Formal Verification of Markov Processes with Learned Parameters | Paper Citation Record

Observation 8201d8fd-fedd-4640-bac3-d10fd0f05dca · outbound

This paper cites Introduction to the numerical solution of markov chains.

Formal Verification of Markov Processes with Learned Parameters Introduction to the numerical solution of markov chains

Reference 1

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This paper cites Principles of model checking.

Formal Verification of Markov Processes with Learned Parameters Principles of model checking

Reference 2

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This paper cites System reliability theory: models, statistical methods, and applications, volume 396.

Formal Verification of Markov Processes with Learned Parameters System reliability theory: models, statistical methods, and applications, volume 396

Reference 3

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This paper cites Markov models in medical decision making: a practical guide.

Formal Verification of Markov Processes with Learned Parameters Markov models in medical decision making: a practical guide

Reference 4

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This paper cites Microsimulation modeling in food policy: A scoping review of methodological aspects.

Formal Verification of Markov Processes with Learned Parameters Microsimulation modeling in food policy: A scoping review of methodological aspects

Reference 5

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This paper cites Microsimulation modeling for health decision sciences using r: a tutorial.

Formal Verification of Markov Processes with Learned Parameters Microsimulation modeling for health decision sciences using r: a tutorial

Reference 6

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This paper cites A logic for reasoning about time and reliability.

Formal Verification of Markov Processes with Learned Parameters A logic for reasoning about time and reliability

Reference 7

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This paper cites Prism: Probabilistic symbolic model checker.

Formal Verification of Markov Processes with Learned Parameters Prism: Probabilistic symbolic model checker

Reference 8

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This paper cites A markov reward model checker.

Formal Verification of Markov Processes with Learned Parameters A markov reward model checker

Reference 9

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This paper cites A markov chain model checker.

Formal Verification of Markov Processes with Learned Parameters A markov chain model checker

Reference 10

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Observation 6a8f5ce7-3a4f-4d79-b3e0-ddfca19a2139 · outbound

This paper cites On statistical model checking of stochastic systems.

Formal Verification of Markov Processes with Learned Parameters On statistical model checking of stochastic systems

Reference 11

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This paper cites Ymer: A statistical model checker.

Formal Verification of Markov Processes with Learned Parameters Ymer: A statistical model checker

Reference 12

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Observation a1c29f43-1036-4135-bb9d-1c599e56c8bd · outbound

This paper cites Approximate verification of probabilistic systems.

Formal Verification of Markov Processes with Learned Parameters Approximate verification of probabilistic systems

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:02:44.254368Z

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Observation f5bf2455-35c4-4491-b870-71da00db17df · outbound

This paper cites Model-checking markov chains in the presence of uncertainties.

Formal Verification of Markov Processes with Learned Parameters Model-checking markov chains in the presence of uncertainties

Reference 14

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Observation cb2cf192-2a54-4406-ab90-7d1e38a8f06a · outbound

This paper cites Parameter synthesis for parametric interval markov chains.

Formal Verification of Markov Processes with Learned Parameters Parameter synthesis for parametric interval markov chains

Reference 15

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This paper cites Parameter synthesis algorithms for parametric interval markov chains.

Formal Verification of Markov Processes with Learned Parameters Parameter synthesis algorithms for parametric interval markov chains

Reference 16

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This paper cites Model repair for markov decision processes.

Formal Verification of Markov Processes with Learned Parameters Model repair for markov decision processes

Reference 17

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This paper cites Parameter synthesis in Markov models.

Formal Verification of Markov Processes with Learned Parameters Parameter synthesis in Markov models

Reference 18

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Observation 3b4c08b7-32b3-4ef8-a0b8-4cdb22766ab7 · outbound

This paper cites Parameter synthesis for markov models: covering the parameter space.

Formal Verification of Markov Processes with Learned Parameters Parameter synthesis for markov models: covering the parameter space

Reference 19

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Observation 0a6b5211-a0cc-4a20-bdaa-f317ac208c14 · outbound

This paper cites Efficient sensitivity analysis for parametric robust markov chains.

Formal Verification of Markov Processes with Learned Parameters Efficient sensitivity analysis for parametric robust markov chains

Reference 20

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Observation dcde74a9-c044-4899-8a49-2d7674de2e5a · outbound

This paper cites On markov chains with uncertain data.

