A Multi-stage Constrained Optimization Framework for Data-driven Problems | Paper Citation Record

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This paper cites An Introduction to Variational Autoen- coders,.

A Multi-stage Constrained Optimization Framework for Data-driven Problems An Introduction to Variational Autoen- coders,

Reference 1

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This paper cites Shape your Space: A Gaussian Mixture Regularization Approach to Deterministic Autoencoders,.

A Multi-stage Constrained Optimization Framework for Data-driven Problems Shape your Space: A Gaussian Mixture Regularization Approach to Deterministic Autoencoders,

Reference 2

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This paper cites Machine learning framework for quantum sampling of highly constrained, continuous optimization problems,.

A Multi-stage Constrained Optimization Framework for Data-driven Problems Machine learning framework for quantum sampling of highly constrained, continuous optimization problems,

Reference 3

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This paper cites COIL: Constrained optimization in learned latent space: Learning representations for valid solutions,.

A Multi-stage Constrained Optimization Framework for Data-driven Problems COIL: Constrained optimization in learned latent space: Learning representations for valid solutions,

Reference 4

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This paper cites Constrained Bayesian Optimization for Automatic Chemical Design,.

A Multi-stage Constrained Optimization Framework for Data-driven Problems Constrained Bayesian Optimization for Automatic Chemical Design,

Reference 5

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This paper cites Learning Heuristics for Combinatorial Optimization Prob- lems with Deep Neural Networks,.

A Multi-stage Constrained Optimization Framework for Data-driven Problems Learning Heuristics for Combinatorial Optimization Prob- lems with Deep Neural Networks,

Reference 6

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This paper cites Improving black- box optimization in V AE latent space using decoder uncertainty,.

A Multi-stage Constrained Optimization Framework for Data-driven Problems Improving black- box optimization in V AE latent space using decoder uncertainty,

Reference 7

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This paper cites Constrained Generation of Semantically Valid Graphs via Regularizing Variational Autoencoders,.

A Multi-stage Constrained Optimization Framework for Data-driven Problems Constrained Generation of Semantically Valid Graphs via Regularizing Variational Autoencoders,

Reference 8

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This paper cites Constrained Graph Variational Autoencoders for Molecule Design,.

A Multi-stage Constrained Optimization Framework for Data-driven Problems Constrained Graph Variational Autoencoders for Molecule Design,

Reference 9

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This paper cites Automatic chemical design using a data-driven continuous representation of molecules,.

A Multi-stage Constrained Optimization Framework for Data-driven Problems Automatic chemical design using a data-driven continuous representation of molecules,

Reference 10

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This paper cites End-to-End Constrained Optimization Learning: A Survey,.

A Multi-stage Constrained Optimization Framework for Data-driven Problems End-to-End Constrained Optimization Learning: A Survey,

Reference 11

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This paper cites Diagnosing and Enhancing V AE Models,.

A Multi-stage Constrained Optimization Framework for Data-driven Problems Diagnosing and Enhancing V AE Models,

Reference 12

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This paper cites Bayesian deep convolutional encoder–decoder networks for surrogate modeling and uncertainty quantification,.

A Multi-stage Constrained Optimization Framework for Data-driven Problems Bayesian deep convolutional encoder–decoder networks for surrogate modeling and uncertainty quantification,

Reference 13

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This paper cites Variational Autoencoder-Based Metamodeling for Multi-Objective Topology Optimization of Electrical Machines,.

A Multi-stage Constrained Optimization Framework for Data-driven Problems Variational Autoencoder-Based Metamodeling for Multi-Objective Topology Optimization of Electrical Machines,

Reference 14

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This paper cites Neural Architecture Optimization with Graph V AE,.

A Multi-stage Constrained Optimization Framework for Data-driven Problems Neural Architecture Optimization with Graph V AE,

Reference 15

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This paper cites DC3: A learning method for optimization with hard constraints.

A Multi-stage Constrained Optimization Framework for Data-driven Problems DC3: A learning method for optimization with hard constraints

Reference 16

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This paper cites Lagrangian Duality for Constrained Deep Learning,.

A Multi-stage Constrained Optimization Framework for Data-driven Problems Lagrangian Duality for Constrained Deep Learning,

Reference 17

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This paper cites Self-Supervised Primal-Dual Learning for Constrained Optimization,.

A Multi-stage Constrained Optimization Framework for Data-driven Problems Self-Supervised Primal-Dual Learning for Constrained Optimization,

Reference 18

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This paper cites Loss landscapes and optimization in over-parameterized non-linear systems and neural networks,.

A Multi-stage Constrained Optimization Framework for Data-driven Problems Loss landscapes and optimization in over-parameterized non-linear systems and neural networks,

Reference 19

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This paper cites Optimizing Variational Graph Au- toencoder for Community Detection with Dual Optimization,.

A Multi-stage Constrained Optimization Framework for Data-driven Problems Optimizing Variational Graph Au- toencoder for Community Detection with Dual Optimization,

Reference 20

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This paper cites Pythae: Unifying Generative Autoencoders in Python – A Benchmarking Use Case,.

