Approximate Probabilistic Bisimulation for Continuous-Time Markov Chains | Paper Citation Record

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This paper cites Electronic Notes in Theoretical Computer Science297, 3–25 (2013).https://doi.org/10.1016/j.entcs.2013.12.002, pro- ceedings of the first workshop on Hybrid Autonomous Systems.

Approximate Probabilistic Bisimulation for Continuous-Time Markov Chains Electronic Notes in Theoretical Computer Science297, 3–25 (2013).https://doi.org/10.1016/j.entcs.2013.12.002, pro- ceedings of the first workshop on Hybrid Autonomous Systems

Reference 1

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This paper cites In: Kroening, D., Păsăreanu, C.S.

Approximate Probabilistic Bisimulation for Continuous-Time Markov Chains In: Kroening, D., Păsăreanu, C.S

Reference 2

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This paper cites In: van Breugel, F., Kashefi, E., Palamidessi, C., Rutten, J.

Approximate Probabilistic Bisimulation for Continuous-Time Markov Chains In: van Breugel, F., Kashefi, E., Palamidessi, C., Rutten, J

Reference 3

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This paper cites PLoS ONE9(4), e94553 (Apr 2014).https://doi.org/10.

Approximate Probabilistic Bisimulation for Continuous-Time Markov Chains PLoS ONE9(4), e94553 (Apr 2014).https://doi.org/10

Reference 4

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Approximate Probabilistic Bisimulation for Continuous-Time Markov Chains Unresolved cited work

Reference 5

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This paper cites In: Petri Nets.

Approximate Probabilistic Bisimulation for Continuous-Time Markov Chains In: Petri Nets

Reference 6

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Approximate Probabilistic Bisimulation for Continuous-Time Markov Chains Unresolved cited work

Reference 7

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This paper cites In: SAFECOMP.

Approximate Probabilistic Bisimulation for Continuous-Time Markov Chains In: SAFECOMP

Reference 8

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This paper cites ACM Trans.

Approximate Probabilistic Bisimulation for Continuous-Time Markov Chains ACM Trans

Reference 9

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This paper cites In: Alur, R., Henzinger, T.A.

Approximate Probabilistic Bisimulation for Continuous-Time Markov Chains In: Alur, R., Henzinger, T.A

Reference 10

Resolution: verified exact; doi, observed 2026-08-07T15:22:13.293618Z

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This paper cites IEEE Trans.

Approximate Probabilistic Bisimulation for Continuous-Time Markov Chains IEEE Trans

Reference 11

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This paper cites In: Montanari, U., Rolim, J.D.P., Welzl, E.

Approximate Probabilistic Bisimulation for Continuous-Time Markov Chains In: Montanari, U., Rolim, J.D.P., Welzl, E

Reference 12

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This paper cites Ab initio properties of the NaLi molecule in the $a^3\Sigma^+$ electronic state.

Approximate Probabilistic Bisimulation for Continuous-Time Markov Chains Ab initio properties of the NaLi molecule in the $a^3\Sigma^+$ electronic state

Reference 13

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This paper cites The MIT Press (2008).

Approximate Probabilistic Bisimulation for Continuous-Time Markov Chains The MIT Press (2008)

Reference 14

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This paper cites Information and Computation200(2), 149–214 (2005).

Approximate Probabilistic Bisimulation for Continuous-Time Markov Chains Information and Computation200(2), 149–214 (2005)

Reference 15

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This paper cites Logical Methods in Computer Science19(1) (2023).https://doi.org/10.46298/lmcs-19(1:22)2023.

Approximate Probabilistic Bisimulation for Continuous-Time Markov Chains Logical Methods in Computer Science19(1) (2023).https://doi.org/10.46298/lmcs-19(1:22)2023

Reference 16

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This paper cites IEEE Transactions on ComputersC-27(6), 540–547 (1978).https://doi.org/ 10.1109/TC.1978.1675145.

