Neural Operators Can Play Dynamic Stackelberg Games | Paper Citation Record

Observation be97c10f-ddb5-413d-83f6-a29f9406fb5a · outbound

This paper cites Designing universal causal deep learning models: The geometric (hyper) transformer.

Neural Operators Can Play Dynamic Stackelberg Games Designing universal causal deep learning models: The geometric (hyper) transformer

Reference 1

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Observation d8c53ddb-b2ff-4fb5-8455-4b39d2ad48f4 · outbound

This paper cites Optimal brokerage contracts in almgren--chriss model with multiple clients.

Neural Operators Can Play Dynamic Stackelberg Games Optimal brokerage contracts in almgren--chriss model with multiple clients

Reference 2

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Observation 2cf3ffd1-33ec-41a8-91a9-51a2ff88e4c0 · outbound

This paper cites Refinement of strong stackelberg equilibria in security games.

Neural Operators Can Play Dynamic Stackelberg Games Refinement of strong stackelberg equilibria in security games

Reference 3

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Observation ed4879ea-9b4f-498a-8b87-1f41d4624cd5 · outbound

This paper cites Neural operator: Graph kernel network for partial differential equations.

Neural Operators Can Play Dynamic Stackelberg Games Neural operator: Graph kernel network for partial differential equations

Reference 4

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Observation 29e9818a-5d1b-4c74-8bdb-5435b7a87e27 · outbound

This paper cites Optimal incentives to mitigate epidemics: a stackelberg mean field game approach.

Neural Operators Can Play Dynamic Stackelberg Games Optimal incentives to mitigate epidemics: a stackelberg mean field game approach

Reference 5

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This paper cites Ba\ nos, Sindre Duedahl, Thilo Meyer-Brandis, and Frank Proske.

Neural Operators Can Play Dynamic Stackelberg Games Ba\ nos, Sindre Duedahl, Thilo Meyer-Brandis, and Frank Proske

Reference 6

Resolution: verified exact; doi, observed 2026-08-12T20:33:45.555781Z

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Observation a20a26f4-4541-4078-b5cd-864b77fd2c2d · outbound

This paper cites Neural machine translation by jointly learning to align and translate.

Neural Operators Can Play Dynamic Stackelberg Games Neural machine translation by jointly learning to align and translate

Reference 7

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Observation 6c935d6f-9f75-47f2-9444-2a4319a06449 · outbound

This paper cites Bartlett, Nick Harvey, Christopher Liaw, and Abbas Mehrabian.

Neural Operators Can Play Dynamic Stackelberg Games Bartlett, Nick Harvey, Christopher Liaw, and Abbas Mehrabian

Reference 8

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Observation eea5c86f-9c16-42cf-baaf-1bbeeb270963 · outbound

This paper cites Representation equivalent neural operators: a framework for alias-free operator learning.

Neural Operators Can Play Dynamic Stackelberg Games Representation equivalent neural operators: a framework for alias-free operator learning

Reference 9

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Observation fedc5c7b-7c22-4f9d-8bc5-317654d857d7 · outbound

This paper cites Out-of-distributional risk bounds for neural operators with applications to the Helmholtz equation.

Neural Operators Can Play Dynamic Stackelberg Games Out-of-distributional risk bounds for neural operators with applications to the Helmholtz equation

Reference 10

Resolution: verified exact; local_arxiv, observed 2026-08-12T20:33:45.836404Z

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Observation 75a3fbd3-d941-46f4-ab1f-9cd58f428d2a · outbound

This paper cites Prevention efforts, insurance demand and price incentives under coherent risk measures.

Neural Operators Can Play Dynamic Stackelberg Games Prevention efforts, insurance demand and price incentives under coherent risk measures

Reference 11

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Observation 17e98c7d-18cd-48db-b0ec-45064ddaf443 · outbound

This paper cites The maximum principle for global solutions of stochastic stackelberg differential games.

