Paper Citation Record · LEDGER

Efficient Contraction of Large Tensor Networks for Weighted Model Counting through Graph Decompositions

As of 22 August 2026, this Paper Citation Record lists 65 of 65 outbound references and 3 inbound Pith citation observations for arXiv:1908.04381.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
1908.04381 v2

Coverage vector

measured 65 of 65 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-14T13:58:09.276534Z

measured 68 of 68 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-22T06:32:14.747728+00:00

measured 3 of 3 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T18:38:54.795726Z

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: arxiv_reference, observed 2026-05-23T00:05:13.433613Z

Reference resolution

65 of 65 outbound references displayed

verified exact1
verified fuzzy37
unresolved27
parse uncertain0
malformed identifier0
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation efe8155e-6b53-4fd0-98ee-3ea75a11545e · outbound

This paper cites Bacchus, S.

Efficient Contraction of Large Tensor Networks for Weighted Model Counting through Graph Decompositions Bacchus, S

Reference 1

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Observation 6fe57db6-9dc9-49d2-9aa1-6cc1e6ac216d · outbound

This paper cites Domshlak, J.

Efficient Contraction of Large Tensor Networks for Weighted Model Counting through Graph Decompositions Domshlak, J

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T13:58:10.146631Z

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Observation 43b256a6-8515-440a-a39f-42b958289322 · outbound

This paper cites an unresolved cited work.

Efficient Contraction of Large Tensor Networks for Weighted Model Counting through Graph Decompositions Unresolved cited work

Reference 3

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Observation c9f462f6-824b-4162-bdf8-de07972306d9 · outbound

This paper cites an unresolved cited work.

Efficient Contraction of Large Tensor Networks for Weighted Model Counting through Graph Decompositions Unresolved cited work

Reference 4

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Observation 88da1256-1d07-420b-846d-658924d548b2 · outbound

This paper cites Oztok, A.

Efficient Contraction of Large Tensor Networks for Weighted Model Counting through Graph Decompositions Oztok, A

Reference 5

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Observation 39edffd4-95a4-46ce-a77f-f15daa1d9271 · outbound

This paper cites Thurley, SharpSAT: counting models with advanced componen t caching and implicit BCP, in: Proc.

Efficient Contraction of Large Tensor Networks for Weighted Model Counting through Graph Decompositions Thurley, SharpSAT: counting models with advanced componen t caching and implicit BCP, in: Proc

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T13:58:10.098041Z

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Observation 7606b31a-7a70-4894-94e9-b807f24c0216 · outbound

This paper cites an unresolved cited work.

Efficient Contraction of Large Tensor Networks for Weighted Model Counting through Graph Decompositions Unresolved cited work

Reference 7

Resolution: unresolved; raw_fallback, observed 2026-08-14T13:58:10.085029Z

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Observation d9e0c081-b5cb-41ec-86d3-18ba418f4ac7 · outbound

This paper cites Tensor Networks in a Nutshell.

Efficient Contraction of Large Tensor Networks for Weighted Model Counting through Graph Decompositions Tensor Networks in a Nutshell

Reference 8

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Observation c3759c8e-1ed7-428c-979f-69cff42be8a6 · outbound

This paper cites Era of Big Data Processing: A New Approach via Tensor Networks and Tensor Decompositions.

Efficient Contraction of Large Tensor Networks for Weighted Model Counting through Graph Decompositions Era of Big Data Processing: A New Approach via Tensor Networks and Tensor Decompositions

Reference 9

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Observation f1b61071-9a62-468b-8a4e-c33869290096 · outbound

This paper cites Or´ us, Tensor networks for complex quantum systems, Na ture Reviews Physics 1 (9) (2019) 538–550.

Efficient Contraction of Large Tensor Networks for Weighted Model Counting through Graph Decompositions Or´ us, Tensor networks for complex quantum systems, Na ture Reviews Physics 1 (9) (2019) 538–550

Reference 10

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Observation 760bc76c-62fd-409b-9502-8cd58a93b42f · outbound

This paper cites an unresolved cited work.