Approximate Probabilistic Bisimulation for Continuous-Time Markov Chains IEEE Transactions on ComputersC-27(6), 540–547 (1978).https://doi.org/ 10.1109/TC.1978.1675145

Reference 17

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This paper cites In: Esparza, J., Murawski, A.S.

Approximate Probabilistic Bisimulation for Continuous-Time Markov Chains In: Esparza, J., Murawski, A.S

Reference 18

Resolution: verified exact; doi, observed 2026-08-07T15:22:11.970730Z

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This paper cites Journal of Applied Probability31(1), 59–75 (1994).https://doi.org/10.2307/3215235.

Approximate Probabilistic Bisimulation for Continuous-Time Markov Chains Journal of Applied Probability31(1), 59–75 (1994).https://doi.org/10.2307/3215235

Reference 19

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This paper cites In: Abate, A., Marin, A.

Approximate Probabilistic Bisimulation for Continuous-Time Markov Chains In: Abate, A., Marin, A

Reference 20

Resolution: verified exact; doi, observed 2026-08-07T15:22:11.493593Z

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This paper cites IEEE Transactions on Automatic Control68(11), 6557–6572 (Nov 2023).https://doi.

Approximate Probabilistic Bisimulation for Continuous-Time Markov Chains IEEE Transactions on Automatic Control68(11), 6557–6572 (Nov 2023).https://doi

Reference 21

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This paper cites In: 24th IEEE Symposium on Logic In Computer Science (LICS).

Approximate Probabilistic Bisimulation for Continuous-Time Markov Chains In: 24th IEEE Symposium on Logic In Computer Science (LICS)

Reference 22

Resolution: verified exact; doi, observed 2026-08-07T15:22:11.283688Z

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This paper cites In: Proceedings of the Thirteenth Annual IEEE Symposium on Logic in Computer Science (LiCS).

Approximate Probabilistic Bisimulation for Continuous-Time Markov Chains In: Proceedings of the Thirteenth Annual IEEE Symposium on Logic in Computer Science (LiCS)

Reference 23

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This paper cites Information and Computation179(2), 163–193 (2002).https://doi.org/ 10.1006/inco.2001.2962.

Approximate Probabilistic Bisimulation for Continuous-Time Markov Chains Information and Computation179(2), 163–193 (2002).https://doi.org/ 10.1006/inco.2001.2962

Reference 24

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This paper cites In: Fifth International Conference on Quantitative Evaluation of Systems (QEST 2008).

Approximate Probabilistic Bisimulation for Continuous-Time Markov Chains In: Fifth International Conference on Quantitative Evaluation of Systems (QEST 2008)

Reference 25

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This paper cites In: Tauman Kalai, Y.

Approximate Probabilistic Bisimulation for Continuous-Time Markov Chains In: Tauman Kalai, Y

Reference 26

Resolution: verified exact; doi, observed 2026-08-07T15:22:10.636392Z

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Observation 0d81f31d-24dc-41fb-aef4-5862212662a4 · outbound

This paper cites an unresolved cited work.

Approximate Probabilistic Bisimulation for Continuous-Time Markov Chains Unresolved cited work

Reference 27

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This paper cites The Post Office Electrical Engineer’s Jour- nal pp.

Approximate Probabilistic Bisimulation for Continuous-Time Markov Chains The Post Office Electrical Engineer’s Jour- nal pp

Reference 28

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Observation 8a13a238-8c4b-400c-8a3d-16dd6058c32e · outbound

This paper cites Performance Evaluation20(1), 223–243 (1994).https://doi.org/10.1016/ 0166-5316(94)90015-9.

Approximate Probabilistic Bisimulation for Continuous-Time Markov Chains Performance Evaluation20(1), 223–243 (1994).https://doi.org/10.1016/ 0166-5316(94)90015-9

Reference 29

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This paper cites IEEE Transactions on Software Engi- neering20(7), 516–525 (1994).https://doi.org/10.1109/32.297940.