Neural Operators Can Play Dynamic Stackelberg Games The maximum principle for global solutions of stochastic stackelberg differential games

Reference 12

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Observation 40d0b816-e886-4202-b8df-cfaef0c99bbb · outbound

This paper cites Geometric nonlinear functional analysis.

Neural Operators Can Play Dynamic Stackelberg Games Geometric nonlinear functional analysis

Reference 13

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Observation 8b16c59e-de0a-4da8-8c03-db97f723535f · outbound

This paper cites Linear L ipschitz and C^1 extension operators through random projection.

Neural Operators Can Play Dynamic Stackelberg Games Linear L ipschitz and C^1 extension operators through random projection

Reference 14

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Observation 94edde6a-e10a-4df0-aa83-5688a42c754e · outbound

This paper cites Artificial neural systems for interpretation and inversion of seismic data.

Neural Operators Can Play Dynamic Stackelberg Games Artificial neural systems for interpretation and inversion of seismic data

Reference 15

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Observation e854f568-2a54-4960-b318-4f89e7602284 · outbound

This paper cites Continuum attention for neural operators.

Neural Operators Can Play Dynamic Stackelberg Games Continuum attention for neural operators

Reference 16

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Observation c52820a6-b064-4685-950f-0d6cf987c4dc · outbound

This paper cites Stackelberg differential game for insurance under model ambiguity.

Neural Operators Can Play Dynamic Stackelberg Games Stackelberg differential game for insurance under model ambiguity

Reference 17

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Observation e7f453b5-44e5-4665-8e43-a87c106ff109 · outbound

This paper cites Choose a transformer: Fourier or galerkin.

Neural Operators Can Play Dynamic Stackelberg Games Choose a transformer: Fourier or galerkin

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-12T20:33:45.234638Z

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Observation 7044ddce-33bb-4e05-9411-8f87ab47ae94 · outbound

This paper cites Metric entropy of convex hulls in H ilbert spaces.

Neural Operators Can Play Dynamic Stackelberg Games Metric entropy of convex hulls in H ilbert spaces

Reference 19

Resolution: verified exact; doi, observed 2026-08-12T20:33:45.542062Z

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Observation 2634b64c-c744-4faf-b3d9-3d318bcf7436 · outbound

This paper cites Mean field game model for an advertising competition in a duopoly.

Neural Operators Can Play Dynamic Stackelberg Games Mean field game model for an advertising competition in a duopoly

Reference 20

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Observation aaf37c6c-1ce3-4e7c-aae9-eb2a29a540cc · outbound

This paper cites The kolmogorov infinite dimensional equation in a hilbert space via deep learning methods.

Neural Operators Can Play Dynamic Stackelberg Games The kolmogorov infinite dimensional equation in a hilbert space via deep learning methods

Reference 21

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Observation 8ebb6f9b-b04a-48bc-8691-69331e6fc88c · outbound

This paper cites Efficient approximation of high-dimensional functions with neural networks.

Neural Operators Can Play Dynamic Stackelberg Games Efficient approximation of high-dimensional functions with neural networks

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T20:33:46.258291Z

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Observation 41b9868e-a513-4df0-a2d9-e70e86cea0e6 · outbound

This paper cites Cohen and Robert J.

Neural Operators Can Play Dynamic Stackelberg Games Cohen and Robert J

Reference 23

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Observation c029b6d4-6ec7-4ce3-bd75-e805ee713895 · outbound

This paper cites Computing the optimal strategy to commit to.

Neural Operators Can Play Dynamic Stackelberg Games Computing the optimal strategy to commit to

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-12T20:33:45.252878Z

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Observation dd7b533b-09ec-4f3f-a2ca-8e1a91b866e8 · outbound

This paper cites An introduction to -convergence , volume 8 of Progress in Nonlinear Differential Equations and their Applications.

