Multi-scale generative adversarial network: three-dimensional reconstruction of the scoliotic spine from biplanar X-rays. [PDF]
Lai Y +7 more
europepmc +1 more source
ABSTRACT Natural products (NPs) have historically yielded numerous therapeutic agents, yet their integration into modern drug discovery has been constrained by chemical complexity, low abundance, laborious dereplication, and limited target annotation.
Antonio Lavecchia
wiley +1 more source
Markov Chain Wave Generative Adversarial Network for Bee Bioacoustic Signal Synthesis. [PDF]
Samarappuli K +3 more
europepmc +1 more source
ABSTRACT The design of control systems for high‐agility mechanical systems operating in extreme environments is a significant challenge in nonlinear dynamics. This paper addresses the complex dynamic control problem of a hypersonic interceptor, modeled as a multi‐input multi‐output (MIMO) mechanical system characterized by strong aerodynamic cross ...
Mohammad Mahdi Soori +1 more
wiley +1 more source
MGANSL: multi-network representation generating with generative adversarial network for synthetic lethality prediction. [PDF]
Li J, Lu X, Li Z, Liu X, Liu H, Ruan J.
europepmc +1 more source
Multi‐Agent Reinforcement Learning for Joint Police Patrol and Dispatch
ABSTRACT Police patrol units need to split their time between performing preventive patrol and being dispatched to serve emergency incidents. In the existing literature, patrol and dispatch decisions are often studied separately. We consider joint optimization of these two decisions to improve police operations efficiency and reduce response time to ...
Matthew Repasky, He Wang, Yao Xie
wiley +1 more source
Utilizing conditional generative adversarial network to generate head MRA based on nonvascular sequences: comparative study of single-modality and multi-modality methods. [PDF]
Song X +8 more
europepmc +1 more source
Interdiction Models and Heuristics for Graph Propagation
ABSTRACT Given a graph G=(V,E)$$ G=\left(V,E\right) $$ and a set S⊂V$$ S\subset V $$ of activated/infected nodes, we consider the problem of determining the set of c$$ c $$ nodes that minimizes the network propagation on the subgraph that results from the removal of those c$$ c $$ nodes. To measure network propagation, we assume that a node i$$ i $$ is
Agostinho Agra, José Maria Samuco
wiley +1 more source
Enhancing cone-beam computed tomography detail and interpretation with a generative adversarial network-driven artificial intelligence framework. [PDF]
Lin CY, Liu CM, Lin YC, Lin WC.
europepmc +1 more source