Formal Verification of Markov Processes with Learned Parameters On markov chains with uncertain data

Reference 21

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Observation 8ad99ea3-ac3c-4539-a3b5-8906ac9226f8 · outbound

This paper cites Sensitivity analysis for finite Markov chains in discrete time.

Formal Verification of Markov Processes with Learned Parameters Sensitivity analysis for finite Markov chains in discrete time

Reference 22

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This paper cites Simulation-based optimization of markov reward processes.

Formal Verification of Markov Processes with Learned Parameters Simulation-based optimization of markov reward processes

Reference 23

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Observation 73ec67b4-e374-4b75-b8ec-09d5e7b3c896 · outbound

This paper cites Approximate gradient methods in policy-space optimiza- tion of markov reward processes.

Formal Verification of Markov Processes with Learned Parameters Approximate gradient methods in policy-space optimiza- tion of markov reward processes

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:02:44.169292Z

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Observation 7d49588e-d056-4c7b-b79d-4c06a853e55b · outbound

This paper cites Robust solutions to markov decision problems with uncertain transition matrices.

Formal Verification of Markov Processes with Learned Parameters Robust solutions to markov decision problems with uncertain transition matrices

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:02:44.159780Z

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This paper cites Robust dynamic programming.

Formal Verification of Markov Processes with Learned Parameters Robust dynamic programming

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:02:44.149701Z

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Observation 5bfda0ef-c437-4a1e-9a0a-d696f65c5bc9 · outbound

This paper cites Robust markov decision processes: Beyond rectangu- larity.

Formal Verification of Markov Processes with Learned Parameters Robust markov decision processes: Beyond rectangu- larity

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:02:44.140490Z

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Observation 5a3dc358-e068-4091-9366-87a912b59c68 · outbound

This paper cites On the convex formulations of robust markov decision processes.

Formal Verification of Markov Processes with Learned Parameters On the convex formulations of robust markov decision processes

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:02:44.132003Z

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Observation 25f1ca03-74f2-4d1d-94fd-a29926979822 · outbound

This paper cites Data un- certainty in markov chains: Application to cost-effectiveness analyses of medical innovations.

Formal Verification of Markov Processes with Learned Parameters Data un- certainty in markov chains: Application to cost-effectiveness analyses of medical innovations

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:02:44.123576Z

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Observation 2e31de81-aa64-43e8-9f07-cd6df2fa7167 · outbound

This paper cites Exact sensitivity analysis of Markov reward processes via algebraic geometry.

Formal Verification of Markov Processes with Learned Parameters Exact sensitivity analysis of Markov reward processes via algebraic geometry

Reference 30

Resolution: verified exact; local_arxiv, observed 2026-08-10T14:02:43.495632Z

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This paper cites ACAS Xu: Integrated collision avoidance and detect and avoid capability for uas.

Formal Verification of Markov Processes with Learned Parameters ACAS Xu: Integrated collision avoidance and detect and avoid capability for uas

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:02:44.115225Z

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Observation 185c0eca-2040-47fb-a0ea-0168ef22ab69 · outbound

This paper cites Reluplex: An efficient smt solver for verifying deep neural networks.

Formal Verification of Markov Processes with Learned Parameters Reluplex: An efficient smt solver for verifying deep neural networks

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:02:44.107313Z

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Observation 64281409-da2e-4c0d-8299-3807029dda0f · outbound

This paper cites Evaluating Robustness of Neural Networks with Mixed Integer Programming.

Formal Verification of Markov Processes with Learned Parameters Evaluating Robustness of Neural Networks with Mixed Integer Programming

Reference 33

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Observation f969c5b7-1bb6-41b5-bac3-31217ba5192b · outbound

This paper cites Maximum resilience of artificial neural networks.

Formal Verification of Markov Processes with Learned Parameters Maximum resilience of artificial neural networks

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:02:44.099384Z

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Observation 5b081c8e-316d-4319-a5b5-c3fb02744206 · outbound

This paper cites Strong mixed-integer programming formulations for trained neural networks.

Formal Verification of Markov Processes with Learned Parameters Strong mixed-integer programming formulations for trained neural networks

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:02:44.090202Z

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Observation 3867b272-bae4-432f-8075-7f802202ec3d · outbound

This paper cites The convex relaxation barrier, revisited: Tightened single-neuron relaxations for neural network verification.

