yujie Fan +10
Time series forecasting at scale presents significant challenges for modern prediction systems, particularly when dealing with large sets of synchronized series, such as in a globa…
MOOSS: Mask-Enhanced Temporal Contrastive Learning for Smooth State Evolution in Visual Reinforcement Learning
Jiarui Sun, M. Ugur Akcal, Wei Zhang +1
In visual Reinforcement Learning (RL), learning from pixel-based observations poses significant challenges on sample efficiency, primarily due to the complexity of extracting infor…
Revealing the Power of Masked Autoencoders in Traffic Forecasting
Jiarui Sun, Yujie Fan, Chin-Chia Michael Yeh +2
Traffic forecasting, crucial for urban planning, requires accurate predictions of spatial-temporal traffic patterns across urban areas. Existing research mainly focuses on designin…
Towards Accurate Human Motion Prediction via Iterative Refinement
Jiarui Sun, Girish Chowdhary
Human motion prediction aims to forecast an upcoming pose sequence given a past human motion trajectory. To address the problem, in this work we propose FreqMRN, a human motion pre…
CoMusion: Towards Consistent Stochastic Human Motion Prediction via Motion Diffusion
Jiarui Sun, Girish Chowdhary
Stochastic Human Motion Prediction (HMP) aims to predict multiple possible future human pose sequences from observed ones. Most prior works learn motion distributions through encod…
Dynamic Graph Node Classification via Time Augmentation
Jiarui Sun, Mengting Gu, Chin-Chia Michael Yeh +3
Node classification for graph-structured data aims to classify nodes whose labels are unknown. While studies on static graphs are prevalent, few studies have focused on dynamic gra…
Elastica: A compliant mechanics environment for soft robotic control
Noel Naughton, Jiarui Sun, Arman Tekinalp +2
Soft robots are notoriously hard to control. This is partly due to the scarcity of models able to capture their complex continuum mechanics, resulting in a lack of control methodol…