Neural Operators Can Play Dynamic Stackelberg Games An introduction to -convergence , volume 8 of Progress in Nonlinear Differential Equations and their Applications

Reference 25

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Observation 1713146b-a5b9-42c3-9a12-96207b82688b · outbound

This paper cites A Machine Learning Method for Stackelberg Mean Field Games.

Neural Operators Can Play Dynamic Stackelberg Games A Machine Learning Method for Stackelberg Mean Field Games

Reference 26

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Observation 6851e8d1-1e2a-46e8-beb0-f33792c9c171 · outbound

This paper cites Mixtures of Neural Operators Reduce Active Complexity in Operator Learning.

Neural Operators Can Play Dynamic Stackelberg Games Mixtures of Neural Operators Reduce Active Complexity in Operator Learning

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-12T20:33:45.261913Z

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Observation f94c4ace-942f-4de5-8e2c-f69b866c7c28 · outbound

This paper cites Deep learning architectures for nonlinear operator functions and nonlinear inverse problems.

Neural Operators Can Play Dynamic Stackelberg Games Deep learning architectures for nonlinear operator functions and nonlinear inverse problems

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T20:33:46.245030Z

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Observation 474d47b4-4865-4073-b09d-8a227b9a5db2 · outbound

This paper cites Error estimates for physics-informed neural networks approximating the navier--stokes equations.

Neural Operators Can Play Dynamic Stackelberg Games Error estimates for physics-informed neural networks approximating the navier--stokes equations

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T20:33:46.236711Z

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Observation 0c56c0d9-8dd2-4950-a405-3eaa869908e5 · outbound

This paper cites Cloud pricing: The spot market strikes back.

Neural Operators Can Play Dynamic Stackelberg Games Cloud pricing: The spot market strikes back

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T20:33:46.228049Z

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Observation 2521e629-56be-4b9f-aa3b-3b30185bfe53 · outbound

This paper cites Adaptive subgradient methods for online learning and stochastic optimization.

Neural Operators Can Play Dynamic Stackelberg Games Adaptive subgradient methods for online learning and stochastic optimization

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T20:33:46.218972Z

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Observation bf3195cf-1777-45e5-8998-58af52688fa9 · outbound

This paper cites Pinsker, and Viacheslav V.

Neural Operators Can Play Dynamic Stackelberg Games Pinsker, and Viacheslav V

Reference 32

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Observation 670bdc48-8dcb-49cd-beba-458c18439b27 · outbound

This paper cites A tale of a principal and many, many agents.

Neural Operators Can Play Dynamic Stackelberg Games A tale of a principal and many, many agents

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T20:33:46.211062Z

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Observation 0953ecc5-60c0-44b8-8ea4-dda70277ed7d · outbound

This paper cites an unresolved cited work.

Neural Operators Can Play Dynamic Stackelberg Games Unresolved cited work

Reference 34

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Observation 7fad11bb-400c-4f67-97c2-761bb3223513 · outbound

This paper cites Spectral neural operators.

Neural Operators Can Play Dynamic Stackelberg Games Spectral neural operators

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T20:33:46.203472Z

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Observation 69f6ce5f-db94-462c-a2ef-bac000f838ce · outbound

This paper cites Geometric measure theory.

Neural Operators Can Play Dynamic Stackelberg Games Geometric measure theory

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T20:33:46.195079Z

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Observation 31406db7-1b22-4fe4-a367-f44d14ca23f8 · outbound

This paper cites Designing Universal Causal Deep Learning Models: The Case of Infinite-Dimensional Dynamical Systems from Stochastic Analysis.

Neural Operators Can Play Dynamic Stackelberg Games Designing Universal Causal Deep Learning Models: The Case of Infinite-Dimensional Dynamical Systems from Stochastic Analysis

Reference 38

Resolution: unresolved; no resolver link, observed 2026-08-12T20:33:45.291803Z

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Observation e099cbc3-750e-4466-ab18-e6ae31aed1f1 · outbound

This paper cites Achieving optimal adversarial accuracy for adversarial deep learning using stackelberg games.

