The mission of this SIG is to raise general knowledge on applied analytical solutions in the Netherlands eScience Center, as well as their technical implementations. We aim for a deeper understanding than is generally needed to use a specific method, that is, to go beyond the black-box level of thinking. Mathematics/statistics is capable of drastically reducing the complexity of existing solutions in a wide variety of cases, as well as formulating novel ideas that lie outside our comfort zone.
We meet roughly every 4 weeks and have, in between, also shared sessions with with Machine Learning SIG.
If you would like to present or invite an external speaker, please feel free to subscribe for any of the upcoming sessions in the table below using a pull request or by opening an issue.
Contact persons
- Flavio Hafner ([email protected])
- Johan Hidding ([email protected])
Date | Type | Speaker | Topic |
---|---|---|---|
January 25, 2024 | Analytics/ML | Laurent Soucasse | Analysis and modelling of thermal convection from simulation data through machine learning techniques |
March 14, 2024 | Analytics | Video: 3b1b | But what is a convolution? |
May 16, 2024 | Analytics/ML | Djura Smits | Privacy protection I: federated learning |
June 6, 2024 | Analytics | Flavio Hafner | Privacy protection II: differential privacy |
June 13, 2024 | Analytics/ML | Malte Lueken | Introduction to amortized Bayesian inference |
July 4, 2024 | Analytics | Nishant Joshi (Donders Institute) | Methods for Comparing Unsupervised Clusters Across Modalities in a Single Neuron Dataset |
September 12, 2024 | Analytics/ML | Video: Jake Hofman | Prediction and explanation in the social sciences |
October 3, 2024 | Analytics | -- | -- |
October 10, 2024 | Analytics/ML | Bob Carpenter (Flatiron Institute) | PPL design for Bayesian workflow |
October 31, 2024 | Analytics | -- | -- |
November 7, 2024 | Analytics/ML | -- | -- |
November 28, 2024 | Analytics | Erik van Zwet (Leiden UMC) | Shrinkage Trilogy |
December 5, 2024 | Analytics/ML | -- | -- |
Do you encounter statistics/mathematics problems in your projects? You can bring your issue to the SIG -- we can look at the issue together and do our best to find an applied analytical solution.
- Open an issue on GitHub and label it
Help | Title
. - Describe the type of issue you want to address. Make sure to include:
- What is the final goal?
- What is the challenge?
- A sample of your code (if possible).
We will discuss your issue during the next SIG meeting.
Did you do something really cool? Share your experiences with the SIG! Contact the SIG to arrange a presentation in one of the upcoming sessions.
Date | Type | Speaker | Topic |
---|---|---|---|
September 14, 2023 | Analytics | Video: Larry Wasserman | Foundations of Statistical Inference |
September 21, 2023 | Analytics/ML | Malte Lueken/Flavio Hafner | Causal Inference |
October 12, 2023 | Analytics | Thijs Vroegh | Social network analysis: the aspect of time |
October 19, 2023 | Analytics/ML | Video: Kyle Cranmer | Simulation-based inference, interpretability, and experimental design |
December 7, 2023 | Analytics | Chang Sun (Maastricht University) | Differentially private synthetic data |
Date | Topic | Presenter |
---|---|---|
2018-04-12 | Importance weighting | Wouter |
2018-05-07 | Network formation models | Laurens |
2018-05-31 | Network community detection | Dafne |
2018-06-21 | Topological data analysis | Johan |
2018-08-02 | Applied multilevel regression analysis | Vincent |
2018-11-05 | Causal inference | Mees |
2019-01-21 | Surrogate modelling | Laurens |
2019-07-18 | Copula | Sarah |
2020-02-17 | Uncertainty quantification | Anna |
2020-05-11 | Complex systems | Johan |
2020-05-25 | Confidence intervals | Hanno |
2020-06-08 | Community detection | Dafne |
2020-06-22 | Change detection in time series | Wanda |
