@netzschleuder@social.skewed.dedblp_cite: DBLP citations (2014)
Citations among papers contained in the DBLP computer science bibliography. If a paper i cites a paper j also in this data set, then a directed edge connects i to j. (Papers not in the data set are excluded.) Self-loops may be present. This snapshot from May 2014.
This network has 12590 nodes and 49759 edges.
Tags: Informational, Citation, Unweighted
@berlinbuzzwords@floss.socialThinking about attending Berlin Buzzwords? Don't miss out! #bbuzz provides many resources and perks, especially for newcomers in data science, AI, and search.
Find out why and register for June 7-9: https://2026.berlinbuzzwords.de/join-bbuzz-rhd/
@seeingwithsound@mas.toGuardian: Face transplants promised hope. Patients were put through the unthinkable https://www.theguardian.com/science/2025/nov/27/face-transplant-patients-results-outcomes "negative data is often buried, driven by funding battles and inst…
@netzschleuder@social.skewed.defaculty_hiring: Faculty hiring networks (Comp. Sci., Business, History)
Three networks of faculty hiring in Computer Science Departments, Business Schools, and History Departments. Each node is a PhD-granting institution in the respective field, and a directed edge (i,j) indicates that a person received their PhD from node i and was tenure-track faculty at node j during time of collection (2011-2013). All data collected from faculty public rosters at the sampled institutions.
Thi…
@Dragofix@veganism.socialJapanese nuclear plant operator fabricated seismic risk data https://arstechnica.com/science/2026/01/japanese-nuclear-plant-operator-fabricated-seismic-risk-data/
@netzschleuder@social.skewed.defaculty_hiring: Faculty hiring networks (Comp. Sci., Business, History)
Three networks of faculty hiring in Computer Science Departments, Business Schools, and History Departments. Each node is a PhD-granting institution in the respective field, and a directed edge (i,j) indicates that a person received their PhD from node i and was tenure-track faculty at node j during time of collection (2011-2013). All data collected from faculty public rosters at the sampled institutions.
Thi…
@jlpiraux@wallonie-bruxelles.social98 % des arbres fruitiers et oliviers de Gaza ont été détruits. 90 % des serres sont endommagées et 75 % détruites, selon une analyse des images satellitaires.
https://www.zmescience.com/science/news-sc
@metacurity@infosec.exchangehttps://europeanspaceflight.com/esa-says-data-breach-was-limited-to-servers-with-unclassified-documents/
The European Space Agency (ESA) has released an initial statement regarding an alleged data breach, stating that it aff…
@lysander07@sigmoid.socialKeynote by Roger H. French on Semantic Data Management and MDS-Onto for Synchrotron Science at the #SeMatS2025 workshop #ISWC2025 presenting a vast amount of Materials Data Science-related research. Amongst others, the Materials Data Science Ontology (MDS-Onto), which builds upon PMDco, CCO, and B…
@nohillside@smnn.ch
@cdarwin@c.im#SciX makes research more efficient by linking data, code, and publications, so findings can be tested, trusted, and built on faster. More reproducible science, less wasted effort, more discoveries. #OpenScience #ResearchIntegrity
@ErikJonker@mastodon.socialInteressant om door de projecten heen te browsen die funding hebben ontvangen.
https://www.openscience.nl/en/news/45-projects-strengthen-dutch-open-science-infrastructure
@carlos@perceptiveconstructs.com @carlos@social.perceptiveconstructs.com
@cosmos4u@scicomm.xyzRE: #Mauve is but one of 140 (!) small satellites on that Falcon 9, collectively known as Transporter 15. What's interesting about the satellite is its commercial approach - you *buy* astronomical UV data: https://bssl.space/mauve/ and https://space.blog.gov.uk/2025/11/06/blue-skies-space-to-launch-mauve-satellite-demonstrating-a-new-model-for-delivering-space-science-data/ and https://www.science.org/content/article/startup-pioneers-subscription-service-space-based-astronomy
@datascience@genomic.socialTidyX: screencasts explaining different aspects of the R language and the coding process. #rstats
@cdarwin@c.im
@KlausBulle@nfdi.socialDas #bpkFotoarchiv der @… erprobt seit 2024 #KI-gestützte Erschließungsmethoden, um seine mehr als 12 Millionen Bildmotive besser zugänglich und nutzbar zu machen.