Neural Operators Can Play Dynamic Stackelberg Games Achieving optimal adversarial accuracy for adversarial deep learning using stackelberg games

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T20:33:46.186630Z

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Observation d28fa30e-121a-48d3-8201-be1270901a3b · outbound

This paper cites Oracles & followers: Stackelberg equilibria in deep multi-agent reinforcement learning.

Neural Operators Can Play Dynamic Stackelberg Games Oracles & followers: Stackelberg equilibria in deep multi-agent reinforcement learning

Reference 40

Resolution: unresolved; no resolver link, observed 2026-08-12T20:33:45.296803Z

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Observation 6783eee8-faad-4841-a363-266b5a166793 · outbound

This paper cites Stackelberg equilibria with multiple policyholders.

Neural Operators Can Play Dynamic Stackelberg Games Stackelberg equilibria with multiple policyholders

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T20:33:46.173284Z

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Observation 52381628-9b85-4abc-9ed7-f2e7d6b8e9d2 · outbound

This paper cites A physics-informed variational deeponet for predicting crack path in quasi-brittle materials.

Neural Operators Can Play Dynamic Stackelberg Games A physics-informed variational deeponet for predicting crack path in quasi-brittle materials

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T20:33:46.164826Z

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Observation b9d84f01-0220-4b64-96a0-16acaa7944ac · outbound

This paper cites Calibrated stackelberg games: Learning optimal commitments against calibrated agents.

Neural Operators Can Play Dynamic Stackelberg Games Calibrated stackelberg games: Learning optimal commitments against calibrated agents

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T20:33:46.155881Z

Source-reported events for the cited work

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Observation 636cc9bc-b3cc-4668-8b8a-b45496691642 · outbound

This paper cites Gnot: A general neural operator transformer for operator learning.

Neural Operators Can Play Dynamic Stackelberg Games Gnot: A general neural operator transformer for operator learning

Reference 44

Resolution: unresolved; no resolver link, observed 2026-08-12T20:33:45.306759Z

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Observation 5a8a1c6c-e252-45ba-b84e-74d2d10e868d · outbound

This paper cites Stackelberg games with side information.

Neural Operators Can Play Dynamic Stackelberg Games Stackelberg games with side information

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T20:33:46.142292Z

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Observation b7e7111c-942b-4ffb-b12c-5c1b94f04a87 · outbound

This paper cites Cooperative advertising and pricing in a dynamic stochastic supply chain: Feedback stackelberg strategies.

Neural Operators Can Play Dynamic Stackelberg Games Cooperative advertising and pricing in a dynamic stochastic supply chain: Feedback stackelberg strategies

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T20:33:46.133747Z

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Observation 00b189a2-fdfb-4f93-9b6a-5fca1977d20a · outbound

This paper cites Time-inconsistent contract theory.

Neural Operators Can Play Dynamic Stackelberg Games Time-inconsistent contract theory

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T20:33:46.124989Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation f8d76aaa-6402-4516-855f-fcb5a810ddf8 · outbound

This paper cites Closed-loop equilibria for Stackelberg games: a story about stochastic targets.

Neural Operators Can Play Dynamic Stackelberg Games Closed-loop equilibria for Stackelberg games: a story about stochastic targets

Reference 48

Resolution: unresolved; no resolver link, observed 2026-08-12T20:33:45.318134Z

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Observation 693e043a-92f4-492b-b950-944d25698aa3 · outbound

This paper cites Bridging the Gap Between Approximation and Learning via Optimal Approximation by ReLU MLPs of Maximal Regularity.

Neural Operators Can Play Dynamic Stackelberg Games Bridging the Gap Between Approximation and Learning via Optimal Approximation by ReLU MLPs of Maximal Regularity

Reference 49

Resolution: unresolved; no resolver link, observed 2026-08-12T20:33:45.321190Z

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Observation e8e9e1f6-0654-4a05-b725-bd577daf7d88 · outbound

This paper cites Incentives, lockdown, and testing: from thucydides’ analysis to the covid-19 pandemic.

