51 citations
- Samsung (South Korea)KR6 papers
- Missouri University of Science and TechnologyUS2 papers
- Applied Materials (United States)US1 paper
- Georgia Institute of TechnologyUS1 paper
- Korea Advanced Institute of Science and TechnologyKR1 paper
- Pohang University of Science and TechnologyKR1 paper
- Seoul Media Institute of TechnologyKR1 paper
- Seoul National UniversityKR1 paper
- Universidad de GranadaES1 paper
6 papers
Experiments and Modeling of Defect Dynamics and BTI Behavior in Doped InO TFTs during C Post-Processing Forming Gas Annealing
Yu-Hsin Kuo, Chengyang Zhang, Priyankka Ravikumar +13
We investigate the impact of a monolithic three-dimensional (M3D) integration process-critical C post-processing forming gas anneal (FGA) on the electrical performance,…
SNAC: Speaker-normalized affine coupling layer in flow-based architecture for zero-shot multi-speaker text-to-speech
Byoung Jin Choi, Myeonghun Jeong, Joun Yeop Lee +1
Zero-shot multi-speaker text-to-speech (ZSM-TTS) models aim to generate a speech sample with the voice characteristic of an unseen speaker. The main challenge of ZSM-TTS is to incr…
Successive Cancellation Decoding with Future Constraints for Polar Codes Over the Binary Erasure Channel
Min Jang, Jong-Hwan Kim, Seho Myung +1
In the conventional successive cancellation (SC) decoder for polar codes, all the future bits to be estimated later are treated as random variables. However, polar codes inevitably…
Reinforcement Learning for Vision-based Object Manipulation with Non-parametric Policy and Action Primitives
Dongwon Son, Myungsin Kim, Jaecheol Sim +1
The object manipulation is a crucial ability for a service robot, but it is hard to solve with reinforcement learning due to some reasons such as sample efficiency. In this paper,…
Grasping as Inference: Reactive Grasping in Heavily Cluttered Environment
Dongwon Son
Although, in the task of grasping via a data-driven method, closed-loop feedback and predicting 6 degrees of freedom (DoF) grasp rather than conventionally used 4DoF top-down grasp…
Transformer Network-based Reinforcement Learning Method for Power Distribution Network (PDN) Optimization of High Bandwidth Memory (HBM)
Hyunwook Park, Minsu Kim, Seongguk Kim +9
In this article, for the first time, we propose a transformer network-based reinforcement learning (RL) method for power distribution network (PDN) optimization of high bandwidth m…