A Multi-stage Constrained Optimization Framework for Data-driven Problems Pythae: Unifying Generative Autoencoders in Python – A Benchmarking Use Case,

Reference 21

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Observation bcc6aa05-9bb1-4bc1-a758-f7edacd77b33 · outbound

This paper cites Variational Inference with Normalizing Flows.

A Multi-stage Constrained Optimization Framework for Data-driven Problems Variational Inference with Normalizing Flows

Reference 22

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This paper cites Improving Variational Inference with Inverse Autoregres- sive Flow,.

A Multi-stage Constrained Optimization Framework for Data-driven Problems Improving Variational Inference with Inverse Autoregres- sive Flow,

Reference 23

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This paper cites Improving Variational Auto-Encoders using Householder Flow,.

A Multi-stage Constrained Optimization Framework for Data-driven Problems Improving Variational Auto-Encoders using Householder Flow,

Reference 24

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This paper cites Importance Weighted Autoencoders,.

A Multi-stage Constrained Optimization Framework for Data-driven Problems Importance Weighted Autoencoders,

Reference 25

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This paper cites Posterior Collapse and Latent Variable Non-identifiability,.

A Multi-stage Constrained Optimization Framework for Data-driven Problems Posterior Collapse and Latent Variable Non-identifiability,

Reference 26

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This paper cites Disentangling by Factorising,.

A Multi-stage Constrained Optimization Framework for Data-driven Problems Disentangling by Factorising,

Reference 27

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This paper cites Isolating Sources of Disentanglement in Variational Autoencoders,.

A Multi-stage Constrained Optimization Framework for Data-driven Problems Isolating Sources of Disentanglement in Variational Autoencoders,

Reference 28

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This paper cites Deep Unsupervised Clustering with Gaussian Mixture Variational Autoencoders,.

A Multi-stage Constrained Optimization Framework for Data-driven Problems Deep Unsupervised Clustering with Gaussian Mixture Variational Autoencoders,

Reference 29

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This paper cites From Variational to Deterministic Autoencoders,.

A Multi-stage Constrained Optimization Framework for Data-driven Problems From Variational to Deterministic Autoencoders,

Reference 30

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This paper cites Improving Variational Encoder-Decoders in Dialogue Generation,.

A Multi-stage Constrained Optimization Framework for Data-driven Problems Improving Variational Encoder-Decoders in Dialogue Generation,

Reference 31

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This paper cites Generative Models for Irregular Sequential Data,.

A Multi-stage Constrained Optimization Framework for Data-driven Problems Generative Models for Irregular Sequential Data,

Reference 32

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This paper cites Generative Modeling of Regular and Irregular Time Series Data via Koopman V AEs,.

A Multi-stage Constrained Optimization Framework for Data-driven Problems Generative Modeling of Regular and Irregular Time Series Data via Koopman V AEs,

Reference 33

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This paper cites AutoV AE: Mismatched Variational Autoencoder with Irregular Posterior-Prior Pairing,.

A Multi-stage Constrained Optimization Framework for Data-driven Problems AutoV AE: Mismatched Variational Autoencoder with Irregular Posterior-Prior Pairing,

Reference 34

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This paper cites Autoencoding Variational Autoencoder,.

A Multi-stage Constrained Optimization Framework for Data-driven Problems Autoencoding Variational Autoencoder,

Reference 35

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This paper cites Coupled Variational Autoencoder,.

A Multi-stage Constrained Optimization Framework for Data-driven Problems Coupled Variational Autoencoder,

Reference 36

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This paper cites Denoising Diffusion Probabilistic Models,.

A Multi-stage Constrained Optimization Framework for Data-driven Problems Denoising Diffusion Probabilistic Models,

Reference 37

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This paper cites NV AE: A Deep Hierarchical Variational Autoencoder,.

A Multi-stage Constrained Optimization Framework for Data-driven Problems NV AE: A Deep Hierarchical Variational Autoencoder,

Reference 38

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This paper cites Challenging Common Assumptions in the Unsupervised Learning of Disentangled Representations,.

A Multi-stage Constrained Optimization Framework for Data-driven Problems Challenging Common Assumptions in the Unsupervised Learning of Disentangled Representations,

Reference 39

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This paper cites Imposing Hard Constraints on Deep Networks: Promises and Limitations.

A Multi-stage Constrained Optimization Framework for Data-driven Problems Imposing Hard Constraints on Deep Networks: Promises and Limitations

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This paper cites A Primal Dual Formulation For Deep Learning With Constraints,.

A Multi-stage Constrained Optimization Framework for Data-driven Problems A Primal Dual Formulation For Deep Learning With Constraints,

Reference 41

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This paper cites A Brief History of Filter Methods,.

A Multi-stage Constrained Optimization Framework for Data-driven Problems A Brief History of Filter Methods,

Reference 42

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This paper cites The Statistical Filter Approach to Constrained Optimization,.

A Multi-stage Constrained Optimization Framework for Data-driven Problems The Statistical Filter Approach to Constrained Optimization,

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This paper cites Deep learning methods for inverse problems,.