Neural Operators Can Play Dynamic Stackelberg Games Incentives, lockdown, and testing: from thucydides’ analysis to the covid-19 pandemic

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T20:33:46.116342Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation d5b976c1-2312-4132-812b-377501beb27c · outbound

This paper cites A neural network-based policy iteration algorithm with global H^2 -superlinear convergence for stochastic games on domains.

Neural Operators Can Play Dynamic Stackelberg Games A neural network-based policy iteration algorithm with global H^2 -superlinear convergence for stochastic games on domains

Reference 51

Resolution: verified exact; doi, observed 2026-08-12T20:33:45.517769Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation d9618d84-2de4-4dfe-b352-2374ecb0ecde · outbound

This paper cites Trends and applications in stackelberg security games.

Neural Operators Can Play Dynamic Stackelberg Games Trends and applications in stackelberg security games

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T20:33:46.107913Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 1e4211d1-8492-40a5-abba-1508c1d97b41 · outbound

This paper cites Dynamic contracting in asset management under the investor-partner-manager relationship.

Neural Operators Can Play Dynamic Stackelberg Games Dynamic contracting in asset management under the investor-partner-manager relationship

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T20:33:46.100016Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 46ec52af-fb0a-4bcb-ac79-ad650a132cc5 · outbound

This paper cites Universal Approximation with Deep Narrow Networks.

Neural Operators Can Play Dynamic Stackelberg Games Universal Approximation with Deep Narrow Networks

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T20:33:46.092134Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 9227fd52-6160-4713-af96-7aa4b4ec3c47 · outbound

This paper cites The generalized stackelberg equilibrium of the all-pay auction with complete information.

Neural Operators Can Play Dynamic Stackelberg Games The generalized stackelberg equilibrium of the all-pay auction with complete information

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T20:33:46.083397Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 708d40f3-28b3-42f5-96ab-f91ac5870963 · outbound

This paper cites On universal approximation and error bounds for F ourier neural operators.

Neural Operators Can Play Dynamic Stackelberg Games On universal approximation and error bounds for F ourier neural operators

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T20:33:46.074645Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 6351d4ea-74cc-4910-9dc4-fdfda7dda934 · outbound

This paper cites Neural operator: Learning maps between function spaces with applications to pdes.

Neural Operators Can Play Dynamic Stackelberg Games Neural operator: Learning maps between function spaces with applications to pdes

Reference 57

Resolution: unresolved; no resolver link, observed 2026-08-12T20:33:45.343499Z

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Observation 112a1322-9879-4921-9dff-ec795d779a63 · outbound

This paper cites Universal approximation theorems for differentiable geometric deep learning.

Neural Operators Can Play Dynamic Stackelberg Games Universal approximation theorems for differentiable geometric deep learning

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T20:33:46.060689Z

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No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation d28b9a5b-a006-4e40-8e94-384c96877e07 · outbound

This paper cites An Approximation Theory for Metric Space-Valued Functions With A View Towards Deep Learning.

Neural Operators Can Play Dynamic Stackelberg Games An Approximation Theory for Metric Space-Valued Functions With A View Towards Deep Learning

Reference 60

Resolution: unresolved; no resolver link, observed 2026-08-12T20:33:45.352635Z

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Observation d30845a1-7296-4b38-a333-54d64fc622e5 · outbound

This paper cites Mixture of experts soften the curse of dimensionality in operator learning.

Neural Operators Can Play Dynamic Stackelberg Games Mixture of experts soften the curse of dimensionality in operator learning

Reference 61

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T20:33:46.051493Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation b0bf1cc2-7bb6-4585-abdb-4222c510906f · outbound

This paper cites Optimal Robust Reinsurance with Multiple Insurers.