Formal Verification of Markov Processes with Learned Parameters The convex relaxation barrier, revisited: Tightened single-neuron relaxations for neural network verification

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:02:44.080728Z

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Observation 1fc4379e-4d48-45ca-8aa8-9209b84cef86 · outbound

This paper cites Between steps: Intermediate relaxations between big-m and convex hull formulations.

Formal Verification of Markov Processes with Learned Parameters Between steps: Intermediate relaxations between big-m and convex hull formulations

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:02:44.070788Z

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Observation 7199af1f-26c6-445c-a125-652ba8e8e48f · outbound

This paper cites Neural Network Verification as Piecewise Linear Optimization: Formulations for the Composition of Staircase Functions.

Formal Verification of Markov Processes with Learned Parameters Neural Network Verification as Piecewise Linear Optimization: Formulations for the Composition of Staircase Functions

Reference 38

Resolution: verified exact; local_arxiv, observed 2026-08-10T14:02:43.472618Z

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Observation 6ff79e19-20ec-4171-96ee-3a87f1943414 · outbound

This paper cites Beta-CROWN: Efficient bound propagation with per-neuron split constraints for complete and incomplete neural network verification.

Formal Verification of Markov Processes with Learned Parameters Beta-CROWN: Efficient bound propagation with per-neuron split constraints for complete and incomplete neural network verification

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:02:44.061440Z

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Observation 54da0e60-cb43-4674-a29b-fee613dcb515 · outbound

This paper cites A branch and bound framework for stronger adversarial attacks of ReLU networks.

Formal Verification of Markov Processes with Learned Parameters A branch and bound framework for stronger adversarial attacks of ReLU networks

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:02:44.052138Z

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Observation 100cc60c-3269-43c3-909c-bb66362915a1 · outbound

This paper cites General cutting planes for bound-propagation-based neural network verification.

Formal Verification of Markov Processes with Learned Parameters General cutting planes for bound-propagation-based neural network verification

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:02:44.042817Z

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Observation 6d2ec248-61ec-464f-ad08-44fa6bcc2aea · outbound

This paper cites Zico Kolter, Krishnamurthy Dvijotham, and Huan Zhang.

Formal Verification of Markov Processes with Learned Parameters Zico Kolter, Krishnamurthy Dvijotham, and Huan Zhang

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:02:44.033073Z

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Observation 187206bd-aed5-4797-93f3-4bca923bf275 · outbound

This paper cites Cost-effectiveness of a us national sugar-sweetened beverage tax with a multistakeholder approach: who pays and who benefits.

Formal Verification of Markov Processes with Learned Parameters Cost-effectiveness of a us national sugar-sweetened beverage tax with a multistakeholder approach: who pays and who benefits

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:02:44.023540Z

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Observation 83477604-8c8d-447f-b497-1b4b1e497808 · outbound

This paper cites Health impact and cost- effectiveness of volume, tiered, and absolute sugar content sugar-sweetened beverage tax policies in the united states: a microsimulation study.

Formal Verification of Markov Processes with Learned Parameters Health impact and cost- effectiveness of volume, tiered, and absolute sugar content sugar-sweetened beverage tax policies in the united states: a microsimulation study

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:02:44.014285Z

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Observation f7941c20-1799-4023-bd0d-3bc0e8a46fe0 · outbound

This paper cites Cost-effectiveness of population-based, community, workplace and individual policies for diabetes prevention in the uk.

Formal Verification of Markov Processes with Learned Parameters Cost-effectiveness of population-based, community, workplace and individual policies for diabetes prevention in the uk

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:02:44.005708Z

Source-reported events for the cited work

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Observation 8ab37077-e8e4-4005-b4c0-bb5d5f651bc3 · outbound

This paper cites Handbook of global optimization, volume 2.

Formal Verification of Markov Processes with Learned Parameters Handbook of global optimization, volume 2

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:02:43.996358Z

Source-reported events for the cited work

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Observation cbcf7d5f-9d75-4168-90b1-311d7b5434bb · outbound

This paper cites Computability of global solutions to factorable nonconvex programs: Part i—convex underestimating problems.

Formal Verification of Markov Processes with Learned Parameters Computability of global solutions to factorable nonconvex programs: Part i—convex underestimating problems

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:02:43.987945Z

Source-reported events for the cited work

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Observation cd944047-bdf3-465c-95b1-d43383d93da4 · outbound

This paper cites Gurobi Optimizer Reference Manual, 2024.