Ste…
@mszll@datasci.socialVery cool paper out by our collaborator Chris Larkin (et al): Identification of plausible low traffic neighbourhoods using open data
https://www.sciencedirect.com/science/article/pii/S2950105925000415
Code:
@lukascbossert@mastodon.socialHow nice @… made it into #researchdatamanagement. Also #Coscine (developed at
@ruth_mottram@fediscience.orgI have been intermittently sick, and working on a grant proposal and doing household stuff with the family all week. It's not the best recipe for a relaxing week on holiday. So now I'm going to do some fun stuff. Saturday morning science - which means looking at pretty data and reading new papers and editing student's paper.
... And wondering where I went so wrong that I have to do the actual science in my free time rather than at the office
@arXiv_csGL_bot@mastoxiv.pageCrosslisted article(s) found for cs.GL. https://arxiv.org/list/cs.GL/new
[1/1]:
- Kaggle Chronicles: 15 Years of Competitions, Community and Data Science Innovation
Kevin B\"onisch, Leandro Losaria
@losttourist@social.chatty.monsterI found these in the supermarket the other week and in the interests of science decided to personally be a guinea pig for them. The sacrifices I make.
Anyway imagine a Ferrero Rocher but instead of being rolled up into a ball it's a long thin stick. Yes. Put that in your pipe and smoke it, Mr spoiled ambassador.
I may of course have not quite tasted them correctly, and seeing as science always needs more data points I expect I'll be going out to buy and eat a few more of these.
#KitKat #chocolate #snack
@cosmos4u@scicomm.xyzTEMPO at Night: #ALAN
@netzschleuder@social.skewed.decora: CORA citations (1998)
Citations among papers indexed by CORA, from 1998, an early computer science research paper search engine. If a paper i cites a paper j also in this data set, then a directed edge connects i to j. (Papers not in the data set are excluded.) Self-loops may be present. The dates of these snapshots are uncertain.
This network has 23166 nodes and 91500 edges.
Tags: Informational, Citation, Unweighted
@blakes7bot@mas.torpidity.netSeries D, Episode 03 - Traitor
QUUTE: A one in a thousand chance, General. The operator happened to pick it up while running a routine line-scan.
GENERAL: And what was this data it was taking from the terminal?
https://blake.torpidity.net/m/403/316 B7B3
@Dragofix@veganism.socialWe've done the science—let's get on with climate action #climate
@HeidiSeibold@fosstodon.orgOh the irony...
@geant@mstdn.social📣 The call for nominations for the Sarah Jones Award 2026 is now open!
What is it?
‘The Sarah Jones Award for exceptional contribution to fostering collaboration in #OpenScience’ was established by the Research Data Alliance (RDA) in June 2024. This bi-annual award honours the memory of our dear colleague Sarah Jones, and her significant contributions to the global open science commu…
@netzschleuder@social.skewed.dedblp_cite: DBLP citations (2014)
Citations among papers contained in the DBLP computer science bibliography. If a paper i cites a paper j also in this data set, then a directed edge connects i to j. (Papers not in the data set are excluded.) Self-loops may be present. This snapshot from May 2014.
This network has 12590 nodes and 49759 edges.
Tags: Informational, Citation, Unweighted
@stf@chaos.socialby accident i stumbled on this review by the #NSA on Bruce Schneiers "Applied Crypto" book from long ago.
![9. BOOK REVIEW: APPLIED CRYPTOGRAPHY [censored] Reviewer
Applied Cryptography, for those who don't read the internet news, is a
book written by Bruce Schneier last year. According to the jacket,
Schneier is a data security expert with a master's degree in computer
science. According to his followers, he is a hero who has finally
brought together the loose threads of cryptography for the general
public to understand. Schneier has gathered academic research, internet
gossip, and everything he co…](https://assets.chaos.social/media_attachments/files/115/617/078/445/675/386/original/56a3f192560809fc.png)
@UP8@mastodon.social👨🏿🌾 Traces of old farm chemicals contaminate water across the US
#chemicals
@arXiv_csLG_bot@mastoxiv.pageReplaced article(s) found for cs.LG. https://arxiv.org/list/cs.LG/new
[1/5]:
- Feed Two Birds with One Scone: Exploiting Wild Data for Both Out-of-Distribution Generalization a...