Neural Operators Can Play Dynamic Stackelberg Games Optimal Robust Reinsurance with Multiple Insurers

Reference 62

Resolution: verified exact; local_arxiv, observed 2026-08-12T20:33:45.595621Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 47e96cce-479e-4326-a57c-7d93511b49b6 · outbound

This paper cites Operator learning with PCA-N et: upper and lower complexity bounds.

Neural Operators Can Play Dynamic Stackelberg Games Operator learning with PCA-N et: upper and lower complexity bounds

Reference 63

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T20:33:46.042626Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 2f3ae747-e47e-4ff0-9f37-d89b01f6324d · outbound

This paper cites The Parametric Complexity of Operator Learning.

Neural Operators Can Play Dynamic Stackelberg Games The Parametric Complexity of Operator Learning

Reference 64

Resolution: unresolved; no resolver link, observed 2026-08-12T20:33:45.363602Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c08bc140-d8fa-4416-b5c6-e7611644b5cf · outbound

This paper cites Error estimates for deeponets: A deep learning framework in infinite dimensions.

Neural Operators Can Play Dynamic Stackelberg Games Error estimates for deeponets: A deep learning framework in infinite dimensions

Reference 65

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T20:33:46.034018Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 4d201e86-6527-4a6b-b113-5cade8086012 · outbound

This paper cites Nonlinear Reconstruction for Operator Learning of PDEs with Discontinuities.

Neural Operators Can Play Dynamic Stackelberg Games Nonlinear Reconstruction for Operator Learning of PDEs with Discontinuities

Reference 66

Resolution: unresolved; no resolver link, observed 2026-08-12T20:33:45.369483Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 559b59cb-9ca9-44a6-a68d-f2a9224c36dd · outbound

This paper cites Hyperdeep ON et: learning operator with complex target function space using the limited resources via hypernetwork.

Neural Operators Can Play Dynamic Stackelberg Games Hyperdeep ON et: learning operator with complex target function space using the limited resources via hypernetwork

Reference 67

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T20:33:46.025275Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 46a6a090-21a9-4666-8032-4f7c7dbad202 · outbound

This paper cites A cooperative stackelberg game based energy management considering price discrimination and risk assessment.

Neural Operators Can Play Dynamic Stackelberg Games A cooperative stackelberg game based energy management considering price discrimination and risk assessment

Reference 68

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T20:33:46.016370Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 2aa9e203-b9df-4c26-a0f9-85fd7ce4e893 · outbound

This paper cites Fourier Neural Operator for Parametric Partial Differential Equations.

Neural Operators Can Play Dynamic Stackelberg Games Fourier Neural Operator for Parametric Partial Differential Equations

Reference 69

Resolution: unresolved; no resolver link, observed 2026-08-12T20:33:45.376976Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4320609b-5111-4c62-a88e-72db24eedf8b · outbound

This paper cites Fourier neural operator with learned deformations for pdes on general geometries.

Neural Operators Can Play Dynamic Stackelberg Games Fourier neural operator with learned deformations for pdes on general geometries

Reference 70

Resolution: unresolved; no resolver link, observed 2026-08-12T20:33:45.379510Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e8924431-ac54-492a-9785-2ec4385656d4 · outbound

This paper cites an unresolved cited work.

Neural Operators Can Play Dynamic Stackelberg Games Unresolved cited work

Reference 71

Resolution: verified exact; doi, observed 2026-08-12T20:33:45.508710Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation e21c65a5-e74d-47e8-b0dd-10f90b35a5aa · outbound

This paper cites Lorentz, Manfred v.

Neural Operators Can Play Dynamic Stackelberg Games Lorentz, Manfred v

Reference 72

Resolution: unresolved; no resolver link, observed 2026-08-12T20:33:45.384549Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1993f760-711c-4be7-94ad-3bae2dfb9bf1 · outbound

This paper cites DeepONet: Learning nonlinear operators for identifying differential equations based on the universal approximation theorem of operators.

