{"id":"https://openalex.org/W7167586794","doi":"https://doi.org/10.48550/arxiv.2607.03513","title":"AquaGen: Scaling generative models to molecular dynamics precision on thousands of atoms","display_name":"AquaGen: Scaling generative models to molecular dynamics precision on thousands of atoms","publication_year":2026,"publication_date":"2026-07-03","ids":{"openalex":"https://openalex.org/W7167586794","doi":"https://doi.org/10.48550/arxiv.2607.03513"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2607.03513","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2607.03513","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2607.03513","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5027310054","display_name":"Emmanuel Bengio","orcid":"https://orcid.org/0000-0002-3257-4661"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Bengio, Emmanuel","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5125617030","display_name":"Sanjeev Raja","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Raja, Sanjeev","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5017648021","display_name":"Yui Tik Pang","orcid":"https://orcid.org/0000-0003-4843-4468"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Pang, Yui Tik","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5063472530","display_name":"Kerstin Klaeser","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Klaeser, Kerstin","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5084967706","display_name":"Cristian Gabellini","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Gabellini, Cristian","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5140215790","display_name":"Nikhil Shenoy","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Shenoy, Nikhil","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5088563202","display_name":"Francesco Di Giovanni","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Di Giovanni, Francesco","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5037753193","display_name":"Prudencio Tossou","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Tossou, Prudencio","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11948","display_name":"Machine Learning in Materials Science","score":0.9657999873161316,"subfield":{"id":"https://openalex.org/subfields/2505","display_name":"Materials Chemistry"},"field":{"id":"https://openalex.org/fields/25","display_name":"Materials Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11948","display_name":"Machine Learning in Materials Science","score":0.9657999873161316,"subfield":{"id":"https://openalex.org/subfields/2505","display_name":"Materials Chemistry"},"field":{"id":"https://openalex.org/fields/25","display_name":"Materials Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10044","display_name":"Protein Structure and Dynamics","score":0.00860000029206276,"subfield":{"id":"https://openalex.org/subfields/1312","display_name":"Molecular Biology"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T10211","display_name":"Computational Drug Discovery Methods","score":0.007799999788403511,"subfield":{"id":"https://openalex.org/subfields/1703","display_name":"Computational Theory and Mathematics"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/interpretability","display_name":"Interpretability","score":0.7139999866485596},{"id":"https://openalex.org/keywords/scaling","display_name":"Scaling","score":0.6159999966621399},{"id":"https://openalex.org/keywords/molecular-dynamics","display_name":"Molecular dynamics","score":0.5809000134468079},{"id":"https://openalex.org/keywords/degrees-of-freedom","display_name":"Degrees of freedom (physics and chemistry)","score":0.45019999146461487},{"id":"https://openalex.org/keywords/energy","display_name":"Energy (signal processing)","score":0.4440999925136566},{"id":"https://openalex.org/keywords/field","display_name":"Field (mathematics)","score":0.42579999566078186},{"id":"https://openalex.org/keywords/force-field","display_name":"Force field (fiction)","score":0.36640000343322754}],"concepts":[{"id":"https://openalex.org/C2781067378","wikidata":"https://www.wikidata.org/wiki/Q17027399","display_name":"Interpretability","level":2,"score":0.7139999866485596},{"id":"https://openalex.org/C99844830","wikidata":"https://www.wikidata.org/wiki/Q102441924","display_name":"Scaling","level":2,"score":0.6159999966621399},{"id":"https://openalex.org/C59593255","wikidata":"https://www.wikidata.org/wiki/Q901663","display_name":"Molecular dynamics","level":2,"score":0.5809000134468079},{"id":"https://openalex.org/C121864883","wikidata":"https://www.wikidata.org/wiki/Q677916","display_name":"Statistical physics","level":1,"score":0.5726000070571899},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4535999894142151},{"id":"https://openalex.org/C208081375","wikidata":"https://www.wikidata.org/wiki/Q274502","display_name":"Degrees