Fetching the paper…
Reading the bibliography…
Direct sampling from a Slater determinant is combined with an autoregressive deep neural network as a Jastrow factor into a fully autoregressive Slater-Jastrow ansatz for variational quantum Monte Carlo, which allows for uncorrelated sampling.
Note on hartree’s method ,
J. C. Slater, · 1930
Earlier work this paper cites.
Many-body problem with strong forces ,
R. Jastrow, · 1955
Earlier work this paper cites.
Anomalous quantum hall effect: An incompressible quantum fluid with fractionally charged excitations ,
R. B. Laughlin, · 1983
Earlier work this paper cites.
Pair wave functions for strongly correlated fermions and their determinantal representation ,
J. Bouchaud, A. Georges and C. Lhuillier, · 1988
Earlier work this paper cites.
Information geometry of boltzmann machines ,
S. Amari, K. Kurata and H. Nagaoka, · 1992
Earlier work this paper cites.
Stable numerical simulations of models of interacting electrons in condensed matter physics ,
E. Loh Jr and J. Gubernatis, · 1992
Earlier work this paper cites.
Natural gradient works efficiently in learning ,
S.-i. Amari, · 1998
Earlier work this paper cites.
Meron-cluster solution of fermion sign problems ,
S. Chandrasekharan and U.-J. Wiese, · 1999
Earlier work this paper cites.
Taking on the curse of dimensionality in joint distributions using neural networks ,
S. Bengio and Y. Bengio, · 2000
Earlier work this paper cites.
Quantum monte carlo simulations of solids ,
W. M. C. Foulkes, L. Mitas, R. J. Needs and G. Rajagopal, · 2001
Earlier work this paper cites.
Generalized lanczos algorithm for variational quantum monte carlo ,
S. Sorella, · 2001
Earlier work this paper cites.
Training products of experts by minimizing contrastive divergence ,
G. E. Hinton, · 2002
Earlier work this paper cites.
Iterative Retraining of Quantum Spin Models Using Recurrent Neural Networks ,
C. Roth, · 2003
Earlier work this paper cites.
Correlated geminal wave function for molecules:?an efficient resonating valence bond approach ,
M. Casula, C. Attaccalite and S. Sorella, · 2004
Earlier work this paper cites.
Wave function optimization in the variational monte carlo method ,
S. Sorella, · 2005
Earlier work this paper cites.
On Representing (Anti)Symmetric Functions ,
M. Hutter, · 2007
Earlier work this paper cites.
Weak binding between two aromatic rings: Feeling the van der waals attraction by quantum monte carlo methods ,
S. Sorella, M. Casula and D. Rocca, · 2007
Earlier work this paper cites.
Pfaffian pairing and backflow wavefunctions for electronic structure quantum monte carlo methods ,
M. Bajdich, L. Mitas, L. K. Wagner and K. E. Schmidt, · 2008
Earlier work this paper cites.
The neural autoregressive distribution estimator ,
H. Larochelle and I. Murray, · 2011
Earlier work this paper cites.
Strategies for improving the efficiency of quantum monte carlo calculations ,
R. M. Lee, G. J. Conduit, N. Nemec, P. López Ríos and N. D. Drummond, · 2011
Earlier work this paper cites.
Computing the energy of a water molecule using multideterminants: A simple, efficient algorithm ,
B. K. Clark, M. A. Morales, J. McMinis, J. Kim and G. E. Scuseria, · 2011
Earlier work this paper cites.
Backflow correlations in the hubbard model: An efficient tool for the study of the metal-insulator transition and the large- u u limit ,
L. F. Tocchio, F. Becca and C. Gros, · 2011
Earlier work this paper cites.
Perfect sampling with unitary tensor networks ,
A. J. Ferris and G. Vidal, · 2012
Earlier work this paper cites.
Determinantal point processes for machine learning ,
A. Kulesza and B. Taskar, · 2012
Earlier work this paper cites.
Optimizing large parameter sets in variational quantum monte carlo ,
E. Neuscamman, C. J. Umrigar and G. K.-L. Chan, · 2012
Earlier work this paper cites.
Multideterminant wave functions in quantum monte carlo ,
M. A. Morales, J. McMinis, B. K. Clark, J. Kim and G. E. Scuseria, · 2012
Earlier work this paper cites.