Efficient Contraction of Large Tensor Networks for Weighted Model Counting through Graph Decompositions Unresolved cited work

Reference 11

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Observation 547badcb-14fe-4609-ac51-6ec4df9d9677 · outbound

This paper cites an unresolved cited work.

Efficient Contraction of Large Tensor Networks for Weighted Model Counting through Graph Decompositions Unresolved cited work

Reference 12

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Observation 09cc5706-1e2e-42c8-8af5-22cd4c96ae7f · outbound

This paper cites an unresolved cited work.

Efficient Contraction of Large Tensor Networks for Weighted Model Counting through Graph Decompositions Unresolved cited work

Reference 13

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Observation b8e0acf6-e5f8-435e-af4a-47c7a9c9ebf3 · outbound

This paper cites Kjolstad, S.

Efficient Contraction of Large Tensor Networks for Weighted Model Counting through Graph Decompositions Kjolstad, S

Reference 14

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Observation f9b4ea15-2737-484d-b4ca-446513fde50d · outbound

This paper cites Tensor Comprehensions: Framework-Agnostic High-Performance Machine Learning Abstractions.

Efficient Contraction of Large Tensor Networks for Weighted Model Counting through Graph Decompositions Tensor Comprehensions: Framework-Agnostic High-Performance Machine Learning Abstractions

Reference 15

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Observation fc437905-bbd0-4b3a-8aeb-c0caf7257456 · outbound

This paper cites an unresolved cited work.

Efficient Contraction of Large Tensor Networks for Weighted Model Counting through Graph Decompositions Unresolved cited work

Reference 16

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Observation 01f4d5b5-0c1d-43e4-beba-e4c3a0ee17c5 · outbound

This paper cites Nelson, A.

Efficient Contraction of Large Tensor Networks for Weighted Model Counting through Graph Decompositions Nelson, A

Reference 17

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Observation 1ec1fd38-3489-45d6-98a3-421887ef9f13 · outbound

This paper cites Pfeifer, J.

Efficient Contraction of Large Tensor Networks for Weighted Model Counting through Graph Decompositions Pfeifer, J

Reference 18

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Observation 42370043-d10f-4d7f-a68f-a3b676a24b18 · outbound

This paper cites Fast counting with tensor networks.

Efficient Contraction of Large Tensor Networks for Weighted Model Counting through Graph Decompositions Fast counting with tensor networks

Reference 19

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Observation 9b2141c9-4780-4c25-94a5-9beae31195c3 · outbound

This paper cites Lecture Notes of Tensor Network Contractions.

Efficient Contraction of Large Tensor Networks for Weighted Model Counting through Graph Decompositions Lecture Notes of Tensor Network Contractions

Reference 20

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Observation 12be83db-daea-4b1a-8ea6-fb20ad7f8fd0 · outbound

This paper cites Greco, N.

Efficient Contraction of Large Tensor Networks for Weighted Model Counting through Graph Decompositions Greco, N

Reference 21

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Observation 002738c7-c085-466c-9908-dd323e97a806 · outbound

This paper cites an unresolved cited work.

Efficient Contraction of Large Tensor Networks for Weighted Model Counting through Graph Decompositions Unresolved cited work

Reference 22

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Observation fb396ee7-ee52-4f49-9c3b-4cc2d6814299 · outbound

This paper cites an unresolved cited work.

Efficient Contraction of Large Tensor Networks for Weighted Model Counting through Graph Decompositions Unresolved cited work

Reference 23

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Observation e72eb6c0-b483-4bba-81e6-9cb7cc538de7 · outbound

This paper cites Abseher, N.

Efficient Contraction of Large Tensor Networks for Weighted Model Counting through Graph Decompositions Abseher, N

Reference 24

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Observation e8dc8ef0-83cb-4531-add7-743e333b1447 · outbound

This paper cites Hamann, B.

Efficient Contraction of Large Tensor Networks for Weighted Model Counting through Graph Decompositions Hamann, B

Reference 25

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Observation 2db6aef5-50b1-410b-a3b9-065a76021e5d · outbound

This paper cites Tamaki, Positive-instance driven dynamic programming for tr eewidth, in: Proc.