Approximate Probabilistic Bisimulation for Continuous-Time Markov Chains IEEE Transactions on Software Engi- neering20(7), 516–525 (1994).https://doi.org/10.1109/32.297940

Reference 30

Resolution: verified exact; doi, observed 2026-08-07T15:22:10.328646Z

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This paper cites In: Remke, A., Stoelinga, M.

Approximate Probabilistic Bisimulation for Continuous-Time Markov Chains In: Remke, A., Stoelinga, M

Reference 31

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This paper cites Com- puters & Operations Research4(1), 47–53 (1977).https://doi.org/10.1016/ 0305-0548(77)90007-7.

Approximate Probabilistic Bisimulation for Continuous-Time Markov Chains Com- puters & Operations Research4(1), 47–53 (1977).https://doi.org/10.1016/ 0305-0548(77)90007-7

Reference 32

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This paper cites In: 2021 American Control Conference (ACC).

Approximate Probabilistic Bisimulation for Continuous-Time Markov Chains In: 2021 American Control Conference (ACC)

Reference 33

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This paper cites International Journal on Software Tools for Technology Transfer (STTT)24, 589–610 (2022).https://doi.org/10.1007/s10009-021-00633-z.

Approximate Probabilistic Bisimulation for Continuous-Time Markov Chains International Journal on Software Tools for Technology Transfer (STTT)24, 589–610 (2022).https://doi.org/10.1007/s10009-021-00633-z

Reference 34

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Observation 36d013b4-2b17-49da-84de-6f6d6c7a53e4 · outbound

This paper cites Scandi- navian Actuarial Journal1953(sup1), 87–91 (1953).https://doi.org/10.1080/ 03461238.1953.10419459.

Approximate Probabilistic Bisimulation for Continuous-Time Markov Chains Scandi- navian Actuarial Journal1953(sup1), 87–91 (1953).https://doi.org/10.1080/ 03461238.1953.10419459

Reference 35

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This paper cites Undergraduate Texts in Mathe- matics (UTM), Springer New York (1976).

Approximate Probabilistic Bisimulation for Continuous-Time Markov Chains Undergraduate Texts in Mathe- matics (UTM), Springer New York (1976)

Reference 36

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This paper cites In: Bojańczy, M., Chekuri, C.

Approximate Probabilistic Bisimulation for Continuous-Time Markov Chains In: Bojańczy, M., Chekuri, C

Reference 37

Resolution: verified exact; doi, observed 2026-08-07T15:22:10.156550Z

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This paper cites Mathematische Annalen104, 415–458 (1931).https://doi.org/10.

Approximate Probabilistic Bisimulation for Continuous-Time Markov Chains Mathematische Annalen104, 415–458 (1931).https://doi.org/10

Reference 38

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This paper cites Springer Texts in Statistics (STS), Springer New York (2010).https://doi.org/ 10.1007/978-1-4419-1772-0.

Approximate Probabilistic Bisimulation for Continuous-Time Markov Chains Springer Texts in Statistics (STS), Springer New York (2010).https://doi.org/ 10.1007/978-1-4419-1772-0

Reference 39

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This paper cites In: Gopalakrishnan, G., Qadeer, S.

Approximate Probabilistic Bisimulation for Continuous-Time Markov Chains In: Gopalakrishnan, G., Qadeer, S

Reference 40

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Reference 41

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Observation 0126e7b6-b9ed-40a8-87e7-db4421d2f8ab · outbound

This paper cites Information and Computation94(1), 1–28 (1991).https://doi.org/10.1016/0890-5401(91) 90030-6.

Approximate Probabilistic Bisimulation for Continuous-Time Markov Chains Information and Computation94(1), 1–28 (1991).https://doi.org/10.1016/0890-5401(91) 90030-6

Reference 42

Resolution: verified exact; doi, observed 2026-08-07T15:22:09.749300Z

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Observation 6bcd0c00-0258-4b3d-bba5-008800e275c1 · outbound

This paper cites Journal of Applied Probability61(4), 1278–1300 (2024).https://doi.org/ 10.1017/jpr.2024.20.