Neural Operators Can Play Dynamic Stackelberg Games DeepONet: Learning nonlinear operators for identifying differential equations based on the universal approximation theorem of operators

Reference 73

Resolution: unresolved; no resolver link, observed 2026-08-12T20:33:45.387533Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation aa83ebd8-9a2d-4de5-8051-4b9f35e005dd · outbound

This paper cites Learning nonlinear operators via deeponet based on the universal approximation theorem of operators.

Neural Operators Can Play Dynamic Stackelberg Games Learning nonlinear operators via deeponet based on the universal approximation theorem of operators

Reference 74

Resolution: unresolved; no resolver link, observed 2026-08-12T20:33:45.390531Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c6a2dfef-43dc-4b21-b2ca-03e69771ab67 · outbound

This paper cites Exponential convergence of deep operator networks for elliptic partial differential equations.

Neural Operators Can Play Dynamic Stackelberg Games Exponential convergence of deep operator networks for elliptic partial differential equations

Reference 75

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T20:33:45.998460Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 7cd3b058-a274-4f01-ab7a-b30f1deb5fdd · outbound

This paper cites Ondelettes et op\' e rateurs.

Neural Operators Can Play Dynamic Stackelberg Games Ondelettes et op\' e rateurs

Reference 76

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T20:33:45.990109Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation b32d62ef-5493-4e9f-9d5e-24de65272f67 · outbound

This paper cites Approximations by L ipschitz functions generated by extensions.

Neural Operators Can Play Dynamic Stackelberg Games Approximations by L ipschitz functions generated by extensions

Reference 77

Resolution: verified exact; doi, observed 2026-08-12T20:33:45.494177Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 652deee3-619b-48bd-a969-741e9ca91de2 · outbound

This paper cites Neural inverse operators for solving pde inverse problems.

Neural Operators Can Play Dynamic Stackelberg Games Neural inverse operators for solving pde inverse problems

Reference 78

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T20:33:45.982548Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation f4267431-7693-46ba-8625-1cf7bcc3e285 · outbound

This paper cites an unresolved cited work.

Neural Operators Can Play Dynamic Stackelberg Games Unresolved cited work

Reference 79

Resolution: unresolved; raw_fallback, observed 2026-08-12T20:33:45.974806Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation f7725cef-9bbe-4861-bfeb-7a8c806f452e · outbound

This paper cites The M alliavin calculus and related topics.

Neural Operators Can Play Dynamic Stackelberg Games The M alliavin calculus and related topics

Reference 80

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T20:33:45.967130Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 33564b5f-3f60-4817-9508-1087c36e380e · outbound

This paper cites Fully coupled forward-backward stochastic differential equations and applications to optimal control.

Neural Operators Can Play Dynamic Stackelberg Games Fully coupled forward-backward stochastic differential equations and applications to optimal control

Reference 81

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T20:33:45.958676Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 8cf816ca-183b-4cef-9b82-11eaff3bc608 · outbound

This paper cites Lipschitz widths.

Neural Operators Can Play Dynamic Stackelberg Games Lipschitz widths

Reference 82

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T20:33:45.948780Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 577d5f9d-0333-4b14-9a16-93a349efff2d · outbound

This paper cites Convolutional neural operators for robust and accurate learning of pdes.

Neural Operators Can Play Dynamic Stackelberg Games Convolutional neural operators for robust and accurate learning of pdes

Reference 83

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T20:33:45.939313Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation e53d57db-1c81-40e9-8874-5117cd3815af · outbound

This paper cites Rectified deep neural networks overcome the curse of dimensionality for nonsmooth value functions in zero-sum games of nonlinear stiff systems.

Neural Operators Can Play Dynamic Stackelberg Games Rectified deep neural networks overcome the curse of dimensionality for nonsmooth value functions in zero-sum games of nonlinear stiff systems

Reference 84

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T20:33:45.930369Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation b1230b18-d13a-4ce2-9b42-4d36df511a20 · outbound

This paper cites Robinson.

