Bimanual Deformable Bag Manipulation Using a Structure-of-Interest Based Neural Dynamics Model Article Swipe
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.48550/arxiv.2401.11432
The manipulation of deformable objects by robotic systems presents a significant challenge due to their complex and infinite-dimensional configuration spaces. This paper introduces a novel approach to Deformable Object Manipulation (DOM) by emphasizing the identification and manipulation of Structures of Interest (SOIs) in deformable fabric bags. We propose a bimanual manipulation framework that leverages a Graph Neural Network (GNN)-based latent dynamics model to succinctly represent and predict the behavior of these SOIs. Our approach involves constructing a graph representation from partial point cloud data of the object and learning the latent dynamics model that effectively captures the essential deformations of the fabric bag within a reduced computational space. By integrating this latent dynamics model with Model Predictive Control (MPC), we empower robotic manipulators to perform precise and stable manipulation tasks focused on the SOIs. We have validated our framework through various empirical experiments demonstrating its efficacy in bimanual manipulation of fabric bags. Our contributions not only address the complexities inherent in DOM but also provide new perspectives and methodologies for enhancing robotic interactions with deformable objects by concentrating on their critical structural elements. Experimental videos can be obtained from https://sites.google.com/view/bagbot.
Related Topics
- Type
- preprint
- Language
- en
- Landing Page
- http://arxiv.org/abs/2401.11432
- https://arxiv.org/pdf/2401.11432
- OA Status
- green
- Cited By
- 2
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4391157830
Raw OpenAlex JSON
- OpenAlex ID
-
https://openalex.org/W4391157830Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.48550/arxiv.2401.11432Digital Object Identifier
- Title
-
Bimanual Deformable Bag Manipulation Using a Structure-of-Interest Based Neural Dynamics ModelWork title
- Type
-
preprintOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2024Year of publication
- Publication date
-
2024-01-21Full publication date if available
- Authors
-
Peng Zhou, Pai Zheng, Jiaming Qi, Chenxi Li, Chenguang Yang, David Navarro-Alarcón, Jia PanList of authors in order
- Landing page
-
https://arxiv.org/abs/2401.11432Publisher landing page
- PDF URL
-
https://arxiv.org/pdf/2401.11432Direct link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
greenOpen access status per OpenAlex
- OA URL
-
https://arxiv.org/pdf/2401.11432Direct OA link when available
- Concepts
-
Computer science, Artificial intelligence, Representation (politics), Object (grammar), Graph, Dynamics (music), Identification (biology), Theoretical computer science, Political science, Law, Botany, Physics, Biology, Politics, AcousticsTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
2Total citation count in OpenAlex
- Citations by year (recent)
-
2024: 2Per-year citation counts (last 5 years)
- Related works (count)
-
10Other works algorithmically related by OpenAlex
Full payload
| id | https://openalex.org/W4391157830 |
|---|---|
| doi | https://doi.org/10.48550/arxiv.2401.11432 |
| ids.doi | https://doi.org/10.48550/arxiv.2401.11432 |
| ids.openalex | https://openalex.org/W4391157830 |
| fwci | |
| type | preprint |
| title | Bimanual Deformable Bag Manipulation Using a Structure-of-Interest Based Neural Dynamics Model |
| biblio.issue | |
| biblio.volume | |
| biblio.last_page | |
| biblio.first_page | |
| topics[0].id | https://openalex.org/T10653 |
| topics[0].field.id | https://openalex.org/fields/22 |
| topics[0].field.display_name | Engineering |
| topics[0].score | 0.9876000285148621 |
| topics[0].domain.id | https://openalex.org/domains/3 |
| topics[0].domain.display_name | Physical Sciences |
| topics[0].subfield.id | https://openalex.org/subfields/2207 |
