
Mixture of Linear Models Cosupervised by Deep Neural Networks
Deep neural network (DNN) models have achieved phenomenal success for ap...
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Unified analysis of finitesize error for periodic HartreeFock and second order MøllerPlesset perturbation theory
Despite decades of practice, finitesize errors in many widely used elec...
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Parallel transport dynamics for mixed quantum states with applications to timedependent density functional theory
Direct simulation of the von Neumann dynamics for a general (pure or mix...
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Staggered mesh method for correlation energy calculations of solids: Second order MøllerPlesset perturbation theory
The calculation of the MP2 correlation energy for extended systems can b...
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NeurTFDR: Controlling FDR by Incorporating Feature Hierarchy
Controlling false discovery rate (FDR) while leveraging the side informa...
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Timedependent unbounded Hamiltonian simulation with vector norm scaling
The accuracy of quantum dynamics simulation is usually measured by the e...
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NoiseRobust EndtoEnd Quantum Control using Deep Autoregressive Policy Networks
Variational quantum eigensolvers have recently received increased attent...
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Towards sharp error analysis of extended Lagrangian molecular dynamics
The extended Lagrangian molecular dynamics (XLMD) method provides a usef...
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Efficient LongRange Convolutions for Point Clouds
The efficient treatment of longrange interactions for point clouds is a...
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Reinforcement Learning for ManyBody Ground State Preparation based on CounterDiabatic Driving
The Quantum Approximate Optimization Ansatz (QAOA) is a prominent exampl...
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Fast inversion, preconditioned quantum linear system solvers, and fast evaluation of matrix functions
Preconditioning is the most widely used and effective way for treating i...
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Random circuit blockencoded matrix and a proposal of quantum LINPACK benchmark
The LINPACK benchmark reports the performance of a computer for solving ...
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Deep Latent Variable Model for Longitudinal Group Factor Analysis
In many scientific problems such as video surveillance, modern genomic a...
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86 PFLOPS Deep Potential Molecular Dynamics simulation of 100 million atoms with ab initio accuracy
We present the GPU version of DeePMDkit, which, upon training a deep ne...
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Nearoptimal ground state preparation
Preparing the ground state of a given Hamiltonian and estimating its gro...
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Learning the mapping x∑_i=1^d x_i^2: the cost of finding the needle in a haystack
The task of using machine learning to approximate the mapping x∑_i=1^d x...
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Split representation of adaptively compressed polarizability operator
The polarizability operator plays a central role in density functional p...
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Policy Gradient based Quantum Approximate Optimization Algorithm
The quantum approximate optimization algorithm (QAOA), as a hybrid quant...
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Numerical solution of large scale HartreeFockBogoliubov equations
The HartreeFockBogoliubov (HFB) theory is the starting point for treat...
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Deep VariableBlock Chain with Adaptive Variable Selection
The architectures of deep neural networks (DNN) rely heavily on the unde...
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Universal approximation of symmetric and antisymmetric functions
We consider universal approximations of symmetric and antisymmetric fun...
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Deep Density: circumventing the KohnSham equations via symmetry preserving neural networks
The recently developed Deep Potential [Phys. Rev. Lett. 120, 143001, 201...
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Solving quantum linear system problem with nearoptimal complexity
We present a simple algorithm to solve the quantum linear system problem...
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Variational embedding for quantum manybody problems
Quantum embedding theories are powerful tools for approximately solving ...
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Quantum linear system solver based on timeoptimal adiabatic quantum computing and quantum approximate optimization algorithm
We demonstrate that with an optimally tuned scheduling function, adiabat...
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Lowrank representation of tensor network operators with longrange pairwise interactions
Tensor network operators, such as the matrix product operator (MPO) and ...
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Explaining Deep Learning Models  A Bayesian Nonparametric Approach
Understanding and interpreting how machine learning (ML) models make dec...
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PSelInv  A Distributed Memory Parallel Algorithm for Selected Inversion: the nonsymmetric Case
This paper generalizes the parallel selected inversion algorithm called ...
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A General Framework of Enhancing Sparsity of Generalized Polynomial Chaos Expansions
Compressive sensing has become a powerful addition to uncertainty quanti...
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Towards Interrogating Discriminative Machine Learning Models
It is oftentimes impossible to understand how machine learning models re...
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A General Model for Robust Tensor Factorization with Unknown Noise
Because of the limitations of matrix factorization, such as losing spati...
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A LeftLooking Selected Inversion Algorithm and Task Parallelism on Shared Memory Systems
Given a sparse matrix A, the selected inversion algorithm is an efficien...
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Lin Lin
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