Abstract This work introduces a method to tune a sequence-based generative model for molecular de novo design that through augmented episodic likelihood can learn to generate structures with certain specified desirable properties.We demonstrate how this model can execute a range of tasks such as generating analogues to a query structure and generat
Deterrent Action of Acamprosate: A Case Report
Background: Among the three pharmacological agents available for alcohol de-addiction, acamprosate and naltrexone are considered anti-craving agents.Among these two, acamprosate is better tolerated, has low abuse potential, and is safe in overdose.But the mechanism of action of acamprosate still remains unclear.Case Report: This case report gives a
Efficient deep reinforcement learning based task scheduler in multi cloud environment
Abstract Task scheduling problem (TSP) is huge challenge in cloud computing paradigm as number of tasks comes to cloud application platform vary from time to time and all the tasks consists of variable length, runtime capacities.All these tasks may generated from various heterogeneous resources which comes onto cloud console directly effects the pe
Joint Conditional Random Field Filter for Multi-Object Tracking
Object tracking can improve the performance of mobile robot especially in populated dynamic environments.A novel joint conditional random field Filter (JCRFF) based on conditional random field with hierarchical structure is proposed for multi-object tracking by abstracting the data associations between objects and measurements to be a smart tv pana