Learning Minimal Representations of Fermionic Ground States | Paper Citation Record

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This paper cites Tindall, M.

Learning Minimal Representations of Fermionic Ground States Tindall, M

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Learning Minimal Representations of Fermionic Ground States Patra, S

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This paper cites Menczer, M.

Learning Minimal Representations of Fermionic Ground States Menczer, M

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This paper cites Massively parallel quantum chemical density matrix renormalization group method.

Learning Minimal Representations of Fermionic Ground States Massively parallel quantum chemical density matrix renormalization group method

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This paper cites The density-matrix renormalization group in the age of matrix product states.

Learning Minimal Representations of Fermionic Ground States The density-matrix renormalization group in the age of matrix product states

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Observation 81676d5e-dca3-4f08-b043-c8b1f205498a · outbound

This paper cites Or´ us, Tensor networks for complex quantum systems, Nature Reviews Physics1, 538 (2019), publisher: Nature Publishing Group.

Learning Minimal Representations of Fermionic Ground States Or´ us, Tensor networks for complex quantum systems, Nature Reviews Physics1, 538 (2019), publisher: Nature Publishing Group

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This paper cites Helgaker, P.

Learning Minimal Representations of Fermionic Ground States Helgaker, P

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This paper cites Matrix Product States, Projected Entangled Pair States, and variational renormalization group methods for quantum spin systems.

Learning Minimal Representations of Fermionic Ground States Matrix Product States, Projected Entangled Pair States, and variational renormalization group methods for quantum spin systems

Reference 14

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Observation 7fafad32-2f3f-4b6e-ab1a-7269a7d8526b · outbound

This paper cites Eisert, M.

Learning Minimal Representations of Fermionic Ground States Eisert, M

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Learning Minimal Representations of Fermionic Ground States Burke and L

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This paper cites Burke, Perspective on density functional theory, The Journal of Chemical Physics136, 150901 (2012).

Learning Minimal Representations of Fermionic Ground States Burke, Perspective on density functional theory, The Journal of Chemical Physics136, 150901 (2012)

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This paper cites Mardirossian and M.

Learning Minimal Representations of Fermionic Ground States Mardirossian and M

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This paper cites Strongly Correlated Electron Materials: Dynamical Mean-Field Theory and Electronic Structure.

Learning Minimal Representations of Fermionic Ground States Strongly Correlated Electron Materials: Dynamical Mean-Field Theory and Electronic Structure

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This paper cites Dawid, J.

Learning Minimal Representations of Fermionic Ground States Dawid, J

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This paper cites Rocchetto, E.

Learning Minimal Representations of Fermionic Ground States Rocchetto, E

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Learning Minimal Representations of Fermionic Ground States Dunjko and H

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Learning Minimal Representations of Fermionic Ground States Carleo, I

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This paper cites Machine learning-based compression of quantum many body physics: PCA and autoencoder representation of the vertex function.

Learning Minimal Representations of Fermionic Ground States Machine learning-based compression of quantum many body physics: PCA and autoencoder representation of the vertex function

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Learning Minimal Representations of Fermionic Ground States Carleo and M

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Learning Minimal Representations of Fermionic Ground States Sajjan, J

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Learning Minimal Representations of Fermionic Ground States Representation Learning: A Review and New Perspectives

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Learning Minimal Representations of Fermionic Ground States I-Con: A Unifying Framework for Representation Learning

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Learning Minimal Representations of Fermionic Ground States A Simple Framework for Contrastive Learning of Visual Representations

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Learning Minimal Representations of Fermionic Ground States Solving deep-learning density functional theory via variational autoencoders

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Learning Minimal Representations of Fermionic Ground States Unresolved cited work

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Learning Minimal Representations of Fermionic Ground States Chen and W

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Learning Minimal Representations of Fermionic Ground States Learning Minimal Representations of Many-Body Physics from Snapshots of a Quantum Simulator

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Learning Minimal Representations of Fermionic Ground States Frohnert and E

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Learning Minimal Representations of Fermionic Ground States Hubbard, Electron correlations in narrow energy bands, Proceedings of the Royal Society of London

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Learning Minimal Representations of Fermionic Ground States Unresolved cited work

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Learning Minimal Representations of Fermionic Ground States Unresolved cited work

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Learning Minimal Representations of Fermionic Ground States Unresolved cited work

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Learning Minimal Representations of Fermionic Ground States Koridon, F

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This paper cites L¨ owdin, Quantum Theory of Many-Particle Sys- tems.

Learning Minimal Representations of Fermionic Ground States L¨ owdin, Quantum Theory of Many-Particle Sys- tems

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Learning Minimal Representations of Fermionic Ground States Unresolved cited work

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Learning Minimal Representations of Fermionic Ground States Akiba, S

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Learning Minimal Representations of Fermionic Ground States Learning Smooth Neural Functions via Lipschitz Regularization

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Learning Minimal Representations of Fermionic Ground States Nakata, B

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Learning Minimal Representations of Fermionic Ground States Unresolved cited work

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Learning Minimal Representations of Fermionic Ground States Accurate and scalable exchange-correlation with deep learning

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Learning Minimal Representations of Fermionic Ground States Kirkpatrick, B

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Learning Minimal Representations of Fermionic Ground States Nelson, R

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Learning Minimal Representations of Fermionic Ground States Paszke, S

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Learning Minimal Representations of Fermionic Ground States Adam: A Method for Stochastic Optimization

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Learning Minimal Representations of Fermionic Ground States SmoothGrad: removing noise by adding noise

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Learning Minimal Representations of Fermionic Ground States Deep Inside Convolutional Networks: Visualising Image Classification Models and Saliency Maps

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Learning Minimal Representations of Fermionic Ground States Axiomatic Attribution for Deep Networks

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Learning Minimal Representations of Fermionic Ground States The Shapley Value in Machine Learning

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Learning Minimal Representations of Fermionic Ground States A Unified Approach to Interpreting Model Predictions

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