Symmetry restoration in hartree-fock-bogoliubov based theories ,
G. F. Bertsch and L. M. Robledo, · 2012
Earlier work this paper cites.
Approximate Inference for Determinantal Point Processes ,
J. A. Gillenwater, · 2014
Earlier work this paper cites.
Adam: A Method for Stochastic Optimization ,
D. P. Kingma and J. Ba, · 2014
Earlier work this paper cites.
Made: Masked autoencoder for distribution estimation ,
M. Germain, K. Gregor, I. Murray and H. Larochelle, · 2015
Earlier work this paper cites.
Delving deep into rectifiers: Surpassing human-level performance on imagenet classification ,
K. He, X. Zhang, S. Ren and J. Sun, · 2015
Earlier work this paper cites.
Solving the fermion sign problem in quantum monte carlo simulations by majorana representation ,
Z.-X. Li, Y.-F. Jiang and H. Yao, · 2015
Earlier work this paper cites.
Split orthogonal group: A guiding principle for sign-problem-free fermionic simulations ,
L. Wang, Y.-H. Liu, M. Iazzi, M. Troyer and G. Harcos, · 2015
Cited alongside, same era.
Efficient continuous-time quantum monte carlo method for the ground state of correlated fermions ,
L. Wang, M. Iazzi, P. Corboz and M. Troyer, · 2015
Cited alongside, same era.
Neural autoregressive distribution estimation ,
B. Uria, M.-A. Côté, K. Gregor, I. Murray and H. Larochelle, · 2016
Cited alongside, same era.
Pixel recurrent neural networks ,
A. van den Oord, N. Kalchbrenner and K. Kavukcuoglu, · 2016
Cited alongside, same era.
WaveNet: A Generative Model for Raw Audio ,
A. van den Oord, S. Dieleman, H. Zen, K. Simonyan, O. Vinyals, A. Graves, N. Kalchbrenner, A. Senior and K. Kavukcuoglu, · 2016
Cited alongside, same era.
Phases of two-dimensional spinless lattice fermions with first-quantized deep neural-network quantum states ,
J. Stokes, J. R. Moreno, E. A. Pnevmatikakis and G. Carleo, · 2020
Later among the works it cites.
Neural network wave functions and the sign problem ,
A. Szabó and C. Castelnovo, · 2020
Later among the works it cites.
Deep learning-enhanced variational monte carlo method for quantum many-body physics ,
L. Yang, Z. Leng, G. Yu, A. Patel, W.-J. Hu and H. Pu, · 2020
Later among the works it cites.
Recurrent neural network wave functions ,
M. Hibat-Allah, M. Ganahl, L. E. Hayward, R. G. Melko and J. Carrasquilla, · 2020
Later among the works it cites.
Fermionic neural-network states for ab-initio electronic structure ,
K. Choo, A. Mezzacapo and G. Carleo, · 2020
Later among the works it cites.
Deep autoregressive models for the efficient variational simulation of many-body quantum systems ,
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
A. Scemama, T. Applencourt, E. Giner and M. Caffarel, · 2016
Cited alongside, same era.
Infinite variance in fermion quantum monte carlo calculations ,
H. Shi and S. Zhang, · 2016
Cited alongside, same era.
Solving the quantum many-body problem with artificial neural networks ,
G. Carleo and M. Troyer, · 2017
Cited alongside, same era.
Restricted boltzmann machine learning for solving strongly correlated quantum systems ,
Y. Nomura, A. S. Darmawan, Y. Yamaji and M. Imada, · 2017
Cited alongside, same era.
Quantum Monte Carlo approaches for correlated systems ,
F. Becca and S. Sorella, · 2017
Cited alongside, same era.
Quantum entanglement in neural network states ,
D.-L. Deng, X. Li and S. Das Sarma, · 2017
Cited alongside, same era.
QuSpin: a Python Package for Dynamics and Exact Diagonalisation of Quantum Many Body Systems part I: spin chains ,
P. Weinberg and M. Bukov, · 2017
Cited alongside, same era.
O. Sharir, Y. Levine, N. Wies, G. Carleo and A. Shashua, · 2020
Later among the works it cites.
Calculating rényi entropies with neural autoregressive quantum states ,
Z. Wang and E. J. Davis, · 2020
Later among the works it cites.
