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08/18/2023
Variational optimization of the amplitude of neural-network quantum many-body ground states
Neural-network quantum states (NQSs), variationally optimized by combini...
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05/11/2022
A simple framework for contrastive learning phases of matter
A main task in condensed-matter physics is to recognize, classify, and c...
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03/02/2022
Parameter-Efficient Mixture-of-Experts Architecture for Pre-trained Language Models
The state-of-the-art Mixture-of-Experts (short as MoE) architecture has ...
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06/04/2021
Enabling Lightweight Fine-tuning for Pre-trained Language Model Compression based on Matrix Product Operators
This paper presents a novel pre-trained language models (PLM) compressio...
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12/22/2020
Compressing LSTM Networks by Matrix Product Operators
Long Short-Term Memory (LSTM) models are the building blocks of many sta...
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10/10/2020
A Model Compression Method with Matrix Product Operators for Speech Enhancement
The deep neural network (DNN) based speech enhancement approaches have a...
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04/11/2019