Efficient Contraction of Large Tensor Networks for Weighted Model Counting through Graph Decompositions Tamaki, Positive-instance driven dynamic programming for tr eewidth, in: Proc

Reference 26

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Observation e5517d43-e77f-41ad-bce8-7b4ac014d525 · outbound

This paper cites Fischer, J.

Efficient Contraction of Large Tensor Networks for Weighted Model Counting through Graph Decompositions Fischer, J

Reference 27

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Observation 69cc295a-323b-4a30-8e85-2fdfb9ef622c · outbound

This paper cites Samer, S.

Efficient Contraction of Large Tensor Networks for Weighted Model Counting through Graph Decompositions Samer, S

Reference 28

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Observation 10588bd7-28ac-425e-bc98-fe63a32bfc7b · outbound

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Efficient Contraction of Large Tensor Networks for Weighted Model Counting through Graph Decompositions Unresolved cited work

Reference 29

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Observation 684b0e33-2e01-4509-9e33-e09561c84c46 · outbound

This paper cites de Oliveira Oliveira, On the satisﬁability of quantum circuits of sm all treewidth, in: International Computer Science Symposium in Russia , Springer, 2015, pp.

Efficient Contraction of Large Tensor Networks for Weighted Model Counting through Graph Decompositions de Oliveira Oliveira, On the satisﬁability of quantum circuits of sm all treewidth, in: International Computer Science Symposium in Russia , Springer, 2015, pp

Reference 30

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Observation 11bb6068-595f-4e76-8949-00858bc234f6 · outbound

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Efficient Contraction of Large Tensor Networks for Weighted Model Counting through Graph Decompositions Unresolved cited work

Reference 31

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Observation 0f567e56-5f6e-4e38-a1ed-590b997a72fd · outbound

This paper cites Grasedyck, Hierarchical singular value decomposition of ten sors, SIAM Journal on Matrix Analysis and Applications 31 (4) (2010) 2029–205 4.

Efficient Contraction of Large Tensor Networks for Weighted Model Counting through Graph Decompositions Grasedyck, Hierarchical singular value decomposition of ten sors, SIAM Journal on Matrix Analysis and Applications 31 (4) (2010) 2029–205 4

Reference 32

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Observation d15510da-ea7f-4157-8f2d-61401748fc1a · outbound

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Efficient Contraction of Large Tensor Networks for Weighted Model Counting through Graph Decompositions Unresolved cited work

Reference 33

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Observation 1689dfad-c46f-486b-a006-cdfaea885427 · outbound

This paper cites Lagniez, P.

Efficient Contraction of Large Tensor Networks for Weighted Model Counting through Graph Decompositions Lagniez, P

Reference 34

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Observation 0d98609d-159f-4d13-abd2-67f1f875ed46 · outbound

This paper cites Charwat, S.

Efficient Contraction of Large Tensor Networks for Weighted Model Counting through Graph Decompositions Charwat, S

Reference 35

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Observation 2ce80430-6c4a-49ce-83c1-652743ef71bb · outbound

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Efficient Contraction of Large Tensor Networks for Weighted Model Counting through Graph Decompositions Unresolved cited work

Reference 36

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Observation efa810f6-f5d4-41bb-861b-cc049c653839 · outbound

This paper cites an unresolved cited work.

Efficient Contraction of Large Tensor Networks for Weighted Model Counting through Graph Decompositions Unresolved cited work

Reference 37

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Observation 984b2826-013f-41b8-8573-8709a0a7473f · outbound

This paper cites Robertson, P.

Efficient Contraction of Large Tensor Networks for Weighted Model Counting through Graph Decompositions Robertson, P

Reference 38

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Observation 05302226-3f1d-4841-a616-3641e08fb0c3 · outbound

This paper cites Sasak, Comparing 17 graph parameters, Master’s thesis, T he University of Bergen (2010).

Efficient Contraction of Large Tensor Networks for Weighted Model Counting through Graph Decompositions Sasak, Comparing 17 graph parameters, Master’s thesis, T he University of Bergen (2010)

Reference 39

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Observation 00bb8b2b-b3df-4158-b8c9-fbd8cdb760ca · outbound

This paper cites Swami, A.

