21 citations · 21 across the 3 of their papers we have counts for
4 papers · 1 filter
Deep Symbolic Optimization: Reinforcement Learning for Symbolic Mathematics
Conor F. Hayes, Felipe Leno Da Silva, Jiachen Yang +15
Deep Symbolic Optimization (DSO) is a novel computational framework that enables symbolic optimization for scientific discovery, particularly in applications involving the search f…
DisCo-DSO: Coupling Discrete and Continuous Optimization for Efficient Generative Design in Hybrid Spaces
Jacob F. Pettit, Chak Shing Lee, Jiachen Yang +4
We consider the challenge of black-box optimization within hybrid discrete-continuous and variable-length spaces, a problem that arises in various applications, such as decision tr…
Single Episode Policy Transfer in Reinforcement Learning
Jiachen Yang, Brenden Petersen, Hongyuan Zha +1
Transfer and adaptation to new unknown environmental dynamics is a key challenge for reinforcement learning (RL). An even greater challenge is performing near-optimally in a single…
Precision medicine as a control problem: Using simulation and deep reinforcement learning to discover adaptive, personalized multi-cytokine therapy for sepsis
Brenden K. Petersen, Jiachen Yang, Will S. Grathwohl +4
Sepsis is a life-threatening condition affecting one million people per year in the US in which dysregulation of the body's own immune system causes damage to its tissues, resultin…