Ab initio solution of the many-electron schrödinger equation with deep neural networks ,
D. Pfau, J. S. Spencer, A. G. D. G. Matthews and W. M. C. Foulkes, · 2020
Later among the works it cites.
Deep-neural-network solution of the electronic schrödinger equation ,
J. Hermann, Z. Schätzle and F. Noé, · 2020
Later among the works it cites.
Vandermonde wave function ansatz for improved variational monte carlo ,
A. Acevedo, M. Curry, S. H. Joshi, B. Leroux and N. Malaya, · 2020
Later among the works it cites.
Artificial neural networks applied as molecular wave function solvers ,
P.-J. Yang, M. Sugiyama, K. Tsuda and T. Yanai, · 2020
Later among the works it cites.
Efficient local energy evaluation for multi-slater wave functions in orbital space quantum monte carlo ,
A. Mahajan and S. Sharma, · 2020
Later among the works it cites.
Hybrid convolutional neural network and projected entangled pair states wave functions for quantum many-particle states ,
X. Liang, S.-J. Dong and L. He, · 2021
Later among the works it cites.
Variational monte carlo calculations of a ≤ 4 a\leq 4 nuclei with an artificial neural-network correlator ansatz ,
C. Adams, G. Carleo, A. Lovato and N. Rocco, · 2021
Later among the works it cites.
Numerically exact mimicking of quantum gas microscopy for interacting lattice fermions ,
S. Humeniuk and Y. Wan, · 2021
Later among the works it cites.
Unbiased monte carlo cluster updates with autoregressive neural networks ,
D. Wu, R. Rossi and G. Carleo, · 2021
Later among the works it cites.
Gauge Invariant Autoregressive Neural Networks for Quantum Lattice Models ,
D. Luo, Z. Chen, K. Hu, Z. Zhao, V. Mikyoung Hur and B. K. Clark, · 2021
Later among the works it cites.
Direct sampling of projected entangled-pair states ,
T. Vieijra, J. Haegeman, F. Verstraete and L. Vanderstraeten, · 2021
Later among the works it cites.
Determinant-free fermionic wave function using feed-forward neural networks ,
K. Inui, Y. Kato and Y. Motome, · 2021
Later among the works it cites.
Solving quasiparticle band spectra of real solids using neural-network quantum states ,
N. Yoshioka, W. Mizukami and F. Nori, · 2021
Later among the works it cites.
Convergence to the fixed-node limit in deep variational monte carlo ,
Z. Schätzle, J. Hermann and F. Noé, · 2021
Later among the works it cites.
Fermion Sampling Made More Efficient ,
H. Sun, J. Zou and X. Li, · 2021
Later among the works it cites.
Helping restricted boltzmann machines with quantum-state representation by restoring symmetry ,
Y. Nomura, · 2021
Later among the works it cites.
New and practical formulation for overlaps of bogoliubov vacua ,
B. G. Carlsson and J. Rotureau, · 2021
Later among the works it cites.
Autoregressive neural network for simulating open quantum systems via a probabilistic formulation ,
D. Luo, Z. Chen, J. Carrasquilla and B. K. Clark, · 2022
Closest in time.
O ( N 2 ) O(N^{2}) Universal Antisymmetry in Fermionic Neural Networks ,
T. Pang, S. Yan and M. Lin, · 2022
Closest in time.
Fermionic wave functions from neural-network constrained hidden states ,
J. R. Moreno, G. Carleo, A. Georges and J. Stokes, · 2022
Closest in time.
Autoregressive neural-network wavefunctions for ab initio quantum chemistry ,
T. D. Barrett, A. Malyshev and A. Lvovsky, · 2022
Closest in time.
Scalable neural quantum states architecture for quantum chemistry ,
T. Zhao, J. Stokes and S. Veerapaneni, · 2022
Closest in time.
m ∗ m^{\ast} of two-dimensional electron gas: a neural canonical transformation study ,
H. Xie, L. Zhang and L. Wang, · 2022
Closest in time.
Variational Benchmarks for Quantum Many-Body Problems ,
D. Wu, R. Rossi, F. Vicentini, N. Astrakhantsev, F. Becca, X. Cao, J. Carrasquilla, F. Ferrari, A. Georges, M. Hibat-Allah, M. Imada, A. M. Läuchli et al. , · 2023
Closest in time.