ev:2017:pdm_program
Differences
This shows you the differences between two versions of the page.
| Both sides previous revision Previous revision Next revision | Previous revision Last revision Both sides next revision | ||
|
ev:2017:pdm_program [2017/10/12 15:08] konstantin |
ev:2017:pdm_program [2017/10/25 22:52] konstantin |
||
|---|---|---|---|
| Line 6: | Line 6: | ||
| ^ time ^ presenting author ^ title ^ | ^ time ^ presenting author ^ title ^ | ||
| - | | 09:00 | Wit, Klemm | Opening, practical info | | + | | //Action Conference// ||| |
| + | | 09:00 | Wit, San Miguel, Klemm| Opening, welcome, practical info | | ||
| | 09:15 | van Duijn | Perceptions in Social Network Analysis: Statistical Modelling of Three-way Data| | | 09:15 | van Duijn | Perceptions in Social Network Analysis: Statistical Modelling of Three-way Data| | ||
| | 09:50 | Tamarit | Emergence of social structure: a generalization of Dunbar's circles | | | 09:50 | Tamarit | Emergence of social structure: a generalization of Dunbar's circles | | ||
| Line 16: | Line 17: | ||
| | 12:35 | Batagelj | The COSTNET website | | | 12:35 | Batagelj | The COSTNET website | | ||
| | 13:00 | lunch break || | | 13:00 | lunch break || | ||
| - | | 14:00 | see below | working group 1: Exploring (massive) network data sets | | + | | // Working Group 1: Exploring (massive) network data sets // ||| |
| - | | 16:00 | coffee break || | + | | 14:00 | Di Serio | Welcome to the session | |
| - | | 16:30 | tba | flash talks advertising posters | | + | | 14:10 | Subelj | Three forms of convexity in graphs and networks| |
| - | | 17:00 | see below | poster session | | + | | 14:30 | Cortes | From multimodal images to connectivity of brain networks in both healthy and pathological conditions| |
| + | | 14:50 | Martincic | The Multilayer Networks for Language| | ||
| + | | 15:10 | Cugmas | The emergence of core-cohesive peripheries blockmodel type| | ||
| + | | 15:30 | Drejerska | Network analysis of commuting flows for delimitation of functional urban areas| | ||
| + | | 15:50 | Chrzanowska | Network Analysis of Commuting Flows in Poland| | ||
| + | | 16:10 | coffee break || | ||
| + | | // Action Conference: Posters // ||| | ||
| + | | 16:40 | see list below | flash talks advertising posters | | ||
| + | | 17:00 | see list below | poster session | | ||
| Line 26: | Line 35: | ||
| ^ time ^ presenting author ^ title ^ | ^ time ^ presenting author ^ title ^ | ||
| - | | 09:00 | Lupparelli | Regression graph models for binary non-independent outcomes | | + | | //Action Conference// ||| |
| - | | 09:35 | Augugliaro | l1-penalized Gaussian graphical model for left-censured data| | + | | 09:00 | Traveset |Improving coextinction models to simulate consequences of pollinator loss on plant communities | |
| + | | 09:35 | Abbruzzo | l1-penalized Gaussian graphical model for left-censured data | | ||
| | 10:00 | Szell | Unveiling untapped potential in cities: From taxi sharing to mobility space inequality | | | 10:00 | Szell | Unveiling untapped potential in cities: From taxi sharing to mobility space inequality | | ||
| | 10:35 | coffee break || | | 10:35 | coffee break || | ||
| - | | 11:00 | see below | working group 2: Network Modelling | | + | | // Working Group 2: Network Modelling // ||| |
| - | | 13:00 | lunch break || | + | | 11:01 | Artime | Ageing and multiplexity in the voter model| |
| - | | 14:00 | see below | working group 3: Network Inference and Prediction | | + | | 11:18 | Engebretsen | How population clustering within a country affects infectious disease spread dynamics| |
| - | | 16:00 | coffee || | + | | 11:35 | Rodriguez | Coinfection in the space: cooperative disease spreading in geometric and contact networks| |
| + | | 11:52 | Behrouzi | Dynamic Chain Graph Models for Time Series Mixed Data| | ||
| + | | 12:09 |Grzegorczyk | Non-homogeneous dynamic Bayesian networks with partially edge-wise coupled interaction parameters| | ||
| + | | 12:26 | Kadilar | On the Graphical Markov Models with an Application| | ||
| + | | 12:43 | Michaud | A stochastic heterogeneous mean-field approximation of agent-based models| | ||
| + | | 13:00 | group photo (outside the lecture hall), then lunch break || | ||
| + | | // Working Group 3: Network Inference and Prediction // ||| | ||
| + | | 14:00 | Elliott | A novel approach to network anomaly detection| | ||
| + | | 14:25 | Jarynowski | What do infection incidences tell us about connectivity of a regional healthcare network?| | ||