of freedom (physics and chemistry)","level":2,"score":0.45019999146461487},{"id":"https://openalex.org/C186370098","wikidata":"https://www.wikidata.org/wiki/Q442787","display_name":"Energy (signal processing)","level":2,"score":0.4440999925136566},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.42579999566078186},{"id":"https://openalex.org/C10803110","wikidata":"https://www.wikidata.org/wiki/Q1341441","display_name":"Force field (fiction)","level":2,"score":0.36640000343322754},{"id":"https://openalex.org/C167966045","wikidata":"https://www.wikidata.org/wiki/Q5532625","display_name":"Generative model","level":3,"score":0.3391999900341034},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.33730000257492065},{"id":"https://openalex.org/C149629883","wikidata":"https://www.wikidata.org/wiki/Q660926","display_name":"Fraction (chemistry)","level":2,"score":0.33320000767707825},{"id":"https://openalex.org/C35304006","wikidata":"https://www.wikidata.org/wiki/Q5962","display_name":"Boltzmann constant","level":2,"score":0.3294000029563904},{"id":"https://openalex.org/C84551667","wikidata":"https://www.wikidata.org/wiki/Q155640","display_name":"Potential energy","level":2,"score":0.3003999888896942},{"id":"https://openalex.org/C97256817","wikidata":"https://www.wikidata.org/wiki/Q1462316","display_name":"Spurious relationship","level":2,"score":0.2799000144004822},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.2797999978065491},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.27489998936653137},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2533000111579895}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2607.03513","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2607.03513","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2607.03513","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2607.03513","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"sustainable_development_goals":[{"score":0.8851644396781921,"display_name":"Affordable and clean energy","id":"https://metadata.un.org/sdg/7"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"We":[0,87,163],"present":[1],"AquaGen,":[2],"the":[3,16,23,68,89,169,189,210],"first":[4],"all-atom,":[5],"explicit":[6],"solvent,":[7],"periodic-boundary-condition-aware":[8],"generative":[9,35],"model":[10,156],"that":[11,37,165],"produces":[12],"molecular":[13,26],"configurations":[14],"from":[15,116,147],"Boltzmann":[17,118],"distribution":[18],"at":[19,52],"a":[20,74],"fraction":[21],"of":[22,25,40,70,80,91,171,191,212],"cost":[24],"dynamics":[27],"(MD).":[28],"This":[29],"is":[30],"in":[31,73,185],"contrast":[32],"with":[33,105,129,179],"existing":[34],"models":[36],"remove":[38],"degrees":[39],"freedom":[41],"by":[42,154],"operating":[43],"on":[44,94],"coarse-grained,":[45],"vacuum,":[46],"or":[47,195],"implicit":[48],"solvent":[49],"systems.":[50],"Operating":[51],"this":[53,92,166],"resolution":[54],"allows":[55],"for":[56,175,209],"post-processing":[57],"through":[58],"force":[59],"field":[60],"energy":[61,82,98,177,199],"evaluations":[62,83],"and":[63,66,104,125,150,158,204,215],"MD":[64,184],"simulations,":[65],"enables":[67],"prediction":[69,190],"relevant":[71],"properties":[72],"gray-box":[75],"manner":[76],"(as":[77],"ensemble":[78,127,173],"averages":[79],"potential":[81,181],"over":[84],"generated":[85],"samples).":[86],"demonstrate":[88],"utility":[90,170],"paradigm":[93],"absolute":[95,196],"hydration":[96],"free":[97,176,198],"(AHFE),":[99],"producing":[100],"estimates":[101],"4-10x":[102],"faster":[103],"comparable":[106],"accuracy":[107],"to":[108,182],"standard":[109],"GPU-based":[110],"MD.":[111],"By":[112],"generating":[113,159],"uncorrelated":[114],"samples":[115],"alchemical":[117],"distributions,":[119],"we":[120],"create":[121],"more":[122,160],"accurate,":[123],"interpretable,":[124],"refinable":[126],"predictions":[128],"calibrated":[130],"uncertainty":[131],"estimates,":[132],"unlike":[133],"regression":[134],"methods":[135],"which":[136],"are":[137],"entirely":[138],"black-box":[139],"predictors.":[140],"Our":[141],"approach":[142,167],"also":[143],"yields":[144],"predictable":[145],"benefits":[146],"increasing":[148],"train-":[149],"test-time":[151],"compute,":[152],"realized":[153],"scaling":[155],"size":[157],"samples,":[161],"respectively.":[162],"believe":[164],"demonstrates":[168],"high-resolution":[172],"generation":[174],"estimation,":[178],"future":[180],"replace":[183],"tasks":[186],"such":[187],"as":[188],"lipophilicity,":[192],"membrane":[193],"permeability,":[194],"binding":[197],"(ABFE)":[200],"--":[201],"whose":[202],"grounding":[203],"interpretability":[205],"may":[206],"be":[207],"critical":[208],"development":[211],"new":[213],"drugs":[214],"materials.":[216]},"counts_by_year":[],"updated_date":"2026-07-28T07:46:37.118299","created_date":"2026-07-08T00:00:00"}