Haoyue Bai, Gregory Canal, Xuefeng Du, Jeongyeol Kwon, Robert Nowak, Yixuan Li
https://arxiv.org/abs/2306.09158
- Sparse, Efficient and Explainable Data Attribution with DualXDA
Galip \"Umit Yolcu, Moritz Weckbecker, Thomas Wiegand, Wojciech Samek, Sebastian Lapuschkin
https://arxiv.org/abs/2402.12118 https://mastoxiv.page/@arXiv_csLG_bot/111962593972369958
- HGQ: High Granularity Quantization for Real-time Neural Networks on FPGAs
Sun, Que, {\AA}rrestad, Loncar, Ngadiuba, Luk, Spiropulu
https://arxiv.org/abs/2405.00645 https://mastoxiv.page/@arXiv_csLG_bot/112370274737558603
- On the Identification of Temporally Causal Representation with Instantaneous Dependence
Li, Shen, Zheng, Cai, Song, Gong, Chen, Zhang
https://arxiv.org/abs/2405.15325 https://mastoxiv.page/@arXiv_csLG_bot/112511890051553111
- Basis Selection: Low-Rank Decomposition of Pretrained Large Language Models for Target Applications
Yang Li, Daniel Agyei Asante, Changsheng Zhao, Ernie Chang, Yangyang Shi, Vikas Chandra
https://arxiv.org/abs/2405.15877 https://mastoxiv.page/@arXiv_csLG_bot/112517547424098076
- Privacy Bias in Language Models: A Contextual Integrity-based Auditing Metric
Yan Shvartzshnaider, Vasisht Duddu
https://arxiv.org/abs/2409.03735 https://mastoxiv.page/@arXiv_csLG_bot/113089789682783135
- Low-Rank Filtering and Smoothing for Sequential Deep Learning
Joanna Sliwa, Frank Schneider, Nathanael Bosch, Agustinus Kristiadi, Philipp Hennig
https://arxiv.org/abs/2410.06800 https://mastoxiv.page/@arXiv_csLG_bot/113283021321510736
- Hierarchical Multimodal LLMs with Semantic Space Alignment for Enhanced Time Series Classification
Xiaoyu Tao, Tingyue Pan, Mingyue Cheng, Yucong Luo, Qi Liu, Enhong Chen
https://arxiv.org/abs/2410.18686 https://mastoxiv.page/@arXiv_csLG_bot/113367101100828901
- Fairness via Independence: A (Conditional) Distance Covariance Framework
Ruifan Huang, Haixia Liu
https://arxiv.org/abs/2412.00720 https://mastoxiv.page/@arXiv_csLG_bot/113587817648503815
- Data for Mathematical Copilots: Better Ways of Presenting Proofs for Machine Learning
Simon Frieder, et al.
