455 citations · 1.1k across the 51 of their papers we have counts for
20 papers · 1 filter
Stability and Identification of Random Asynchronous Linear Time-Invariant Systems
Sahin Lale, Oguzhan Teke, Babak Hassibi +1
In many computational tasks and dynamical systems, asynchrony and randomization are naturally present and have been considered as ways to increase the speed and reduce the cost of…
Multi-task learning for electronic structure to predict and explore molecular potential energy surfaces
Zhuoran Qiao, Feizhi Ding, Matthew Welborn +5
We refine the OrbNet model to accurately predict energy, forces, and other response properties for molecules using a graph neural-network architecture based on features from low-co…
MEGATRON-CNTRL: Controllable Story Generation with External Knowledge Using Large-Scale Language Models
Peng Xu, Mostofa Patwary, Mohammad Shoeybi +4
Existing pre-trained large language models have shown unparalleled generative capabilities. However, they are not controllable. In this paper, we propose MEGATRON-CNTRL, a novel fr…
Deep learning-based computer vision to recognize and classify suturing gestures in robot-assisted surgery
Francisco Luongo, Ryan Hakim, Jessica H. Nguyen +2
Our previous work classified a taxonomy of suturing gestures during a vesicourethral anastomosis of robotic radical prostatectomy in association with tissue tears and patient outco…
OCEAN: Online Task Inference for Compositional Tasks with Context Adaptation
Hongyu Ren, Yuke Zhu, Jure Leskovec +2
Real-world tasks often exhibit a compositional structure that contains a sequence of simpler sub-tasks. For instance, opening a door requires reaching, grasping, rotating, and pull…
Automated Synthetic-to-Real Generalization
Wuyang Chen, Zhiding Yu, Zhangyang Wang +1
Models trained on synthetic images often face degraded generalization to real data. As a convention, these models are often initialized with ImageNet pre-trained representation. Ye…