Formal Verification of Markov Processes with Learned Parameters Gurobi Optimizer Reference Manual, 2024

Reference 48

Resolution: unresolved; no resolver link, observed 2026-08-10T14:02:43.311661Z

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Observation c0d45515-ee86-4dc3-9abc-1cced9b6a23c · outbound

This paper cites New socp relaxation and branching rule for bipartite bilinear programs.

Formal Verification of Markov Processes with Learned Parameters New socp relaxation and branching rule for bipartite bilinear programs

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:02:43.974604Z

Source-reported events for the cited work

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Observation ab3e2053-7ad4-4204-a6a4-2d392c251db1 · outbound

This paper cites Markov decision processes: discrete stochastic dynamic programming.

Formal Verification of Markov Processes with Learned Parameters Markov decision processes: discrete stochastic dynamic programming

Reference 50

Resolution: unresolved; no resolver link, observed 2026-08-10T14:02:43.317810Z

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Observation e852aec6-8b13-4d93-9387-32cae0a05e9f · outbound

This paper cites Mathematical theory of reliability.

Formal Verification of Markov Processes with Learned Parameters Mathematical theory of reliability

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:02:43.960501Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation ae7af8a8-338b-47a4-afe9-e5de7d7b74cc · outbound

This paper cites Determining the acceptance of cadaveric livers using an implicit model of the waiting list.

Formal Verification of Markov Processes with Learned Parameters Determining the acceptance of cadaveric livers using an implicit model of the waiting list

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:02:43.951558Z

Source-reported events for the cited work

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Observation 5dafcb24-9875-41c8-847d-2d8e691028a9 · outbound

This paper cites an unresolved cited work.

Formal Verification of Markov Processes with Learned Parameters Unresolved cited work

Reference 53

Resolution: unresolved; raw_fallback, observed 2026-08-10T14:02:43.941323Z

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Observation 2a0c7c8e-2984-487c-b1a3-3af3238037ee · outbound

This paper cites New techniques for the analysis of linear interval equations.

Formal Verification of Markov Processes with Learned Parameters New techniques for the analysis of linear interval equations

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:02:43.820309Z

Source-reported events for the cited work

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Observation c5dee3b6-d055-48ae-a1ef-24135b9be849 · outbound

This paper cites Nonnegative matrices in the mathematical sciences.

Formal Verification of Markov Processes with Learned Parameters Nonnegative matrices in the mathematical sciences

Reference 55

Resolution: unresolved; no resolver link, observed 2026-08-10T14:02:43.332247Z

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Observation ac413ce3-2e3f-47f1-aca6-9e3d29868703 · outbound

This paper cites Pedregosa, G.

Formal Verification of Markov Processes with Learned Parameters Pedregosa, G

Reference 56

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This paper cites Pytorch: An imperative style, high-performance deep learning library.

Formal Verification of Markov Processes with Learned Parameters Pytorch: An imperative style, high-performance deep learning library

Reference 57

Resolution: unresolved; no resolver link, observed 2026-08-10T14:02:43.337899Z

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Observation 7b62b66a-61f4-4218-b7c6-ab693bd40c39 · outbound

This paper cites Gurobi machine learning, 2024.

Formal Verification of Markov Processes with Learned Parameters Gurobi machine learning, 2024

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:02:43.794755Z

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No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 024c3e63-64e1-4c3d-92c5-5624721359ed · outbound

This paper cites Cost-effectiveness of drone-delivered automated external defibrillators for cardiac arrest.

Formal Verification of Markov Processes with Learned Parameters Cost-effectiveness of drone-delivered automated external defibrillators for cardiac arrest

Reference 59

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:02:43.785444Z

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No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation b1add0d8-800a-4983-89a8-f2eb90f448bd · outbound

This paper cites Association between sex and mortality in adults with in-hospital and out-of-hospital cardiac arrest: A systematic review and meta-analysis.

Formal Verification of Markov Processes with Learned Parameters Association between sex and mortality in adults with in-hospital and out-of-hospital cardiac arrest: A systematic review and meta-analysis

Reference 60

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:02:43.776418Z

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Observation d0b6addf-9a10-4420-b8d8-ea5dcc38b9c8 · outbound

This paper cites Interval linear and nonlinear systems.