https://arxiv.org/abs/2412.15184 https://mastoxiv.page/@arXiv_csLG_bot/113683924322164777
- Pairwise Elimination with Instance-Dependent Guarantees for Bandits with Cost Subsidy
Ishank Juneja, Carlee Joe-Wong, Osman Ya\u{g}an
https://arxiv.org/abs/2501.10290 https://mastoxiv.page/@arXiv_csLG_bot/113859392622871057
- Towards Human-Guided, Data-Centric LLM Co-Pilots
Evgeny Saveliev, Jiashuo Liu, Nabeel Seedat, Anders Boyd, Mihaela van der Schaar
https://arxiv.org/abs/2501.10321 https://mastoxiv.page/@arXiv_csLG_bot/113859392688054204
- Regularized Langevin Dynamics for Combinatorial Optimization
Shengyu Feng, Yiming Yang
https://arxiv.org/abs/2502.00277
- Generating Samples to Probe Trained Models
Eren Mehmet K{\i}ral, Nur\c{s}en Ayd{\i}n, \c{S}. \.Ilker Birbil
https://arxiv.org/abs/2502.06658 https://mastoxiv.page/@arXiv_csLG_bot/113984059089245671
- On Agnostic PAC Learning in the Small Error Regime
Julian Asilis, Mikael M{\o}ller H{\o}gsgaard, Grigoris Velegkas
https://arxiv.org/abs/2502.09496 https://mastoxiv.page/@arXiv_csLG_bot/114000974082372598
- Preconditioned Inexact Stochastic ADMM for Deep Model
Shenglong Zhou, Ouya Wang, Ziyan Luo, Yongxu Zhu, Geoffrey Ye Li
https://arxiv.org/abs/2502.10784 https://mastoxiv.page/@arXiv_csLG_bot/114023667639951005
- On the Effect of Sampling Diversity in Scaling LLM Inference
Wang, Liu, Chen, Light, Liu, Chen, Zhang, Cheng
https://arxiv.org/abs/2502.11027 https://mastoxiv.page/@arXiv_csLG_bot/114023688225233656
- How to use score-based diffusion in earth system science: A satellite nowcasting example
Randy J. Chase, Katherine Haynes, Lander Ver Hoef, Imme Ebert-Uphoff
https://arxiv.org/abs/2505.10432 https://mastoxiv.page/@arXiv_csLG_bot/114516300594057680
- PEAR: Equal Area Weather Forecasting on the Sphere
Hampus Linander, Christoffer Petersson, Daniel Persson, Jan E. Gerken
https://arxiv.org/abs/2505.17720 https://mastoxiv.page/@arXiv_csLG_bot/114572963019603744
- Train Sparse Autoencoders Efficiently by Utilizing Features Correlation
Vadim Kurochkin, Yaroslav Aksenov, Daniil Laptev, Daniil Gavrilov, Nikita Balagansky
https://arxiv.org/abs/2505.22255 https://mastoxiv.page/@arXiv_csLG_bot/114589956040892075
- A Certified Unlearning Approach without Access to Source Data
Umit Yigit Basaran, Sk Miraj Ahmed, Amit Roy-Chowdhury, Basak Guler
https://arxiv.org/abs/2506.06486 https://mastoxiv.page/@arXiv_csLG_bot/114658421178857085
toXiv_bot_toot
@berlinbuzzwords@floss.socialNew year, new opportunities – become a speaker at this year's Berlin Buzzwords on 7-9 June and share your projects, insights, and ideas!
We are looking for talks on search, data science, operations, store, scale, people and community, and much more. Visit our website to find out more and submit your proposal!
Call for Papers: https://2026.berlinbuzzwords.de/call-for-papers/
@cdarwin@c.imClimate scientists and meteorologists
are sounding the alarm
after White House budget director Russell Vought announced
the Trump administration will
❌break up the National Center for Atmospheric Research in Boulder, Colorado, known as NCAR.
“He is executing the playbook of Project 2025,” says Michael Mann,
scientist and co-author of
"Science Under Siege".
Without NCAR, “we will not have the sorts of observational data and climate m…
@netzschleuder@social.skewed.defaculty_hiring: Faculty hiring networks (Comp. Sci., Business, History)
Three networks of faculty hiring in Computer Science Departments, Business Schools, and History Departments. Each node is a PhD-granting institution in the respective field, and a directed edge (i,j) indicates that a person received their PhD from node i and was tenure-track faculty at node j during time of collection (2011-2013). All data collected from faculty public rosters at the sampled institutions.
Thi…
@netzschleuder@social.skewed.decs_department: Aarhus Computer Science department relationships
Multiplex network consisting of 5 edge types corresponding to online and offline relationships (Facebook, leisure, work, co-authorship, lunch) between employees of the Computer Science department at Aarhus. Data hosted by Manlio De Domenico.
This network has 61 nodes and 620 edges.
Tags: Social, Relationships, Multilayer, Unweighted
@cosmos4u@scicomm.xyzThere is also a #PUNCH video showing only #comet #Lemmon and its tails in https://science.nasa.gov/blogs/punch/2025/12/19/nasas-punch-spies-comet-lemmon/ - unfortunately too faint so much tail structure gets lost which can be glimpsed in the full video. But the data are there, waiting for someone to process them for science.