Efficient Contraction of Large Tensor Networks for Weighted Model Counting through Graph Decompositions Swami, A

Reference 40

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Observation a18af759-4010-42c0-bc95-dce2d6e72413 · outbound

This paper cites Dechter, Bucket elimination: A unifying framework for reaso ning, Arti- ﬁcial Intelligence 113 (1-2) (1999) 41–85.

Efficient Contraction of Large Tensor Networks for Weighted Model Counting through Graph Decompositions Dechter, Bucket elimination: A unifying framework for reaso ning, Arti- ﬁcial Intelligence 113 (1-2) (1999) 41–85

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T13:58:09.714164Z

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Observation 7d39f4b9-9fa9-4da7-af92-468ff0cef594 · outbound

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Efficient Contraction of Large Tensor Networks for Weighted Model Counting through Graph Decompositions Unresolved cited work

Reference 42

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Observation 950e08fc-f4d9-4790-ba33-e84eca08b747 · outbound

This paper cites Chaudhuri, M.

Efficient Contraction of Large Tensor Networks for Weighted Model Counting through Graph Decompositions Chaudhuri, M

Reference 43

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Observation 1426b0aa-3d4d-48bc-95d6-cb19e11f134f · outbound

This paper cites Cavallo, M.

Efficient Contraction of Large Tensor Networks for Weighted Model Counting through Graph Decompositions Cavallo, M

Reference 44

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Observation 8c5c0708-4107-4a4b-94bc-eba57c131f76 · outbound

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Efficient Contraction of Large Tensor Networks for Weighted Model Counting through Graph Decompositions Unresolved cited work

Reference 45

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Observation a4c5ff8a-7cb1-4123-b5ea-af896e941266 · outbound

This paper cites Duality of Graphical Models and Tensor Networks.

Efficient Contraction of Large Tensor Networks for Weighted Model Counting through Graph Decompositions Duality of Graphical Models and Tensor Networks

Reference 46

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This paper cites Abo Khamis, H.

Efficient Contraction of Large Tensor Networks for Weighted Model Counting through Graph Decompositions Abo Khamis, H

Reference 47

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Observation 6e499177-6837-4326-8d5d-abe0e16a9dcc · outbound

This paper cites an unresolved cited work.

Efficient Contraction of Large Tensor Networks for Weighted Model Counting through Graph Decompositions Unresolved cited work

Reference 48

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Observation 4c6733b9-3042-4979-923a-766d9969dab7 · outbound

This paper cites Fatahalian, J.

Efficient Contraction of Large Tensor Networks for Weighted Model Counting through Graph Decompositions Fatahalian, J

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T13:58:09.623168Z

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Observation 604722bb-ec19-4c16-827c-4f3d221dd764 · outbound

This paper cites Due˜ nas-Osorio, M.

Efficient Contraction of Large Tensor Networks for Weighted Model Counting through Graph Decompositions Due˜ nas-Osorio, M

Reference 50

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Observation c5041816-8baf-4fb6-aac7-815dcac627b2 · outbound

This paper cites Evenbly, R.

Efficient Contraction of Large Tensor Networks for Weighted Model Counting through Graph Decompositions Evenbly, R

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T13:58:09.598343Z

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Observation a54c1959-5fe6-4438-9985-6ee1569e80d1 · outbound

This paper cites Dechter, Constraint processing, Morgan Kaufmann, 2003.

Efficient Contraction of Large Tensor Networks for Weighted Model Counting through Graph Decompositions Dechter, Constraint processing, Morgan Kaufmann, 2003

Reference 52

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Observation ff872bf9-b7ff-479d-a9e9-e09acb913a88 · outbound

This paper cites Ying, Tensor network skeletonization, Multiscale Modeling & Sim ulation 15 (4) (2017) 1423–1447.

Efficient Contraction of Large Tensor Networks for Weighted Model Counting through Graph Decompositions Ying, Tensor network skeletonization, Multiscale Modeling & Sim ulation 15 (4) (2017) 1423–1447

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T13:58:09.574475Z

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Observation 88e19450-81ed-468d-98e8-f3b3647d9f56 · outbound

This paper cites an unresolved cited work.

Efficient Contraction of Large Tensor Networks for Weighted Model Counting through Graph Decompositions Unresolved cited work

Reference 54

Resolution: unresolved; raw_fallback, observed 2026-08-14T13:58:09.562040Z

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This paper cites Dalmau, P.