Formal Verification of Markov Processes with Learned Parameters Interval linear and nonlinear systems

Reference 61

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:02:43.767597Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation d756afdf-3dfd-468e-ac25-ec13c265139d · outbound

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Formal Verification of Markov Processes with Learned Parameters Unresolved cited work

Reference 62

Resolution: unresolved; raw_fallback, observed 2026-08-10T14:02:43.758624Z

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Observation 2ce9ba08-3882-488c-8f20-2748dbaeb95c · outbound

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Formal Verification of Markov Processes with Learned Parameters Unresolved cited work

Reference 63

Resolution: unresolved; raw_fallback, observed 2026-08-10T14:02:43.750310Z

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This paper cites All operations above are interval arithmetic operations.

Formal Verification of Markov Processes with Learned Parameters All operations above are interval arithmetic operations

Reference 64

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:02:43.742055Z

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Formal Verification of Markov Processes with Learned Parameters Unresolved cited work

Reference 65

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Formal Verification of Markov Processes with Learned Parameters Unresolved cited work

Reference 66

Resolution: unresolved; raw_fallback, observed 2026-08-10T14:02:43.726215Z

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Observation 034c95ca-a75e-48ef-8903-10284807d94d · outbound

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Formal Verification of Markov Processes with Learned Parameters Unresolved cited work

Reference 67

Resolution: unresolved; raw_fallback, observed 2026-08-10T14:02:43.717752Z

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Observation b6814bb7-6471-41a3-a60d-3ba625617b64 · outbound

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Formal Verification of Markov Processes with Learned Parameters Unresolved cited work

Reference 68

Resolution: unresolved; raw_fallback, observed 2026-08-10T14:02:43.709643Z

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No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation f51bf02b-727a-42e0-8b23-11b1bb8f9117 · outbound

This paper cites if-then" rules specified in natural language, e.g., “if age >= 65 then 0.8.

Formal Verification of Markov Processes with Learned Parameters if-then" rules specified in natural language, e.g., “if age >= 65 then 0.8

Reference 69

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:02:43.701026Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 905cd0f0-f1c5-4d44-8cfb-2fb7736724a4 · outbound

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Formal Verification of Markov Processes with Learned Parameters Unresolved cited work

Reference 70

Resolution: unresolved; raw_fallback, observed 2026-08-10T14:02:43.692201Z

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Observation 660d3bda-fcb5-4a79-9022-8c9e65998794 · outbound

This paper cites Models for r and π are always used, while the number of modeled rows in P varies from 1 to 19, so that the total number of models runs from 3 to 21.

Formal Verification of Markov Processes with Learned Parameters Models for r and π are always used, while the number of modeled rows in P varies from 1 to 19, so that the total number of models runs from 3 to 21

Reference 71

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:02:43.683621Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 3318f39c-6f8e-4770-9409-f30cf6c5c05c · outbound

This paper cites Remaining rows of P are uniform.

Formal Verification of Markov Processes with Learned Parameters Remaining rows of P are uniform

Reference 72

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:02:43.674145Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation c5898a8b-9a3f-4b4f-88b2-1f29c79b58e5 · outbound

This paper cites We vary hidden layers in {1, 2} and neurons per layer in {5, 10, 15, 20}, with remaining rows of P set uniformly.

Formal Verification of Markov Processes with Learned Parameters We vary hidden layers in {1, 2} and neurons per layer in {5, 10, 15, 20}, with remaining rows of P set uniformly

Reference 73

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:02:43.664940Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation bdd9fde8-7647-4301-a7d7-1add30f90133 · outbound

This paper cites [Yes] " is generally preferable to.

Formal Verification of Markov Processes with Learned Parameters [Yes] " is generally preferable to

Reference 74

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:02:43.656254Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 95c94d45-5951-409a-97fd-7b7a5525bc75 · outbound

This paper cites Guidelines: • The answer NA means that the abstract and introduction do not include the claims made in the paper.

Formal Verification of Markov Processes with Learned Parameters Guidelines: • The answer NA means that the abstract and introduction do not include the claims made in the paper

Reference 75

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:02:43.648058Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation eb3100b6-fbfd-4ed7-a2fb-9b0202b93432 · outbound

This paper cites Limitations.

Formal Verification of Markov Processes with Learned Parameters Limitations

Reference 76

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:02:43.639887Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 3af61c1d-cd70-430b-860d-3605036827a1 · outbound

This paper cites For proofs using more novel techniques (e.g.

