304 citations · 437 across the 8 of their papers we have counts for
8 papers
Neuromorphic Hebbian learning with magnetic tunnel junction synapses
Peng Zhou, Alexander J. Edwards, Frederick B. Mancoff +3
Neuromorphic computing aims to mimic both the function and structure of biological neural networks to provide artificial intelligence with extreme efficiency. Conventional approach…
NNQS-Transformer: an Efficient and Scalable Neural Network Quantum States Approach for Ab initio Quantum Chemistry
Yangjun Wu, Chu Guo, Yi Fan +2
Neural network quantum state (NNQS) has emerged as a promising candidate for quantum many-body problems, but its practical applications are often hindered by the high cost of sampl…
Compressing Neural Networks Using Tensor Networks with Exponentially Fewer Variational Parameters
Yong Qing, Ke Li, Peng-Fei Zhou +1
Neural network (NN) designed for challenging machine learning tasks is in general a highly nonlinear mapping that contains massive variational parameters. High complexity of NN, if…
Tensor Network Efficiently Representing Schmidt Decomposition of Quantum Many-Body States
Peng-Fei Zhou, Ying Lu, Jia-Hao Wang +1
Efficient methods to access the entanglement of a quantum many-body state, where the complexity generally scales exponentially with the system size , have long a concern. Here w…
Quantum compiling with a variational instruction set for accurate and fast quantum computing
Ying Lu, Peng-Fei Zhou, Shao-Ming Fei +1
The quantum instruction set (QIS) is defined as the quantum gates that are physically realizable by controlling the qubits in quantum hardware. Compiling quantum circuits into the…
Passive frustrated nanomagnet reservoir computing
Alexander J. Edwards, Dhritiman Bhattacharya, Peng Zhou +10
Reservoir computing (RC) has received recent interest because reservoir weights do not need to be trained, enabling extremely low-resource consumption implementations, which could…
Joint Extraction of Entities and Relations Based on a Novel Tagging Scheme
Suncong Zheng, Feng Wang, Hongyun Bao +3
Joint extraction of entities and relations is an important task in information extraction. To tackle this problem, we firstly propose a novel tagging scheme that can convert the jo…
Text Classification Improved by Integrating Bidirectional LSTM with Two-dimensional Max Pooling
Peng Zhou, Zhenyu Qi, Suncong Zheng +3
Recurrent Neural Network (RNN) is one of the most popular architectures used in Natural Language Processsing (NLP) tasks because its recurrent structure is very suitable to process…