Robert Palovics

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András BenczúrInstitute for Computer Science and ControlEmail verificata su sztaki.hu
Tony Wyss-CorayStanford UniversityEmail verificata su stanford.edu
Fabian Kern, Ph.D.Helmholtz Institute for Pharmaceutical Research SaarlandEmail verificata su helmholtz-hips.de
Andreas KellerProfessor for Clinical Bioinformatics, Center for Bioinformatics, Saarland Informatics CampusEmail verificata su ccb.uni-saarland.de
Jian LuoPAVIR, VA Palo Alto Health Care SystemEmail verificata su stanford.edu
Patricia Morán LosadaPostdoc at Stanford School of MedicineEmail verificata su stanford.edu
Erzsébet FrigóSZTAKIEmail verificata su sztaki.hu
Andrew Chris YangUCSFEmail verificata su ucsf.edu
Nicholas SchaumUniversity of CambridgeEmail verificata su vt.edu
Kruti CalcuttawalaResearch Professional, Stanford UniversityEmail verificata su caredx.com
Oliver HahnPrincipal Investigator, Calico Life Sciences LLCEmail verificata su calicolabs.com
Nannan LuStanford UniversityEmail verificata su stanford.edu
Achint KaurPh.D. Student, Northwestern UniversityEmail verificata su northwestern.edu
Benoit LehallierAlkahestEmail verificata su alkahest.com
Ryan T VestPostdoctoral Scholar, Stanford UniversityEmail verificata su stanford.edu
Elizabeth Y. WangUniversity of HawaiiEmail verificata su hawaii.edu
Domokos Miklós KelenEötvös Loránd UniversityEmail verificata su sztaki.mta.hu
David Gate, PhDAssistant Professor, Northwestern UniversityEmail verificata su northwestern.edu
Nathalie KhouryStanford UniversityEmail verificata su med.miami.edu
Davis Park LeeUniversity of San DiegoEmail verificata su ucsd.edu

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Robert Palovics

Instructor, Stanford University

Email verificata su stanford.edu

data mining machine learning single-cell data science


Titolo Ordina per citazioni Ordina per anno Ordina per titolo	Citata da Citata da	Anno
A single cell transcriptomic atlas characterizes aging tissues in the mouse Tabula Muris Consortium Nature 583 (7817), 590, 2020	852	2020
A human brain vascular atlas reveals diverse mediators of Alzheimer’s risk AC Yang, RT Vest, F Kern, DP Lee, M Agam, CA Maat, PM Losada, ... Nature 603 (7903), 885-892, 2022	475	2022
Ageing hallmarks exhibit organ-specific temporal signatures N Schaum, B Lehallier, O Hahn, R Pálovics, S Hosseinzadeh, SE Lee, ... Nature 583 (7817), 596-602, 2020	434	2020
Young CSF restores oligodendrogenesis and memory in aged mice via Fgf17 T Iram, F Kern, A Kaur, S Myneni, AR Morningstar, H Shin, MA Garcia, ... Nature 605 (7910), 509-515, 2022	137	2022
Organ aging signatures in the plasma proteome track health and disease HSH Oh, J Rutledge, D Nachun, R Pálovics, O Abiose, P Moran-Losada, ... Nature 624 (7990), 164-172, 2023	108	2023
Molecular hallmarks of heterochronic parabiosis at single-cell resolution R Pálovics, A Keller, N Schaum, W Tan, T Fehlmann, M Borja, F Kern, ... Nature 603 (7900), 309-314, 2022	81	2022
Exploiting temporal influence in online recommendation R Pálovics, AA Benczúr, L Kocsis, T Kiss, E Frigó Proceedings of the 8th ACM Conference on Recommender systems, 273-280, 2014	73	2014
Recsys challenge 2016: Job recommendations F Abel, A Benczúr, D Kohlsdorf, M Larson, R Pálovics Proceedings of the 10th ACM Conference on Recommender Systems, 425-426, 2016	56	2016
Atlas of the aging mouse brain reveals white matter as vulnerable foci O Hahn, AG Foltz, M Atkins, B Kedir, P Moran-Losada, IH Guldner, ... Cell 186 (19), 4117-4133. e22, 2023	52	2023
Online Machine Learning in Big Data Streams AA Benczúr, L Kocsis, R Pálovics arXiv preprint arXiv:1802.05872, 2018	52	2018
APOE4/4 is linked to damaging lipid droplets in Alzheimer’s disease microglia MS Haney, R Pálovics, CN Munson, C Long, PK Johansson, O Yip, ... Nature 628 (8006), 154-161, 2024	51	2024
Node embeddings in dynamic graphs F Béres, DM Kelen, R Pálovics, AA Benczúr Applied Network Science 4 (1), 64, 2019	41	2019
Temporal influence over the Last. fm social network R Pálovics, AA Benczúr Social Network Analysis and Mining 5 (1), 4, 2015	40	2015
Temporal walk based centrality metric for graph streams F Béres, R Pálovics, A Oláh, AA Benczúr Applied network science 3, 1-26, 2018	30	2018
The murine transcriptome reveals global aging nodes with organ-specific phase and amplitude N Schaum, B Lehallier, O Hahn, S Hosseinzadeh, SE Lee, R Sit, DP Lee, ... bioRxiv, 662254, 2019	19	2019
Location-aware online learning for top-k recommendation R Pálovics, P Szalai, J Pap, E Frigó, L Kocsis, AA Benczúr Pervasive and Mobile Computing 38, 490-504, 2017	19	2017
Temporal prediction of retweet count R Pálovics, B Daróczy, AA Benczúr Cognitive Infocommunications (CogInfoCom), 2013 IEEE 4th International …, 2013	17	2013
Online ranking prediction in non-stationary environments E Frigó, R Pálovics, D Kelen, L Kocsis, A Benczúr CEUR-WS. org, 2017	13	2017
APOE4/4 is linked to damaging lipid droplets in Alzheimer’s microglia MS Haney, R Palovics, CN Munson, C Long, P Johansson, O Yip, ... bioRxiv, 2023	11	2023
Single Cell ADNP Predictive of Human Muscle Disorders: Mouse Knockdown Results in Muscle Wasting O Kapitansky, G Karmon, S Sragovich, A Hadar, M Shahoha, I Jaljuli, ... Cells 9 (10), 2320, 2020	11	2020

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