Efficient Contraction of Large Tensor Networks for Weighted Model Counting through Graph Decompositions Dalmau, P

Reference 55

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Observation b1c92752-ffc4-49a2-8198-9b4b8bf6d93d · outbound

This paper cites an unresolved cited work.

Efficient Contraction of Large Tensor Networks for Weighted Model Counting through Graph Decompositions Unresolved cited work

Reference 56

Resolution: unresolved; raw_fallback, observed 2026-08-14T13:58:09.535774Z

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Observation 0e2a3315-99e4-411f-a35d-b06731abf4bd · outbound

This paper cites an unresolved cited work.

Efficient Contraction of Large Tensor Networks for Weighted Model Counting through Graph Decompositions Unresolved cited work

Reference 57

Resolution: unresolved; raw_fallback, observed 2026-08-14T13:58:09.523528Z

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Observation 2e3d1092-e452-49a5-8393-5ba28511f406 · outbound

This paper cites `Alvarez, R.

Efficient Contraction of Large Tensor Networks for Weighted Model Counting through Graph Decompositions `Alvarez, R

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T13:58:09.510634Z

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Efficient Contraction of Large Tensor Networks for Weighted Model Counting through Graph Decompositions Unresolved cited work

Reference 59

Resolution: unresolved; raw_fallback, observed 2026-08-14T13:58:09.495233Z

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Observation f4d9c672-a08b-4415-9e21-0b8fdc066815 · outbound

This paper cites Samer, S.

Efficient Contraction of Large Tensor Networks for Weighted Model Counting through Graph Decompositions Samer, S

Reference 60

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Observation 4135d6ab-3c1b-4108-859c-1f77d44d9e83 · outbound

This paper cites de Oliveira Oliveira, Size-treewidth tradeoﬀs for circuits comp uting the element distinctness function, Theory of Computing Systems 62 (1 ) (2018) 136–161.

Efficient Contraction of Large Tensor Networks for Weighted Model Counting through Graph Decompositions de Oliveira Oliveira, Size-treewidth tradeoﬀs for circuits comp uting the element distinctness function, Theory of Computing Systems 62 (1 ) (2018) 136–161

Reference 61

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Observation 5d569ab8-9c94-4193-9323-1e23e27a855c · outbound

This paper cites Viger, M.

Efficient Contraction of Large Tensor Networks for Weighted Model Counting through Graph Decompositions Viger, M

Reference 62

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Observation 18d683de-9671-4ee6-a202-17f19c57df28 · outbound

This paper cites Lagniez, P.

Efficient Contraction of Large Tensor Networks for Weighted Model Counting through Graph Decompositions Lagniez, P

Reference 63

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Observation 1558bbc8-ca2e-48de-8b9c-830115926f56 · outbound

This paper cites Lagniez, E.

Efficient Contraction of Large Tensor Networks for Weighted Model Counting through Graph Decompositions Lagniez, E

Reference 64

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Observation 76dc6df5-e7b6-40ce-9272-702c3eb9f283 · outbound

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Reference 65

Resolution: unresolved; raw_fallback, observed 2026-08-14T13:58:09.411309Z

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Pith citing papers

Observation 7883d3b5-58e6-4892-9133-1b73656814c5 · inbound

Counting with the quantum alternating operator ansatz cites this paper.

Counting with the quantum alternating operator ansatz Efficient Contraction of Large Tensor Networks for Weighted Model Counting through Graph Decompositions

Reference 24

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Observation 7db33d21-3de4-4736-a899-55d8223f6e19 · inbound

Quantum Counting in the Rydberg Blockade cites this paper.

Quantum Counting in the Rydberg Blockade Efficient Contraction of Large Tensor Networks for Weighted Model Counting through Graph Decompositions

Reference 14

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Observation df59a608-e278-4be4-8534-cc77fee4882c · inbound

From Tensor Networks to Tractable Circuits, and back cites this paper.

From Tensor Networks to Tractable Circuits, and back Efficient Contraction of Large Tensor Networks for Weighted Model Counting through Graph Decompositions

Reference 18

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