| topics[0].subfield.display_name | Control and Systems Engineering |
| topics[0].display_name | Robot Manipulation and Learning |
| topics[1].id | https://openalex.org/T10719 |
| topics[1].field.id | https://openalex.org/fields/22 |
| topics[1].field.display_name | Engineering |
| topics[1].score | 0.9617999792098999 |
| topics[1].domain.id | https://openalex.org/domains/3 |
| topics[1].domain.display_name | Physical Sciences |
| topics[1].subfield.id | https://openalex.org/subfields/2206 |
| topics[1].subfield.display_name | Computational Mechanics |
| topics[1].display_name | 3D Shape Modeling and Analysis |
| topics[2].id | https://openalex.org/T11159 |
| topics[2].field.id | https://openalex.org/fields/22 |
| topics[2].field.display_name | Engineering |
| topics[2].score | 0.9430000185966492 |
| topics[2].domain.id | https://openalex.org/domains/3 |
| topics[2].domain.display_name | Physical Sciences |
| topics[2].subfield.id | https://openalex.org/subfields/2209 |
| topics[2].subfield.display_name | Industrial and Manufacturing Engineering |
| topics[2].display_name | Manufacturing Process and Optimization |
| is_xpac | False |
| apc_list | |
| apc_paid | |
| concepts[0].id | https://openalex.org/C41008148 |
| concepts[0].level | 0 |
| concepts[0].score | 0.6960912942886353 |
| concepts[0].wikidata | https://www.wikidata.org/wiki/Q21198 |
| concepts[0].display_name | Computer science |
| concepts[1].id | https://openalex.org/C154945302 |
| concepts[1].level | 1 |
| concepts[1].score | 0.6117376685142517 |
| concepts[1].wikidata | https://www.wikidata.org/wiki/Q11660 |
| concepts[1].display_name | Artificial intelligence |
| concepts[2].id | https://openalex.org/C2776359362 |
| concepts[2].level | 3 |
| concepts[2].score | 0.5649738907814026 |
| concepts[2].wikidata | https://www.wikidata.org/wiki/Q2145286 |
| concepts[2].display_name | Representation (politics) |
| concepts[3].id | https://openalex.org/C2781238097 |
| concepts[3].level | 2 |
| concepts[3].score | 0.5457955002784729 |
| concepts[3].wikidata | https://www.wikidata.org/wiki/Q175026 |
| concepts[3].display_name | Object (grammar) |
| concepts[4].id | https://openalex.org/C132525143 |
| concepts[4].level | 2 |
| concepts[4].score | 0.4869862496852875 |
| concepts[4].wikidata | https://www.wikidata.org/wiki/Q141488 |
| concepts[4].display_name | Graph |
| concepts[5].id | https://openalex.org/C145912823 |
| concepts[5].level | 2 |
| concepts[5].score | 0.46911221742630005 |
| concepts[5].wikidata | https://www.wikidata.org/wiki/Q113558 |
| concepts[5].display_name | Dynamics (music) |
| concepts[6].id | https://openalex.org/C116834253 |
| concepts[6].level | 2 |
| concepts[6].score | 0.43715089559555054 |
| concepts[6].wikidata | https://www.wikidata.org/wiki/Q2039217 |
| concepts[6].display_name | Identification (biology) |
| concepts[7].id | https://openalex.org/C80444323 |
| concepts[7].level | 1 |
| concepts[7].score | 0.09649497270584106 |
| concepts[7].wikidata | https://www.wikidata.org/wiki/Q2878974 |
| concepts[7].display_name | Theoretical computer science |
| concepts[8].id | https://openalex.org/C17744445 |
| concepts[8].level | 0 |
| concepts[8].score | 0.0 |
| concepts[8].wikidata | https://www.wikidata.org/wiki/Q36442 |
| concepts[8].display_name | Political science |
| concepts[9].id | https://openalex.org/C199539241 |
| concepts[9].level | 1 |
| concepts[9].score | 0.0 |
| concepts[9].wikidata | https://www.wikidata.org/wiki/Q7748 |
| concepts[9].display_name | Law |
| concepts[10].id | https://openalex.org/C59822182 |
| concepts[10].level | 1 |
| concepts[10].score | 0.0 |
| concepts[10].wikidata | https://www.wikidata.org/wiki/Q441 |
| concepts[10].display_name | Botany |
| concepts[11].id | https://openalex.org/C121332964 |
| concepts[11].level | 0 |
| concepts[11].score | 0.0 |
| concepts[11].wikidata | https://www.wikidata.org/wiki/Q413 |
| concepts[11].display_name | Physics |
| concepts[12].id | https://openalex.org/C86803240 |