Formal Verification of Markov Processes with Learned Parameters For proofs using more novel techniques (e.g

Reference 77

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:02:43.631790Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 2b499f03-836c-4be1-a0c9-b24b853797b9 · outbound

This paper cites As well, we release all code for the numerical experiments (with instructions on how to run each of the experiments with a simple command-line command).

Formal Verification of Markov Processes with Learned Parameters As well, we release all code for the numerical experiments (with instructions on how to run each of the experiments with a simple command-line command)

Reference 78

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:02:43.624128Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 84e97058-9d6f-4392-b6de-a94a6c0af4df · outbound

This paper cites We also release all the code for the numerical experiments, as simple scripts to run them, and for the case study.

Formal Verification of Markov Processes with Learned Parameters We also release all the code for the numerical experiments, as simple scripts to run them, and for the case study

Reference 79

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:02:43.616685Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation d1491dbf-9047-42a8-a52d-730124684744 · outbound

This paper cites Guidelines: • The answer NA means that the paper does not include experiments.

Formal Verification of Markov Processes with Learned Parameters Guidelines: • The answer NA means that the paper does not include experiments

Reference 80

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:02:43.608794Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation db990547-59e1-462f-a528-81dea8cb1f63 · outbound

This paper cites Guidelines: • The answer NA means that the paper does not include experiments.

Formal Verification of Markov Processes with Learned Parameters Guidelines: • The answer NA means that the paper does not include experiments

Reference 81

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:02:43.601022Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 297037e5-44f3-428f-bc1b-1550e8bea5e1 · outbound

This paper cites an unresolved cited work.

Formal Verification of Markov Processes with Learned Parameters Unresolved cited work

Reference 82

Resolution: unresolved; raw_fallback, observed 2026-08-10T14:02:43.593255Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

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This paper cites Guidelines: • The answer NA means that the authors have not reviewed the NeurIPS Code of Ethics.

Formal Verification of Markov Processes with Learned Parameters Guidelines: • The answer NA means that the authors have not reviewed the NeurIPS Code of Ethics

Reference 83

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:02:43.583650Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation b652b833-dbe9-4c49-973c-3f28ef0c48ff · outbound

This paper cites Guidelines: • The answer NA means that there is no societal impact of the work performed.

Formal Verification of Markov Processes with Learned Parameters Guidelines: • The answer NA means that there is no societal impact of the work performed

Reference 84

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:02:43.574267Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation e3035af1-8a09-4e01-9081-bb88522ff879 · outbound

This paper cites Guidelines: • The answer NA means that the paper poses no such risks.

Formal Verification of Markov Processes with Learned Parameters Guidelines: • The answer NA means that the paper poses no such risks

Reference 85

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:02:43.564533Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 2ead9a7b-bf5f-4ef4-a7d3-c8c24e5be41c · outbound

This paper cites Guidelines: • The answer NA means that the paper does not use existing assets.

Formal Verification of Markov Processes with Learned Parameters Guidelines: • The answer NA means that the paper does not use existing assets

Reference 86

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:02:43.554836Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation e4016cb7-884b-4862-ae21-615066b09722 · outbound

This paper cites Guidelines: • The answer NA means that the paper does not release new assets.

Formal Verification of Markov Processes with Learned Parameters Guidelines: • The answer NA means that the paper does not release new assets

Reference 87

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:02:43.545184Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 7edca5fa-6385-4372-9e30-0ae44392ee3b · outbound

This paper cites Guidelines: • The answer NA means that the paper does not involve crowdsourcing nor research with human subjects.

Formal Verification of Markov Processes with Learned Parameters Guidelines: • The answer NA means that the paper does not involve crowdsourcing nor research with human subjects

Reference 88

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:02:43.535304Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 13d935ed-79d9-4976-a0ca-64aec68523c9 · outbound

This paper cites Guidelines: • The answer NA means that the paper does not involve crowdsourcing nor research with human subjects.

Formal Verification of Markov Processes with Learned Parameters Guidelines: • The answer NA means that the paper does not involve crowdsourcing nor research with human subjects

Reference 89

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:02:43.526722Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 516a494f-904f-4977-8e3e-983740f762e3 · outbound

This paper cites Answer: [No] Justification: Does not use LLMs.

Formal Verification of Markov Processes with Learned Parameters Answer: [No] Justification: Does not use LLMs

Reference 90

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:02:43.517886Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

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