Approximate Probabilistic Bisimulation for Continuous-Time Markov Chains Journal of Applied Probability61(4), 1278–1300 (2024).https://doi.org/ 10.1017/jpr.2024.20

Reference 43

Resolution: verified exact; doi, observed 2026-08-07T15:22:09.541664Z

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This paper cites Sci- ence China Mathematics58(2), 2633–2642 (2015).https://doi.org/10.1007/ s11425-015-5019-z.

Approximate Probabilistic Bisimulation for Continuous-Time Markov Chains Sci- ence China Mathematics58(2), 2633–2642 (2015).https://doi.org/10.1007/ s11425-015-5019-z

Reference 44

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This paper cites Advances in Applied Probability50(2), 645–669 (2018).https://doi.org/10.1017/apr.2018.28.

Approximate Probabilistic Bisimulation for Continuous-Time Markov Chains Advances in Applied Probability50(2), 645–669 (2018).https://doi.org/10.1017/apr.2018.28

Reference 45

Resolution: verified exact; doi, observed 2026-08-07T15:22:09.388326Z

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Approximate Probabilistic Bisimulation for Continuous-Time Markov Chains Unresolved cited work

Reference 46

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Observation f75317bc-66f4-4745-9e2a-2d0e7641d7ce · outbound

This paper cites Performance Evaluation7(3), 175–194 (1987).https://doi.org/10.1016/ 0166-5316(87)90039-3.

Approximate Probabilistic Bisimulation for Continuous-Time Markov Chains Performance Evaluation7(3), 175–194 (1987).https://doi.org/10.1016/ 0166-5316(87)90039-3

Reference 47

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Observation 9fbdaa96-f6fe-43a9-8f16-7f133f1e5b8d · outbound

This paper cites In: André, É., Stoelinga, M.(eds.)FormalModelingandAnalysisofTimedSystems(FORMATS)2019.Lec- ture Notes in Computer Science (LNCS), vol.

Approximate Probabilistic Bisimulation for Continuous-Time Markov Chains In: André, É., Stoelinga, M.(eds.)FormalModelingandAnalysisofTimedSystems(FORMATS)2019.Lec- ture Notes in Computer Science (LNCS), vol

Reference 48

Resolution: verified exact; doi, observed 2026-08-07T15:22:09.092486Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 92412537-4aec-476c-af61-57c4a6065120 · outbound

This paper cites Acta Inf.59(2–3), 211–244 (Jun 2022).https://doi.org/10.1007/ s00236-021-00404-y.

Approximate Probabilistic Bisimulation for Continuous-Time Markov Chains Acta Inf.59(2–3), 211–244 (Jun 2022).https://doi.org/10.1007/ s00236-021-00404-y

Reference 49

Resolution: malformed identifier; raw_fallback, observed 2026-08-07T15:22:18.537829Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 94158851-d26a-4103-bf6b-bf3d50a2e6ae · outbound

This paper cites Society for Industrial and Applied Mathematics, Philadelphia, PA (2000).

Approximate Probabilistic Bisimulation for Continuous-Time Markov Chains Society for Industrial and Applied Mathematics, Philadelphia, PA (2000)

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:22:18.412828Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation d9fab9f5-9f06-4b33-995d-2d6f353dcdf9 · outbound

This paper cites Journal of Applied Probability42(4), 1003–1014 (2005).

Approximate Probabilistic Bisimulation for Continuous-Time Markov Chains Journal of Applied Probability42(4), 1003–1014 (2005)

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:22:18.319553Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation d932fb2a-4644-4b28-a7d6-d325913a694d · outbound

This paper cites Mathematics12(11) (2024).https://doi.org/10.

Approximate Probabilistic Bisimulation for Continuous-Time Markov Chains Mathematics12(11) (2024).https://doi.org/10

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:22:18.115943Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation f0c24a24-3565-4b30-9135-2d5bfb6521cf · outbound

This paper cites SIAM Review45(1), 3–49 (Jan 2003).https: //doi.org/10.1137/S00361445024180.