@netzschleuder@social.skewed.defaculty_hiring: Faculty hiring networks (Comp. Sci., Business, History)
Three networks of faculty hiring in Computer Science Departments, Business Schools, and History Departments. Each node is a PhD-granting institution in the respective field, and a directed edge (i,j) indicates that a person received their PhD from node i and was tenure-track faculty at node j during time of collection (2011-2013). All data collected from faculty public rosters at the sampled institutions.
Thi…
@cdarwin@c.imWhat the White House is calling the
"Genesis Mission" is to speed research and scientific discovery
by analyzing massive science, engineering, energy and health care data sets in the federal government, university and private sector
with supercomputing technology.
It's an AI initiative the White House hopes will result in quicker breakthroughs in areas of research including disease therapies.
Michael Krastios, science adviser to the president, t…
@netzschleuder@social.skewed.decora: CORA citations (1998)
Citations among papers indexed by CORA, from 1998, an early computer science research paper search engine. If a paper i cites a paper j also in this data set, then a directed edge connects i to j. (Papers not in the data set are excluded.) Self-loops may be present. The dates of these snapshots are uncertain.
This network has 23166 nodes and 91500 edges.
Tags: Informational, Citation, Unweighted
@netzschleuder@social.skewed.decs_department: Aarhus Computer Science department relationships
Multiplex network consisting of 5 edge types corresponding to online and offline relationships (Facebook, leisure, work, co-authorship, lunch) between employees of the Computer Science department at Aarhus. Data hosted by Manlio De Domenico.
This network has 61 nodes and 620 edges.
Tags: Social, Relationships, Multilayer, Unweighted
@netzschleuder@social.skewed.desp_infectious: Art exhibit dynamic contacts (2011)
This dataset contains the daily dynamic contact networks collected during the Infectious SocioPatterns event that took place at the Science Gallery in Dublin, Ireland, during the artscience exhibition INFECTIOUS: STAY AWAY. Each file in the downloadable package contains a tab-separated list representing the active contacts during 20-second intervals of one day of data collection. Each line has the form “t i j“, where i and j are the a…
@berlinbuzzwords@floss.socialWhat is #bbuzz all about?
Our video team captured the essence of #bbuzz on film: #bbuzz by joining us as a speaker! We are looking for talks on search, data science, streams, operations, scale, storage, people and community, society, ethics, sustainability, and more: https://2026.berlinbuzzwords.de/call-for-papers/
@netzschleuder@social.skewed.dedblp_cite: DBLP citations (2014)
Citations among papers contained in the DBLP computer science bibliography. If a paper i cites a paper j also in this data set, then a directed edge connects i to j. (Papers not in the data set are excluded.) Self-loops may be present. This snapshot from May 2014.
This network has 12590 nodes and 49759 edges.
Tags: Informational, Citation, Unweighted
@netzschleuder@social.skewed.decs_department: Aarhus Computer Science department relationships
Multiplex network consisting of 5 edge types corresponding to online and offline relationships (Facebook, leisure, work, co-authorship, lunch) between employees of the Computer Science department at Aarhus. Data hosted by Manlio De Domenico.
This network has 61 nodes and 620 edges.
Tags: Social, Relationships, Multilayer, Unweighted
@cdarwin@c.imThe offices at John Quackenbush’s lab at the Harvard T.H. Chan School of Public Health
were once full of postdoctoral fellows, graduate students, and interns.
Young scientists here worked on some of the most cutting-edge computational biology research in the world,
driving new discoveries and the creation of widely used big data tools, including one the National Cancer Institute named among the most important advances of 2024.