Neural Operators Can Play Dynamic Stackelberg Games Robinson

Reference 85

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T20:33:45.920801Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation eb16fd6e-e1f8-46fa-8749-29c8ddf529f5 · outbound

This paper cites Optimal approximation rate of R e LU networks in terms of width and depth.

Neural Operators Can Play Dynamic Stackelberg Games Optimal approximation rate of R e LU networks in terms of width and depth

Reference 86

Resolution: unresolved; no resolver link, observed 2026-08-12T20:33:45.424074Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e8b92187-9792-4a06-9f91-d9d646d4b9a7 · outbound

This paper cites Deep learning algorithms for hedging with frictions.

Neural Operators Can Play Dynamic Stackelberg Games Deep learning algorithms for hedging with frictions

Reference 87

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T20:33:45.910270Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 1131822c-5aa0-4d21-86dd-bbf10bcb1101 · outbound

This paper cites an unresolved cited work.

Neural Operators Can Play Dynamic Stackelberg Games Unresolved cited work

Reference 88

Resolution: unresolved; no resolver link, observed 2026-08-12T20:33:45.429836Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7de58cff-6507-4cc7-83e0-819be6531755 · outbound

This paper cites van der Vaart and Jon A.

Neural Operators Can Play Dynamic Stackelberg Games van der Vaart and Jon A

Reference 89

Resolution: unresolved; no resolver link, observed 2026-08-12T20:33:45.432557Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 16195d72-b2cb-4535-865b-f1d16a17c75e · outbound

This paper cites The infinite-dimensional topology of function spaces, volume 64 of North-Holland Mathematical Library.

Neural Operators Can Play Dynamic Stackelberg Games The infinite-dimensional topology of function spaces, volume 64 of North-Holland Mathematical Library

Reference 90

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T20:33:45.901566Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation d5b89e3f-d9d8-4f0a-8060-0e06b14323e6 · outbound

This paper cites Attention is all you need.

Neural Operators Can Play Dynamic Stackelberg Games Attention is all you need

Reference 91

Resolution: unresolved; no resolver link, observed 2026-08-12T20:33:45.438245Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c70c80c1-4b01-4996-99fe-44d68d01bddf · outbound

This paper cites Lipschitz algebras.

Neural Operators Can Play Dynamic Stackelberg Games Lipschitz algebras

Reference 92

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T20:33:45.887867Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation ee5ff2c2-97b3-44a0-bdcb-e28dab94b4c3 · outbound

This paper cites A leader-follower stochastic linear quadratic differential game.

Neural Operators Can Play Dynamic Stackelberg Games A leader-follower stochastic linear quadratic differential game

Reference 93

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T20:33:45.879356Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation f51c9910-4b5e-446a-b23d-ddb51da96a0e · outbound

This paper cites The optimization of supply chain financing for bank green credit using stackelberg game theory in digital economy under internet of things.

Neural Operators Can Play Dynamic Stackelberg Games The optimization of supply chain financing for bank green credit using stackelberg game theory in digital economy under internet of things

Reference 94

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T20:33:45.869926Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 72511f5b-b47c-4e7e-ab4b-12bf849f5311 · outbound

This paper cites Improved nystr \"o m low-rank approximation and error analysis.

Neural Operators Can Play Dynamic Stackelberg Games Improved nystr \"o m low-rank approximation and error analysis

Reference 95

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T20:33:45.861797Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation e224b1cf-70e6-4aa8-8ea3-38a22a2de824 · outbound

This paper cites Deep network approximation: Achieving arbitrary accuracy with fixed number of neurons.

Neural Operators Can Play Dynamic Stackelberg Games Deep network approximation: Achieving arbitrary accuracy with fixed number of neurons

Reference 96

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T20:33:45.853965Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 91ee0451-fb29-48ee-89d9-2bfcf899367e · outbound

This paper cites A stackelberg game approach to proactive caching in large-scale mobile edge networks.

Neural Operators Can Play Dynamic Stackelberg Games A stackelberg game approach to proactive caching in large-scale mobile edge networks

Reference 97

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T20:33:45.845332Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

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