no code implementations • 24 Sep 2021 • Peter Reinhard Hansen, Chan Kim, Wade Kimbrough
We study recurrent patterns in volatility and volume for major cryptocurrencies, Bitcoin and Ether, using data from two centralized exchanges (Coinbase Pro and Binance) and a decentralized exchange (Uniswap V2).
1 code implementation • 3 Jun 2022 • Se-Wook Yoo, Chan Kim, Jin-Woo Choi, Seong-Woo Kim, Seung-Woo Seo
Applying reinforcement learning to autonomous driving entails particular challenges, primarily due to dynamically changing traffic flows.
no code implementations • 22 Nov 2022 • Jaehoon Lee, Chan Kim, Gyumin Lee, Haksoo Lim, Jeongwhan Choi, Kookjin Lee, Dongeun Lee, Sanghyun Hong, Noseong Park
Forecasting future outcomes from recent time series data is not easy, especially when the future data are different from the past (i. e. time series are under temporal drifts).
no code implementations • 19 May 2023 • Pablo Villanueva-Perez, Valerio Bellucci, Yuhe Zhang, Sarlota Birnsteinova, Rita Graceffa, Luigi Adriano, Eleni Myrto Asimakopoulou, Ilia Petrov, Zisheng Yao, Marco Romagnoni, Andrea Mazzolari, Romain Letrun, Chan Kim, Jayanath C. P. Koliyadu, Carsten Deiter, Richard Bean, Gabriele Giovanetti, Luca Gelisio, Tobias Ritschel, Adrian Mancuso, Henry N. Chapman, Alke Meents, Tokushi Sato, Patrik Vagovic
X-ray time-resolved tomography is one of the most popular X-ray techniques to probe dynamics in three dimensions (3D).
no code implementations • 12 Oct 2023 • Hwajong Lee, Chan Kim, Seong-Woo Kim
We present a model and parameter setting to build a virtual environment for different display transfer robots, and training methods of reinforcement learning on the environment to obtain an optimal scheduling of glass flow control systems.
1 code implementation • 7 Nov 2023 • Chan Kim, Jaekyung Cho, Christophe Bobda, Seung-Woo Seo, Seong-Woo Kim
Moreover, we show that our method can retrain the agent to recover from OOD situations even when in-distribution states are difficult to visit through exploration.