Today, the offices are rows of empty comp…
@arXiv_csLG_bot@mastoxiv.pageReplaced article(s) found for cs.LG. https://arxiv.org/list/cs.LG/new
[4/5]:
- Sample, Don't Search: Rethinking Test-Time Alignment for Language Models
Gon\c{c}alo Faria, Noah A. Smith
https://arxiv.org/abs/2504.03790 https://mastoxiv.page/@arXiv_csCL_bot/114301112970577326
- A Survey on Archetypal Analysis
Aleix Alcacer, Irene Epifanio, Sebastian Mair, Morten M{\o}rup
https://arxiv.org/abs/2504.12392 https://mastoxiv.page/@arXiv_statME_bot/114357826909813483
- The Stochastic Occupation Kernel (SOCK) Method for Learning Stochastic Differential Equations
Michael L. Wells, Kamel Lahouel, Bruno Jedynak
https://arxiv.org/abs/2505.11622 https://mastoxiv.page/@arXiv_statML_bot/114539065460187982
- BOLT: Block-Orthonormal Lanczos for Trace estimation of matrix functions
Kingsley Yeon, Promit Ghosal, Mihai Anitescu
https://arxiv.org/abs/2505.12289 https://mastoxiv.page/@arXiv_mathNA_bot/114539035462135281
- Clustering and Pruning in Causal Data Fusion
Otto Tabell, Santtu Tikka, Juha Karvanen
https://arxiv.org/abs/2505.15215 https://mastoxiv.page/@arXiv_statML_bot/114550346291754635
- On the performance of multi-fidelity and reduced-dimensional neural emulators for inference of ph...
Chloe H. Choi, Andrea Zanoni, Daniele E. Schiavazzi, Alison L. Marsden
https://arxiv.org/abs/2506.11683 https://mastoxiv.page/@arXiv_statML_bot/114692410563481289
- Beyond Force Metrics: Pre-Training MLFFs for Stable MD Simulations
Maheshwari, Tang, Ock, Kolluru, Farimani, Kitchin
https://arxiv.org/abs/2506.14850 https://mastoxiv.page/@arXiv_physicschemph_bot/114709402590755731
- Quantifying Uncertainty in the Presence of Distribution Shifts
Yuli Slavutsky, David M. Blei
https://arxiv.org/abs/2506.18283 https://mastoxiv.page/@arXiv_statML_bot/114738165218533987
- ZKPROV: A Zero-Knowledge Approach to Dataset Provenance for Large Language Models
Mina Namazi, Alexander Nemecek, Erman Ayday
https://arxiv.org/abs/2506.20915 https://mastoxiv.page/@arXiv_csCR_bot/114754394485208892
- SpecCLIP: Aligning and Translating Spectroscopic Measurements for Stars
Zhao, Huang, Xue, Kong, Liu, Tang, Beers, Ting, Luo
https://arxiv.org/abs/2507.01939 https://mastoxiv.page/@arXiv_astrophIM_bot/114788369702591337
- Towards Facilitated Fairness Assessment of AI-based Skin Lesion Classifiers Through GenAI-based I...
Ko Watanabe, Stanislav Frolov, Aya Hassan, David Dembinsky, Adriano Lucieri, Andreas Dengel
https://arxiv.org/abs/2507.17860 https://mastoxiv.page/@arXiv_csCV_bot/114912976717523345
- PASS: Probabilistic Agentic Supernet Sampling for Interpretable and Adaptive Chest X-Ray Reasoning
Yushi Feng, Junye Du, Yingying Hong, Qifan Wang, Lequan Yu
https://arxiv.org/abs/2508.10501 https://mastoxiv.page/@arXiv_csAI_bot/115032101532614110
- Unified Acoustic Representations for Screening Neurological and Respiratory Pathologies from Voice
Ran Piao, Yuan Lu, Hareld Kemps, Tong Xia, Aaqib Saeed
https://arxiv.org/abs/2508.20717 https://mastoxiv.page/@arXiv_csSD_bot/115111255835875066
- Machine Learning-Driven Predictive Resource Management in Complex Science Workflows
Tasnuva Chowdhury, et al.
https://arxiv.org/abs/2509.11512 https://mastoxiv.page/@arXiv_csDC_bot/115213444524490263
- MatchFixAgent: Language-Agnostic Autonomous Repository-Level Code Translation Validation and Repair
Ali Reza Ibrahimzada, Brandon Paulsen, Reyhaneh Jabbarvand, Joey Dodds, Daniel Kroening
https://arxiv.org/abs/2509.16187 https://mastoxiv.page/@arXiv_csSE_bot/115247172280557686
- Automated Machine Learning Pipeline: Large Language Models-Assisted Automated Dataset Generation ...