| + | | 14:50 | Wit | Network inference in genomics| | ||
| + | | 15:15 | Ranciati | Mixture model under overlapping clusters: an application to network data| | ||
| + | | 15:40 | Nurushev | Local inference by penalization method for biclustering model| | ||
| + | | 16:05 | coffee || | ||
| + | | 16:15 | bus departure for old town of Palma || | ||
| ==== Friday (Oct 27) ==== | ==== Friday (Oct 27) ==== | ||
| ^ time ^ presenting author ^ title ^ | ^ time ^ presenting author ^ title ^ | ||
| - | | 09:00 | Traveset |Improving coextinction models to simulate consequences of pollinator loss on plant communities | | + | | 09:00 | Lupparelli | Graphical models for sequences of non-independent regressions | |
| | 09:35 | Ibañez-Marcelo | When shape matters: Brain networks studied under a persistent homology view| | | 09:35 | Ibañez-Marcelo | When shape matters: Brain networks studied under a persistent homology view| | ||
| | 10:00 | Fernandez-Gracia | Gromov-Wasserstein distance of complex networks| | | 10:00 | Fernandez-Gracia | Gromov-Wasserstein distance of complex networks| | ||
| | 10:25 | Batagelj | Describing network evolution using probabilistic inductive classes| | | 10:25 | Batagelj | Describing network evolution using probabilistic inductive classes| | ||
| - | | 10:35 | coffee break || | + | | 10:50 | coffee break || |
| - | | 11:05 | Rancoita | Bayesian networks for data imputation in survival tree analysis| | + | | 11:20 | Rancoita | Bayesian networks for data imputation in survival tree analysis| |
| - | | 11:30 | Signorelli |How to integrate gene enrichment analysis with information from gene interaction networks| | + | | 11:45 | Signorelli |How to integrate gene enrichment analysis with information from gene interaction networks| |
| - | | 11:55 | Stadler | Gene Trees, Species Trees, Reconciliation Maps, and Phylogenenies| | + | | 12:10 | Stadler | Gene Trees, Species Trees, Reconciliation Maps, and Phylogenenies| |
| - | | 12:30 | closing, lunch || | + | | 12:45 | closing, lunch || |
| - | ==== Meeting of working group 1: Exploring (massive) network data sets ==== | + | ==== COSTNET action conference: posters and flash talks ==== |
| - | + | ||
| - | ^ presenting author ^ title ^ | + | |
| - | |Chrzanowska | Network Analysis of Commuting Flows in Poland| | + | |
| - | |Cortes | From multimodal images to connectivity of brain networks in both healthy and pathological conditions| | + | |
| - | |Cugmas | The emergence of core-cohesive peripheries blockmodel type| | + | |
| - | |Drejerska | Network analysis of commuting flows for delimitation of functional urban areas| | + | |
| - | |Fierascu | Corruption Networks in Post-Communist Countries. The Case of State Capture in Hungary| | + | |
| - | |Martincic | The Multilayer Networks for Language| | + | |
| - | |Subelj | Three forms of convexity in graphs and networks| | + | |
| - | + | ||
| - | + | ||
| - | + | ||
| - | ==== Meeting of working group 2: Network Modelling ==== | + | |
| - | + | ||
| - | ^ presenting author ^ title ^ | + | |
| - | |Artime | Ageing and multiplexity in the voter model| | + | |
| - | |Behrouzi | Dynamic Chain Graph Models for Time Series Mixed Data| | + | |
| - | |Engebretsen | How population clustering within a country affects infectious disease spread dynamics| | + | |
| - | |Grzegorczyk | Non-homogeneous dynamic Bayesian networks with partially edge-wise coupled interaction parameters| | + | |
| - | |Kadilar | On the Graphical Markov Models with an Application| | + | |
| - | |Michaud | A stochastic heterogeneous mean-field approximation of agent-based models| | + | |
| - | |Rodriguez | Coinfection in the space: cooperative disease spreading in geometric and contact networks| | + | |
| - | + | ||
| - | ==== Meeting of working group 3: Network Inference and Prediction ==== | + | |
| - | + | ||
| - | ^ presenting author ^ title ^ | + | |
| - | |Elliott | A novel approach to network anomaly detection| | + | |
| - | |Jarynowski | What do infection incidences tell us about connectivity of a regional healthcare network?| | + | |
| - | |Nurushev | Local inference by penalization method for biclustering model| | + | |
| - | |Ranciati | Mixture model under overlapping clusters: an application to network data| | + | |
| - | |Wit | Network inference in genomics| | + | |
| - | + | ||
| - | + | ||
| - | ==== COSTNET action conference: contributed talks ==== | + | |
| - | + | ||
| - | ^ presenting author ^ title ^ | + | |