| concepts[12].level | 0 |
| concepts[12].score | 0.0 |
| concepts[12].wikidata | https://www.wikidata.org/wiki/Q420 |
| concepts[12].display_name | Biology |
| concepts[13].id | https://openalex.org/C94625758 |
| concepts[13].level | 2 |
| concepts[13].score | 0.0 |
| concepts[13].wikidata | https://www.wikidata.org/wiki/Q7163 |
| concepts[13].display_name | Politics |
| concepts[14].id | https://openalex.org/C24890656 |
| concepts[14].level | 1 |
| concepts[14].score | 0.0 |
| concepts[14].wikidata | https://www.wikidata.org/wiki/Q82811 |
| concepts[14].display_name | Acoustics |
| keywords[0].id | https://openalex.org/keywords/computer-science |
| keywords[0].score | 0.6960912942886353 |
| keywords[0].display_name | Computer science |
| keywords[1].id | https://openalex.org/keywords/artificial-intelligence |
| keywords[1].score | 0.6117376685142517 |
| keywords[1].display_name | Artificial intelligence |
| keywords[2].id | https://openalex.org/keywords/representation |
| keywords[2].score | 0.5649738907814026 |
| keywords[2].display_name | Representation (politics) |
| keywords[3].id | https://openalex.org/keywords/object |
| keywords[3].score | 0.5457955002784729 |
| keywords[3].display_name | Object (grammar) |
| keywords[4].id | https://openalex.org/keywords/graph |
| keywords[4].score | 0.4869862496852875 |
| keywords[4].display_name | Graph |
| keywords[5].id | https://openalex.org/keywords/dynamics |
| keywords[5].score | 0.46911221742630005 |
| keywords[5].display_name | Dynamics (music) |
| keywords[6].id | https://openalex.org/keywords/identification |
| keywords[6].score | 0.43715089559555054 |
| keywords[6].display_name | Identification (biology) |
| keywords[7].id | https://openalex.org/keywords/theoretical-computer-science |
| keywords[7].score | 0.09649497270584106 |
| keywords[7].display_name | Theoretical computer science |
| language | en |
| locations[0].id | pmh:oai:arXiv.org:2401.11432 |
| locations[0].is_oa | True |
| locations[0].source.id | https://openalex.org/S4306400194 |
| locations[0].source.issn | |
| locations[0].source.type | repository |
| locations[0].source.is_oa | True |
| locations[0].source.issn_l | |
| locations[0].source.is_core | False |
| locations[0].source.is_in_doaj | False |
| locations[0].source.display_name | arXiv (Cornell University) |
| locations[0].source.host_organization | https://openalex.org/I205783295 |
| locations[0].source.host_organization_name | Cornell University |
| locations[0].source.host_organization_lineage | https://openalex.org/I205783295 |
| locations[0].license | |
| locations[0].pdf_url | https://arxiv.org/pdf/2401.11432 |
| locations[0].version | submittedVersion |
| locations[0].raw_type | |
| locations[0].license_id | |
| locations[0].is_accepted | False |
| locations[0].is_published | False |
| locations[0].raw_source_name | |
| locations[0].landing_page_url | http://arxiv.org/abs/2401.11432 |
| locations[1].id | doi:10.48550/arxiv.2401.11432 |
| locations[1].is_oa | True |
| locations[1].source.id | https://openalex.org/S4306400194 |
| locations[1].source.issn | |
| locations[1].source.type | repository |
| locations[1].source.is_oa | True |
| locations[1].source.issn_l | |
| locations[1].source.is_core | False |
| locations[1].source.is_in_doaj | False |
| locations[1].source.display_name | arXiv (Cornell University) |
| locations[1].source.host_organization | https://openalex.org/I205783295 |
| locations[1].source.host_organization_name | Cornell University |
| locations[1].source.host_organization_lineage | https://openalex.org/I205783295 |
| locations[1].license | |
| locations[1].pdf_url | |
| locations[1].version | |
| locations[1].raw_type | article |
| locations[1].license_id | |
| locations[1].is_accepted | False |
| locations[1].is_published | |
| locations[1].raw_source_name | |
| locations[1].landing_page_url | https://doi.org/10.48550/arxiv.2401.11432 |
| indexed_in | arxiv, datacite |