Adam Lahouari, Jutta Rogal, Mark E. Tuckerman
https://arxiv.org/abs/2509.21647 https://mastoxiv.page/@arXiv_condmatmtrlsci_bot/115286737423175311
- Quantifying the Impact of Structured Output Format on Large Language Models through Causal Inference
Han Yuan, Yue Zhao, Li Zhang, Wuqiong Luo, Zheng Ma
https://arxiv.org/abs/2509.21791 https://mastoxiv.page/@arXiv_csCL_bot/115287166674809413
- The Generation Phases of Flow Matching: a Denoising Perspective
Anne Gagneux, S\'egol\`ene Martin, R\'emi Gribonval, Mathurin Massias
https://arxiv.org/abs/2510.24830 https://mastoxiv.page/@arXiv_csCV_bot/115462527449411627
- Data-driven uncertainty-aware seakeeping prediction of the Delft 372 catamaran using ensemble Han...
Giorgio Palma, Andrea Serani, Matteo Diez
https://arxiv.org/abs/2511.04461 https://mastoxiv.page/@arXiv_eessSY_bot/115507785247809767
- Generalized infinite dimensional Alpha-Procrustes based geometries
Salvish Goomanee, Andi Han, Pratik Jawanpuria, Bamdev Mishra
https://arxiv.org/abs/2511.09801 https://mastoxiv.page/@arXiv_statML_bot/115547135711272091
toXiv_bot_toot
@netzschleuder@social.skewed.decora: CORA citations (1998)
Citations among papers indexed by CORA, from 1998, an early computer science research paper search engine. If a paper i cites a paper j also in this data set, then a directed edge connects i to j. (Papers not in the data set are excluded.) Self-loops may be present. The dates of these snapshots are uncertain.
This network has 23166 nodes and 91500 edges.
Tags: Informational, Citation, Unweighted
@netzschleuder@social.skewed.decs_department: Aarhus Computer Science department relationships
Multiplex network consisting of 5 edge types corresponding to online and offline relationships (Facebook, leisure, work, co-authorship, lunch) between employees of the Computer Science department at Aarhus. Data hosted by Manlio De Domenico.
This network has 61 nodes and 620 edges.
Tags: Social, Relationships, Multilayer, Unweighted
@netzschleuder@social.skewed.desp_infectious: Art exhibit dynamic contacts (2011)
This dataset contains the daily dynamic contact networks collected during the Infectious SocioPatterns event that took place at the Science Gallery in Dublin, Ireland, during the artscience exhibition INFECTIOUS: STAY AWAY. Each file in the downloadable package contains a tab-separated list representing the active contacts during 20-second intervals of one day of data collection. Each line has the form “t i j“, where i and j are the a…
@netzschleuder@social.skewed.decora: CORA citations (1998)
Citations among papers indexed by CORA, from 1998, an early computer science research paper search engine. If a paper i cites a paper j also in this data set, then a directed edge connects i to j. (Papers not in the data set are excluded.) Self-loops may be present. The dates of these snapshots are uncertain.
This network has 23166 nodes and 91500 edges.
Tags: Informational, Citation, Unweighted
@netzschleuder@social.skewed.decora: CORA citations (1998)
Citations among papers indexed by CORA, from 1998, an early computer science research paper search engine. If a paper i cites a paper j also in this data set, then a directed edge connects i to j. (Papers not in the data set are excluded.) Self-loops may be present. The dates of these snapshots are uncertain.
This network has 23166 nodes and 91500 edges.