Approximate Probabilistic Bisimulation for Continuous-Time Markov Chains SIAM Review45(1), 3–49 (Jan 2003).https: //doi.org/10.1137/S00361445024180

Reference 53

Resolution: unresolved; no resolver link, observed 2026-08-07T15:22:06.022721Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation da6e0cd0-fec4-4519-9115-efb4b00cb2ec · outbound

This paper cites an unresolved cited work.

Approximate Probabilistic Bisimulation for Continuous-Time Markov Chains Unresolved cited work

Reference 54

Resolution: unresolved; raw_fallback, observed 2026-08-07T15:22:18.009345Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation b43ce2e2-5eec-45b6-b42f-d03ec42fb275 · outbound

This paper cites In: Abate, A., Marin, A.

Approximate Probabilistic Bisimulation for Continuous-Time Markov Chains In: Abate, A., Marin, A

Reference 55

Resolution: verified exact; doi, observed 2026-08-07T15:22:08.618549Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 1790d645-91b4-4b99-ae0b-37fdcd62ba1f · outbound

This paper cites https://doi.org/10.3390/a17040159.

Approximate Probabilistic Bisimulation for Continuous-Time Markov Chains https://doi.org/10.3390/a17040159

Reference 56

Resolution: verified exact; doi, observed 2026-08-07T15:22:08.464091Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 3225cc54-8307-46d0-a5c8-a4f02475e1c3 · outbound

This paper cites In: Jon- sson, B., Parrow, J.

Approximate Probabilistic Bisimulation for Continuous-Time Markov Chains In: Jon- sson, B., Parrow, J

Reference 57

Resolution: unresolved; no resolver link, observed 2026-08-07T15:22:06.452218Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9c3c01c3-57c2-44a9-a668-fa920cbabb48 · outbound

This paper cites SIAM Journal on Numerical Analysis 37(4), 1120–1137 (2000).https://doi.org/10.1137/S0036142998337235.

Approximate Probabilistic Bisimulation for Continuous-Time Markov Chains SIAM Journal on Numerical Analysis 37(4), 1120–1137 (2000).https://doi.org/10.1137/S0036142998337235

Reference 58

Resolution: verified exact; doi, observed 2026-08-07T15:22:08.281383Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation dab47512-6ce4-40a1-8703-acd3f840ecdc · outbound

This paper cites In: Majumdar, R., Silva, A.

Approximate Probabilistic Bisimulation for Continuous-Time Markov Chains In: Majumdar, R., Silva, A

Reference 59

Resolution: unresolved; no resolver link, observed 2026-08-07T15:22:06.636100Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a09cb084-1500-4b28-be5c-c2b266d7ef9e · outbound

This paper cites In: Massink, M., Norman, G.

Approximate Probabilistic Bisimulation for Continuous-Time Markov Chains In: Massink, M., Norman, G

Reference 60

Resolution: verified exact; doi, observed 2026-08-07T15:22:08.095445Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 688b5de3-72d0-442e-a213-61bee259cc03 · outbound

This paper cites IEEE Trans.

Approximate Probabilistic Bisimulation for Continuous-Time Markov Chains IEEE Trans

Reference 61

Resolution: metadata mismatch; raw_fallback, observed 2026-08-07T15:22:14.624082Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation ecb8427d-d852-4459-a8e2-a926034fc02d · outbound

This paper cites The Annals of Mathematical Statistics32(3), 716–729 (Sep 1961).https://doi.org/ 10.1214/aoms/1177704967.

Approximate Probabilistic Bisimulation for Continuous-Time Markov Chains The Annals of Mathematical Statistics32(3), 716–729 (Sep 1961).https://doi.org/ 10.1214/aoms/1177704967

Reference 62

Resolution: unresolved; no resolver link, observed 2026-08-07T15:22:06.903803Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 06dd5a59-087e-4aad-b997-621779160651 · outbound

This paper cites an unresolved cited work.