A Multi-stage Constrained Optimization Framework for Data-driven Problems Deep learning methods for inverse problems,

Reference 44

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This paper cites Denoising criterion for variational auto-encoding framework,.

A Multi-stage Constrained Optimization Framework for Data-driven Problems Denoising criterion for variational auto-encoding framework,

Reference 45

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This paper cites Solving Bayesian Inverse Problems via Variational Autoencoders,.

A Multi-stage Constrained Optimization Framework for Data-driven Problems Solving Bayesian Inverse Problems via Variational Autoencoders,

Reference 46

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This paper cites Variational Autoencoder Inverse Mapper: An End-to-End Deep Learning Framework for Inverse Problems,.

A Multi-stage Constrained Optimization Framework for Data-driven Problems Variational Autoencoder Inverse Mapper: An End-to-End Deep Learning Framework for Inverse Problems,

Reference 47

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This paper cites Electric Machine Inverse Design with Variational Auto-Encoder (V AE),.

A Multi-stage Constrained Optimization Framework for Data-driven Problems Electric Machine Inverse Design with Variational Auto-Encoder (V AE),

Reference 48

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This paper cites Recent Advances in Adversarial Training for Adversarial Robustness,.

A Multi-stage Constrained Optimization Framework for Data-driven Problems Recent Advances in Adversarial Training for Adversarial Robustness,

Reference 49

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This paper cites Inverse Optimization: Theory and Applications,.

A Multi-stage Constrained Optimization Framework for Data-driven Problems Inverse Optimization: Theory and Applications,

Reference 50

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This paper cites Intriguing properties of neural networks,.

A Multi-stage Constrained Optimization Framework for Data-driven Problems Intriguing properties of neural networks,

Reference 51

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This paper cites Solving Inverse Problems by Joint Posterior Maximization with Autoencoding Prior,.

A Multi-stage Constrained Optimization Framework for Data-driven Problems Solving Inverse Problems by Joint Posterior Maximization with Autoencoding Prior,

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This paper cites Uniform Transformation: Refining Latent Representation in Variational Autoencoders,.

A Multi-stage Constrained Optimization Framework for Data-driven Problems Uniform Transformation: Refining Latent Representation in Variational Autoencoders,

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This paper cites To Compress or Not to Compress— Self-Supervised Learning and Information Theory: A Review,.

A Multi-stage Constrained Optimization Framework for Data-driven Problems To Compress or Not to Compress— Self-Supervised Learning and Information Theory: A Review,

Reference 54

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This paper cites Disentangled Representation Learning,.

A Multi-stage Constrained Optimization Framework for Data-driven Problems Disentangled Representation Learning,

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This paper cites Tackling Over- pruning in Variational Autoencoders,.

A Multi-stage Constrained Optimization Framework for Data-driven Problems Tackling Over- pruning in Variational Autoencoders,

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Observation 520453df-55fc-40b6-a2bd-f32ea5d943e2 · outbound

This paper cites Sparsity in Variational Autoencoders,.

A Multi-stage Constrained Optimization Framework for Data-driven Problems Sparsity in Variational Autoencoders,

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This paper cites The Probability Integral Transformation When Parameters are Estimated from the Sample,.

A Multi-stage Constrained Optimization Framework for Data-driven Problems The Probability Integral Transformation When Parameters are Estimated from the Sample,

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Observation ef3cbfbf-e6c5-4ce7-aa90-541325f84346 · outbound

This paper cites ZINC20— A Free Ultralarge-Scale Chemical Database for Ligand Discovery,.

A Multi-stage Constrained Optimization Framework for Data-driven Problems ZINC20— A Free Ultralarge-Scale Chemical Database for Ligand Discovery,

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This paper cites Weininger, “SMILES, a chemical language and information system.

A Multi-stage Constrained Optimization Framework for Data-driven Problems Weininger, “SMILES, a chemical language and information system

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A Multi-stage Constrained Optimization Framework for Data-driven Problems Unresolved cited work

Reference 61

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Observation 089841b9-a6f6-48d9-aff4-ab41570b771f · outbound

This paper cites Attention Is All You Need.

A Multi-stage Constrained Optimization Framework for Data-driven Problems Attention Is All You Need

Reference 62

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Observation e8d4e384-42a7-4e6f-8424-ec43434896e2 · outbound

This paper cites Hierarchical Graph-to-Graph Translation for Molecules,.

A Multi-stage Constrained Optimization Framework for Data-driven Problems Hierarchical Graph-to-Graph Translation for Molecules,

Reference 63

Resolution: unresolved; no resolver link, observed 2026-07-30T21:18:19.799145Z

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Observation eda41885-94ec-4406-8cea-8102c409d76b · outbound

This paper cites Optimization of Molecules via Deep Reinforcement Learning,.

A Multi-stage Constrained Optimization Framework for Data-driven Problems Optimization of Molecules via Deep Reinforcement Learning,

Reference 64

Resolution: unresolved; no resolver link, observed 2026-07-30T21:18:19.802151Z

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