| authorships[0].author.id | https://openalex.org/A5076945936 |
| authorships[0].author.orcid | https://orcid.org/0000-0002-7020-0943 |
| authorships[0].author.display_name | Peng Zhou |
| authorships[0].author_position | first |
| authorships[0].raw_author_name | Zhou, Peng |
| authorships[0].is_corresponding | False |
| authorships[1].author.id | https://openalex.org/A5079101040 |
| authorships[1].author.orcid | https://orcid.org/0000-0002-2329-8634 |
| authorships[1].author.display_name | Pai Zheng |
| authorships[1].author_position | middle |
| authorships[1].raw_author_name | Zheng, Pai |
| authorships[1].is_corresponding | False |
| authorships[2].author.id | https://openalex.org/A5079424145 |
| authorships[2].author.orcid | https://orcid.org/0000-0003-2655-6835 |
| authorships[2].author.display_name | Jiaming Qi |
| authorships[2].author_position | middle |
| authorships[2].raw_author_name | Qi, Jiaming |
| authorships[2].is_corresponding | False |
| authorships[3].author.id | https://openalex.org/A5062460840 |
| authorships[3].author.orcid | https://orcid.org/0000-0002-0963-4363 |
| authorships[3].author.display_name | Chenxi Li |
| authorships[3].author_position | middle |
| authorships[3].raw_author_name | Li, Chenxi |
| authorships[3].is_corresponding | False |
| authorships[4].author.id | https://openalex.org/A5019906827 |
| authorships[4].author.orcid | https://orcid.org/0000-0001-5255-5559 |
| authorships[4].author.display_name | Chenguang Yang |
| authorships[4].author_position | middle |
| authorships[4].raw_author_name | Yang, Chenguang |
| authorships[4].is_corresponding | False |
| authorships[5].author.id | https://openalex.org/A5056734737 |
| authorships[5].author.orcid | https://orcid.org/0000-0002-3426-6638 |
| authorships[5].author.display_name | David Navarro-Alarcón |
| authorships[5].author_position | middle |
| authorships[5].raw_author_name | Navarro-Alarcon, David |
| authorships[5].is_corresponding | False |
| authorships[6].author.id | https://openalex.org/A5076812698 |
| authorships[6].author.orcid | https://orcid.org/0000-0001-9003-2054 |
| authorships[6].author.display_name | Jia Pan |
| authorships[6].author_position | last |
| authorships[6].raw_author_name | Pan, Jia |
| authorships[6].is_corresponding | False |
| has_content.pdf | True |
| has_content.grobid_xml | True |
| is_paratext | False |
| open_access.is_oa | True |
| open_access.oa_url | https://arxiv.org/pdf/2401.11432 |
| open_access.oa_status | green |
| open_access.any_repository_has_fulltext | False |
| created_date | 2024-01-24T00:00:00 |
| display_name | Bimanual Deformable Bag Manipulation Using a Structure-of-Interest Based Neural Dynamics Model |
| has_fulltext | True |
| is_retracted | False |
| updated_date | 2025-11-06T06:51:31.235846 |
| primary_topic.id | https://openalex.org/T10653 |
| primary_topic.field.id | https://openalex.org/fields/22 |
| primary_topic.field.display_name | Engineering |
| primary_topic.score | 0.9876000285148621 |
| primary_topic.domain.id | https://openalex.org/domains/3 |
| primary_topic.domain.display_name | Physical Sciences |
| primary_topic.subfield.id | https://openalex.org/subfields/2207 |
| primary_topic.subfield.display_name | Control and Systems Engineering |
| primary_topic.display_name | Robot Manipulation and Learning |
| related_works | https://openalex.org/W2062195135, https://openalex.org/W2898732673, https://openalex.org/W2410053581, https://openalex.org/W2383658677, https://openalex.org/W3123203398, https://openalex.org/W2737719445, https://openalex.org/W2795079307, https://openalex.org/W4239098401, https://openalex.org/W2588268827, https://openalex.org/W1834370135 |
| cited_by_count | 2 |
| counts_by_year[0].year | 2024 |
| counts_by_year[0].cited_by_count | 2 |
| locations_count | 2 |
| best_oa_location.id | pmh:oai:arXiv.org:2401.11432 |
| best_oa_location.is_oa | True |
| best_oa_location.source.id | https://openalex.org/S4306400194 |
| best_oa_location.source.issn | |
