Microbial Decomposition
Microbial decomposition research focuses on understanding and modeling the breakdown of organic matter by microorganisms, primarily to improve predictions of nutrient cycling and carbon sequestration in various environments. Current research emphasizes developing advanced computational methods, including neural networks and decomposition-based algorithms, to analyze complex datasets and simulate decomposition processes more accurately. This work is significant for advancing ecological modeling, improving predictions of environmental change, and informing applications in areas such as bioremediation and waste management. Furthermore, decomposition techniques are being applied across diverse fields, from image analysis and natural language processing to robotics and materials science, highlighting its broad utility in data analysis and model optimization.
Papers
ADaPT: As-Needed Decomposition and Planning with Language Models
Archiki Prasad, Alexander Koller, Mareike Hartmann, Peter Clark, Ashish Sabharwal, Mohit Bansal, Tushar Khot
Long-term Time Series Forecasting based on Decomposition and Neural Ordinary Differential Equations
Seonkyu Lim, Jaehyeon Park, Seojin Kim, Hyowon Wi, Haksoo Lim, Jinsung Jeon, Jeongwhan Choi, Noseong Park