It has been shown that entanglement distillation of Gaussian entangled states by means of local photon subtraction can be improved by local Gaussian transformations. Here we show that a similar effect can be expected for the distillation of an asymmetric Gaussian entangled state that is produced by a single squeezed beam. We show that for low initial entanglement, our largely simplified protoco...

Knowledge Distillation (KD), which is an effective model compression and acceleration technique, has been successfully applied to graph neural networks (GNNs) recently. Existing approaches utilize a single GNN as the teacher distill knowledge. However, we notice that models with different number of layers demonstrate classification abilities on nodes degrees. On one hand, for high degrees, thei...

In real applications, new object classes often emerge after the detection model has been trained on a prepared dataset with fixed classes. Fine-tuning old only data will lead to well-known phenomenon of catastrophic forgetting, which severely degrades performance modern detectors. Due storage burden, privacy and time consumption, sometimes it is impractical train from scratch all both this pape...

Abstract Knowledge distillation is a simple yet effective technique for deep model compression, which aims to transfer the knowledge learned by large teacher small student model. To mimic how teaches student, existing methods mainly adapt an unidirectional transfer, where extracted from different intermedicate layers of used guide However, it turns out that students can learn more effectively t...

This article deals with the issues associated with developing a new design methodology for the nonlinear model-predictive control (MPC) of a chemical plant. A combination of multiple neural networks is selected and used to model a nonlinear multi-input multi-output (MIMO) process with time delays.  An optimization procedure for a neural MPC algorithm based on this model is then developed. T...

a shortcut procedure as quick, easy-to use method for design and simulation of multicomponent batch distillation is used to predict the operating condition of recovering xylene from solvent in an existing batch distillation column in benzol refinery. the procedure can be used to investigate the effect of the operating parameters on the operation of column for three possible modes of batch disti...

Knowledge distillation is an effective method to transfer the knowledge from cumbersome teacher model lightweight student model. Online uses ensembled prediction results of multiple models as soft targets train each However, homogenization problem will lead difficulty in further improving performance. In this work, we propose a new enhance diversity among models. We introduce Feature Fusion Mod...