Approximate Probabilistic Bisimulation for Continuous-Time Markov Chains Unresolved cited work

Reference 63

Resolution: malformed identifier; raw_fallback, observed 2026-08-07T15:22:17.795934Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 9ccb102e-9610-44a9-bd7b-92a1bb3076c7 · outbound

This paper cites 3.s∼s ′ iffs∼ 0,0 s′.

Approximate Probabilistic Bisimulation for Continuous-Time Markov Chains 3.s∼s ′ iffs∼ 0,0 s′

Reference 65

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:22:17.612443Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation f4920eb9-4ce3-4453-b3f2-69d8c41be53d · outbound

This paper cites Define R={(x, z)∈S×S| ∃y∈S:x∼ ε1,δ1 yandy∼ ε2,δ2 z}.

Approximate Probabilistic Bisimulation for Continuous-Time Markov Chains Define R={(x, z)∈S×S| ∃y∈S:x∼ ε1,δ1 yandy∼ ε2,δ2 z}

Reference 66

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:22:17.436976Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation d5dc1b48-9c1b-488c-a12a-f17956dcfac2 · outbound

This paper cites To see this, lets∼0,0 s′ and s′ ∼0,0 s′′.

Approximate Probabilistic Bisimulation for Continuous-Time Markov Chains To see this, lets∼0,0 s′ and s′ ∼0,0 s′′

Reference 67

Resolution: malformed identifier; raw_fallback, observed 2026-08-07T15:22:17.202948Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation ddfdc3a0-2d04-4fae-9c08-84de2a1fd178 · outbound

This paper cites Theorem 17.Letθ∈[0,1),t >0, andq= max p∈S E(p).

Approximate Probabilistic Bisimulation for Continuous-Time Markov Chains Theorem 17.Letθ∈[0,1),t >0, andq= max p∈S E(p)

Reference 68

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:22:17.083159Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 98689a8d-ee14-4581-8c78-65a5123277b2 · outbound

This paper cites EachJi with corresponding eigenvalueλ i is anr i ×r i matrix of the form Ji =   λi 1 0 0.

Approximate Probabilistic Bisimulation for Continuous-Time Markov Chains EachJi with corresponding eigenvalueλ i is anr i ×r i matrix of the form Ji =   λi 1 0 0

Reference 69

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:22:16.891995Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation f6b0ae6b-bcde-46d7-b623-ab50a786cde9 · outbound

This paper cites an unresolved cited work.

Approximate Probabilistic Bisimulation for Continuous-Time Markov Chains Unresolved cited work

Reference 70

Resolution: unresolved; raw_fallback, observed 2026-08-07T15:22:16.752326Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation bbedd51e-b4c5-42cf-9293-6c379feebcdb · outbound

This paper cites Spork et al.

Approximate Probabilistic Bisimulation for Continuous-Time Markov Chains Spork et al

Reference 71

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:22:16.497935Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 2eb5ec16-3aae-47ff-b9a0-6982b40ff855 · outbound

This paper cites an unresolved cited work.

Approximate Probabilistic Bisimulation for Continuous-Time Markov Chains Unresolved cited work

Reference 72

Resolution: unresolved; raw_fallback, observed 2026-08-07T15:22:16.243569Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation cc3131fd-8d1d-43f3-b7d0-54b494950fda · outbound

This paper cites an unresolved cited work.

Approximate Probabilistic Bisimulation for Continuous-Time Markov Chains Unresolved cited work

Reference 73

Resolution: unresolved; raw_fallback, observed 2026-08-07T15:22:16.033477Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation e94f157d-66c2-4b1a-b90f-96ca487c935b · outbound

This paper cites an unresolved cited work.

Approximate Probabilistic Bisimulation for Continuous-Time Markov Chains Unresolved cited work

Reference 516

Resolution: verified exact; doi, observed 2026-08-07T15:22:08.844440Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Coverage vector

Reference resolution

Outbound references

Pith citing papers