| best_oa_location.source.type | repository |
| best_oa_location.source.is_oa | True |
| best_oa_location.source.issn_l | |
| best_oa_location.source.is_core | False |
| best_oa_location.source.is_in_doaj | False |
| best_oa_location.source.display_name | arXiv (Cornell University) |
| best_oa_location.source.host_organization | https://openalex.org/I205783295 |
| best_oa_location.source.host_organization_name | Cornell University |
| best_oa_location.source.host_organization_lineage | https://openalex.org/I205783295 |
| best_oa_location.license | |
| best_oa_location.pdf_url | https://arxiv.org/pdf/2401.11432 |
| best_oa_location.version | submittedVersion |
| best_oa_location.raw_type | |
| best_oa_location.license_id | |
| best_oa_location.is_accepted | False |
| best_oa_location.is_published | False |
| best_oa_location.raw_source_name | |
| best_oa_location.landing_page_url | http://arxiv.org/abs/2401.11432 |
| primary_location.id | pmh:oai:arXiv.org:2401.11432 |
| primary_location.is_oa | True |
| primary_location.source.id | https://openalex.org/S4306400194 |
| primary_location.source.issn | |
| primary_location.source.type | repository |
| primary_location.source.is_oa | True |
| primary_location.source.issn_l | |
| primary_location.source.is_core | False |
| primary_location.source.is_in_doaj | False |
| primary_location.source.display_name | arXiv (Cornell University) |
| primary_location.source.host_organization | https://openalex.org/I205783295 |
| primary_location.source.host_organization_name | Cornell University |
| primary_location.source.host_organization_lineage | https://openalex.org/I205783295 |
| primary_location.license | |
| primary_location.pdf_url | https://arxiv.org/pdf/2401.11432 |
| primary_location.version | submittedVersion |
| primary_location.raw_type | |
| primary_location.license_id | |
| primary_location.is_accepted | False |
| primary_location.is_published | False |
| primary_location.raw_source_name | |
| primary_location.landing_page_url | http://arxiv.org/abs/2401.11432 |
| publication_date | 2024-01-21 |
| publication_year | 2024 |
| referenced_works_count | 0 |
| abstract_inverted_index.a | 9, 23, 48, 54, 76, 104 |
| abstract_inverted_index.By | 108 |
| abstract_inverted_index.We | 46, 134 |
| abstract_inverted_index.be | 186 |
| abstract_inverted_index.by | 5, 31, 176 |
| abstract_inverted_index.in | 42, 146, 160 |
| abstract_inverted_index.of | 2, 37, 39, 69, 84, 99, 149 |
| abstract_inverted_index.on | 131, 178 |
| abstract_inverted_index.to | 13, 26, 62, 123 |
| abstract_inverted_index.we | 119 |
| abstract_inverted_index.DOM | 161 |
| abstract_inverted_index.Our | 72, 152 |
| abstract_inverted_index.The | 0 |
| abstract_inverted_index.and | 16, 35, 65, 87, 126, 167 |
| abstract_inverted_index.bag | 102 |
| abstract_inverted_index.but | 162 |
| abstract_inverted_index.can | 185 |
| abstract_inverted_index.due | 12 |
| abstract_inverted_index.for | 169 |
| abstract_inverted_index.its | 144 |
| abstract_inverted_index.new | 165 |
| abstract_inverted_index.not | 154 |
| abstract_inverted_index.our | 137 |
| abstract_inverted_index.the | 33, 67, 85, 89, 96, 100, 132, 157 |
| abstract_inverted_index.This | 20 |
| abstract_inverted_index.also | 163 |
| abstract_inverted_index.data | 83 |
| abstract_inverted_index.from | 79, 188 |
| abstract_inverted_index.have | 135 |
| abstract_inverted_index.only | 155 |
| abstract_inverted_index.that | 52, 93 |
| abstract_inverted_index.this | 110 |
| abstract_inverted_index.with | 114, 173 |
| abstract_inverted_index.(DOM) | 30 |
| abstract_inverted_index.Graph | 55 |
| abstract_inverted_index.Model | 115 |
| abstract_inverted_index.SOIs. | 71, 133 |
| abstract_inverted_index.bags. | 45, 151 |
| abstract_inverted_index.cloud | 82 |
| abstract_inverted_index.graph | 77 |
| abstract_inverted_index.model | 61, 92, 113 |
| abstract_inverted_index.novel | 24 |
| abstract_inverted_index.paper | 21 |
| abstract_inverted_index.point | 81 |
| abstract_inverted_index.tasks | 129 |