| - | |Augugliaro | $\ell _1$-penalized Gaussian graphical model for left-censured data| | + | |
| - | |Batagelj | Describing network evolution using probabilistic inductive classes| | + | |
| - | |Cutillo | From Networks to Communities: a Robustness Measure| | + | |
| - | |Fernandez-Gracia | Gromov-Wasserstein distance of complex networks| | + | |
| - | |Ibanez-Marcelo | When shape matters: Brain networks studied under a persistent homology view| | + | |
| - | |Matias | A semiparametric extension of the stochastic block model for longitudinal networks| | + | |
| - | |Niezink | Standard errors in stochastic actor-oriented models| | + | |
| - | |Rancoita | Bayesian networks for data imputation in survival tree analysis| | + | |
| - | |Signorelli | How to integrate gene enrichment analysis with information from gene interaction networks| | + | |
| - | |Tamarit | Emergence of social structure: a generalization of Dunbar's circles| | + | |
| - | ==== COSTNET action conference: posters ==== | + | Authors printed in //italics// announce their poster by a flash talk before the poster session. |
| ^ presenting author ^ title ^ | ^ presenting author ^ title ^ | ||
| + | |Artime | Dynamics on Networks: Competition between Temporal and Topological Correlations| | ||
| + | |Bassolas | Scaling in the recovery of cities during special events| | ||
| + | |Bozhilova | Thresholding and random network generation based on uncertain networks | | ||
| |Cardoso | Topical homophily in online social systems| | |Cardoso | Topical homophily in online social systems| | ||
| - | |Janosov | Quantifying and comparing success in artistic careers| | + | |//Janosov//| Quantifying and comparing success in artistic careers| |
| |Kadilar | An Analysis of Air Quality Data with Markov Chains and Time Series| | |Kadilar | An Analysis of Air Quality Data with Markov Chains and Time Series| | ||
| |Khalil | Zealots in the mean-field noisy voter model | | |Khalil | Zealots in the mean-field noisy voter model | | ||
| |Koutras | Random order statistics probability models for networks | | |Koutras | Random order statistics probability models for networks | | ||
| - | |Lebacher| International Arms Trade: A Dynamic Separable Network Model with Heterogeneity Components| | + | |//Lebacher//| International Arms Trade: A Dynamic Separable Network Model with Heterogeneity Components| |
| - | |Lee | A Network Epidemic Model for Online Community Commissioning Data | | + | |//Lee//| A Network Epidemic Model for Online Community Commissioning Data | |
| |Lehmann | ERGMs in neuroimaging - developments and challenges| | |Lehmann | ERGMs in neuroimaging - developments and challenges| | ||
| - | |Leskela | Moment-based parameter estimation in binomial random intersection graph | | + | |//Leskela//| Moment-based parameter estimation in binomial random intersection graph | |
| |Marchetti | Graphoid properties and independence with Credal Networks | | |Marchetti | Graphoid properties and independence with Credal Networks | | ||
| |Min | Fragmentation transitions in a coevolving nonlinear voter model | | |Min | Fragmentation transitions in a coevolving nonlinear voter model | | ||
| Line 114: | Line 94: | ||
| |Pereda | From Ego Networks to Dunbar's Numbers and Social Structure: an experiment| | |Pereda | From Ego Networks to Dunbar's Numbers and Social Structure: an experiment| | ||
| |Pinho | Classifier Precision Analysis for Sleep Apnea Detection with ECG Signals | | |Pinho | Classifier Precision Analysis for Sleep Apnea Detection with ECG Signals | | ||
| - | |Pont Serra | Exact Computation of Percolation Cluster Sizes in Finite Networks | | + | |//Pont Serra//| Exact Computation of Percolation Cluster Sizes in Finite Networks | |
| - | |Raducha | Predicting language diversity with complex networks | | + | |//Raducha// | Predicting language diversity with complex networks | |
| |Sheykhali | Plasticity on Ecological Bipartite Networks| | |Sheykhali | Plasticity on Ecological Bipartite Networks| | ||
| |Sieradzki | Network Analysis of scientific Co-operation between faculties at Warsaw University of Life Sciences | | |Sieradzki | Network Analysis of scientific Co-operation between faculties at Warsaw University of Life Sciences | | ||
ev/2017/pdm_program.txt · Last modified: 2017/10/26 08:48 by konstantin
Page Tools
Except where otherwise noted, content on this wiki is licensed under the following license: CC Attribution-Share Alike 4.0 International