Tags: Informational, Citation, Unweighted
@netzschleuder@social.skewed.desp_infectious: Art exhibit dynamic contacts (2011)
This dataset contains the daily dynamic contact networks collected during the Infectious SocioPatterns event that took place at the Science Gallery in Dublin, Ireland, during the artscience exhibition INFECTIOUS: STAY AWAY. Each file in the downloadable package contains a tab-separated list representing the active contacts during 20-second intervals of one day of data collection. Each line has the form “t i j“, where i and j are the a…
@netzschleuder@social.skewed.desp_infectious: Art exhibit dynamic contacts (2011)
This dataset contains the daily dynamic contact networks collected during the Infectious SocioPatterns event that took place at the Science Gallery in Dublin, Ireland, during the artscience exhibition INFECTIOUS: STAY AWAY. Each file in the downloadable package contains a tab-separated list representing the active contacts during 20-second intervals of one day of data collection. Each line has the form “t i j“, where i and j are the a…
@netzschleuder@social.skewed.defaculty_hiring: Faculty hiring networks (Comp. Sci., Business, History)
Three networks of faculty hiring in Computer Science Departments, Business Schools, and History Departments. Each node is a PhD-granting institution in the respective field, and a directed edge (i,j) indicates that a person received their PhD from node i and was tenure-track faculty at node j during time of collection (2011-2013). All data collected from faculty public rosters at the sampled institutions.
Thi…
@netzschleuder@social.skewed.decora: CORA citations (1998)
Citations among papers indexed by CORA, from 1998, an early computer science research paper search engine. If a paper i cites a paper j also in this data set, then a directed edge connects i to j. (Papers not in the data set are excluded.) Self-loops may be present. The dates of these snapshots are uncertain.
This network has 23166 nodes and 91500 edges.
Tags: Informational, Citation, Unweighted
@netzschleuder@social.skewed.defaculty_hiring: Faculty hiring networks (Comp. Sci., Business, History)
Three networks of faculty hiring in Computer Science Departments, Business Schools, and History Departments. Each node is a PhD-granting institution in the respective field, and a directed edge (i,j) indicates that a person received their PhD from node i and was tenure-track faculty at node j during time of collection (2011-2013). All data collected from faculty public rosters at the sampled institutions.
Thi…
@netzschleuder@social.skewed.decs_department: Aarhus Computer Science department relationships
Multiplex network consisting of 5 edge types corresponding to online and offline relationships (Facebook, leisure, work, co-authorship, lunch) between employees of the Computer Science department at Aarhus. Data hosted by Manlio De Domenico.
This network has 61 nodes and 620 edges.
Tags: Social, Relationships, Multilayer, Unweighted
@netzschleuder@social.skewed.decs_department: Aarhus Computer Science department relationships
Multiplex network consisting of 5 edge types corresponding to online and offline relationships (Facebook, leisure, work, co-authorship, lunch) between employees of the Computer Science department at Aarhus. Data hosted by Manlio De Domenico.
This network has 61 nodes and 620 edges.
Tags: Social, Relationships, Multilayer, Unweighted
@netzschleuder@social.skewed.decora: CORA citations (1998)
Citations among papers indexed by CORA, from 1998, an early computer science research paper search engine. If a paper i cites a paper j also in this data set, then a directed edge connects i to j. (Papers not in the data set are excluded.) Self-loops may be present. The dates of these snapshots are uncertain.
This network has 23166 nodes and 91500 edges.
Tags: Informational, Citation, Unweighted
@netzschleuder@social.skewed.defaculty_hiring: Faculty hiring networks (Comp. Sci., Business, History)
Three networks of faculty hiring in Computer Science Departments, Business Schools, and History Departments. Each node is a PhD-granting institution in the respective field, and a directed edge (i,j) indicates that a person received their PhD from node i and was tenure-track faculty at node j during time of collection (2011-2013). All data collected from faculty public rosters at the sampled institutions.
Thi…
@netzschleuder@social.skewed.defaculty_hiring: Faculty hiring networks (Comp. Sci., Business, History)
Three networks of faculty hiring in Computer Science Departments, Business Schools, and History Departments. Each node is a PhD-granting institution in the respective field, and a directed edge (i,j) indicates that a person received their PhD from node i and was tenure-track faculty at node j during time of collection (2011-2013). All data collected from faculty public rosters at the sampled institutions.
Thi…
@netzschleuder@social.skewed.desp_infectious: Art exhibit dynamic contacts (2011)
This dataset contains the daily dynamic contact networks collected during the Infectious SocioPatterns event that took place at the Science Gallery in Dublin, Ireland, during the artscience exhibition INFECTIOUS: STAY AWAY. Each file in the downloadable package contains a tab-separated list representing the active contacts during 20-second intervals of one day of data collection. Each line has the form “t i j“, where i and j are the a…