| abstract_inverted_index.their | 14, 179 |
| abstract_inverted_index.these | 70 |
| abstract_inverted_index.(MPC), | 118 |
| abstract_inverted_index.(SOIs) | 41 |
| abstract_inverted_index.Neural | 56 |
| abstract_inverted_index.Object | 28 |
| abstract_inverted_index.fabric | 44, 101, 150 |
| abstract_inverted_index.latent | 59, 90, 111 |
| abstract_inverted_index.object | 86 |
| abstract_inverted_index.space. | 107 |
| abstract_inverted_index.stable | 127 |
| abstract_inverted_index.videos | 184 |
| abstract_inverted_index.within | 103 |
| abstract_inverted_index.Control | 117 |
| abstract_inverted_index.Network | 57 |
| abstract_inverted_index.address | 156 |
| abstract_inverted_index.complex | 15 |
| abstract_inverted_index.empower | 120 |
| abstract_inverted_index.focused | 130 |
| abstract_inverted_index.objects | 4, 175 |
| abstract_inverted_index.partial | 80 |
| abstract_inverted_index.perform | 124 |
| abstract_inverted_index.precise | 125 |
| abstract_inverted_index.predict | 66 |
| abstract_inverted_index.propose | 47 |
| abstract_inverted_index.provide | 164 |
| abstract_inverted_index.reduced | 105 |
| abstract_inverted_index.robotic | 6, 121, 171 |
| abstract_inverted_index.spaces. | 19 |
| abstract_inverted_index.systems | 7 |
| abstract_inverted_index.through | 139 |
| abstract_inverted_index.various | 140 |
| abstract_inverted_index.Interest | 40 |
| abstract_inverted_index.approach | 25, 73 |
| abstract_inverted_index.behavior | 68 |
| abstract_inverted_index.bimanual | 49, 147 |
| abstract_inverted_index.captures | 95 |
| abstract_inverted_index.critical | 180 |
| abstract_inverted_index.dynamics | 60, 91, 112 |
| abstract_inverted_index.efficacy | 145 |
| abstract_inverted_index.inherent | 159 |
| abstract_inverted_index.involves | 74 |
| abstract_inverted_index.learning | 88 |
| abstract_inverted_index.obtained | 187 |
| abstract_inverted_index.presents | 8 |
| abstract_inverted_index.challenge | 11 |
| abstract_inverted_index.elements. | 182 |
| abstract_inverted_index.empirical | 141 |
| abstract_inverted_index.enhancing | 170 |
| abstract_inverted_index.essential | 97 |
| abstract_inverted_index.framework | 51, 138 |
| abstract_inverted_index.leverages | 53 |
| abstract_inverted_index.represent | 64 |
| abstract_inverted_index.validated | 136 |
| abstract_inverted_index.Deformable | 27 |
| abstract_inverted_index.Predictive | 116 |
| abstract_inverted_index.Structures | 38 |
| abstract_inverted_index.deformable | 3, 43, 174 |
| abstract_inverted_index.introduces | 22 |
| abstract_inverted_index.structural | 181 |
| abstract_inverted_index.succinctly | 63 |
| abstract_inverted_index.(GNN)-based | 58 |
| abstract_inverted_index.effectively | 94 |
| abstract_inverted_index.emphasizing | 32 |
| abstract_inverted_index.experiments | 142 |
| abstract_inverted_index.integrating | 109 |
| abstract_inverted_index.significant | 10 |
| abstract_inverted_index.Experimental | 183 |
| abstract_inverted_index.Manipulation | 29 |
| abstract_inverted_index.complexities | 158 |
| abstract_inverted_index.constructing | 75 |
| abstract_inverted_index.deformations | 98 |
| abstract_inverted_index.interactions | 172 |
| abstract_inverted_index.manipulation | 1, 36, 50, 128, 148 |
| abstract_inverted_index.manipulators | 122 |
| abstract_inverted_index.perspectives | 166 |
| abstract_inverted_index.computational | 106 |
| abstract_inverted_index.concentrating | 177 |
| abstract_inverted_index.configuration | 18 |
| abstract_inverted_index.contributions | 153 |
| abstract_inverted_index.demonstrating | 143 |
| abstract_inverted_index.methodologies | 168 |
| abstract_inverted_index.identification | 34 |
| abstract_inverted_index.representation | 78 |
| abstract_inverted_index.infinite-dimensional | 17 |
| abstract_inverted_index.https://sites.google.com/view/bagbot. | 189 |
| cited_by_percentile_year | |
| countries_distinct_count | 0 |
| institutions_distinct_count | 7 |
| citation_normalized_percentile |