-- Starting Electronic System Level (ESL) design flows with executable High-Level Models (HLMs) has the potential to sustainably improve productivity. However, writing good HLMs fo...
Christian Zebelein, Joachim Falk, Christian Haubel...
Reinforcement learning is a paradigm under which an agent seeks to improve its policy by making learning updates based on the experiences it gathers through interaction with the en...
Human crooked neck protein (hcrn) containing 17 HAT or TPR repeats plays a role in pre-mRNA processing. Conserved residues in the TPR consensus sequence of 34 aa were found at hel...
In this paper we summarize recent developments in compact dynamical modeling for both linear and nonlinear systems arising in analog applications. These techniques include methods...
We propose a modular reinforcement learning architecture for non-linear, nonstationary control tasks, which we call multiple model-based reinforcement learning (MMRL). The basic i...