2020-07-06 | Chapter0-Introduction in "A First Course in Network Science" | course |
2020-07-20 | Chapter1-Network elements in "A First Course in Network Science" | course |
2020-08-31 | Chapter1-Network elements in "A First Course in Network Science" | course |
2020-09-14 | Chapter1-Network elements in "A First Course in Network Science" | course |
2020-09-28 | Chapter2-Small Worlds in "A First Course in Network Science" | course |
2020-10-12 | Complex numbers for research software engineers | Pablo R. |
2020-10-26 | Chapter2-Small Worlds in "A First Course in Network Science" | course |
2020-11-09 | Voronoi diagrams and their many and varied uses, an introduction | Johan |
2020-11-23 | Chapter2-Small Worlds in "A First Course in Network Science" | Sarah |
2020-12-07 | Extreme value theory in weather & climate | Gijs |
2021-02-15 | Chapter3-Hubs in "A First Course in Network Science" | Dafne & Djura |
2021-03-01 | Random walks - part I | video-lecture |
2021-03-15 | Chapter4-Directions in "A First Course in Network Science" | Sarah & Barbara |
2021-03-25 | SIG lightning talk | Pablo R. |
2021-03-29 | Mining gold with Bayesian Optimization | Floris |
2021-04-12 | Chapter4&5- "A First Course in Network Science" | Cunliang & Sarah |
2021-04-26 | Probability, by Richard Feynman | Pablo R. |
2021-06-07 | Chapter6- "A First Course in Network Science" | Cunliang & Sarah |
2021-06-21 | Brainstorming on applied mathematics | Jens |
2021-10-11 | Optimization and Julia | Abel |
2021-11-08 | Descriptive and Inferential statistics | Study Group |
2021-11-22 | Brainstorming on applied mathematics | Johan & Pablo |
2022-01-17 | Descriptive and Inferential statistics | Study Group |
2021-01-31 | Pattern formation | Frits |
2022-02-28 | Leaders meeting | SIG meetings |
2022-03-14 | Study group | Study Group |
2022-03-28 | Cancelled | Cancelled |
2022-04-11 | Study group | Study Group |
2022-04-25 | Study group | Johan |
2022-05-09 | Brainstorm public SIGs | Pablo R. |
2022-07-18 | SIG future strategy | Pablo R. |
2023-05-25 | Geometric Numerical Integration and Scientific Machine Learning | Michael Kraus, MPI - NMPP |
Technique | Engineer(s) |
---|---|
Structural Equation Modelling (SEM) | Laurens |
Hamiltonian Monte Carlo (HMC) | Patrick |
Applied dynamical systems theory | Pablo R. |
Computer vision | Pablo R. |
Geo-statistics | Sarah |
Software | Engineer(s) |
---|---|
R | Laurens, Vincent, Pablo R. |
SPSS | Laurens |
AMOS | Laurens |
Matlab | Pablo R. |
Topic | Suggested by |
---|---|
Trade-off between stability and accuracy in deep learning | Sarah |
Kinematics with a smartphone | Pablo R. |
Something about partial differential equations? | Pablo R. |
Watch lecture on Network epidemiology | Dafne |
Watch lectures on Random walks | Dafne |
Course on Agent based models | Dafne |
Counter-intuitive probability problems | Pablo R. and Barbara |
Structure-preserving numerical methods for PDEs | Artur |
Reproducing a model | Pablo R. |
Name | Institution | Expertise | Notes |
---|---|---|---|
Pablo Deleteme | NLeSC | Making tables | Delete this line |
Location | Organisation | Event |
---|---|---|
Utrecht | Utrecht University | Data Science SIG |
Utrecht | Utrecht University | R Cafe |
Utrecht | Utrecht University | Complexity lab |
Amsterdam | MeetUp | Data Science Amsterdam |
Amsterdam | MeetUp | Amste-R-dam |
- | Congress | Nederlands Matematisch Congres |
Location | Date | Course |
---|---|---|
Utrecht | 10 July 2019 - 12 July 2019 | Introduction to Multilevel Analysis |
Utrecht | 15 July 2019 - 17 July 2019 | Advanced Multilevel Analysis |
Utrecht | 19 August 2019 - 23 August 2019 | Modeling the dynamics of intensive longitudinal data |
Utrecht | 15 April 2019 - 18 April 2019 | Applied Bayesian Statistics |
Utrecht | 08 July 2019 - 12 July 2019 | Introduction to Structural Equation Modeling using Mplus |
Utrecht | 15 July 2019 - 19 July 2019 | Advanced course on using Mplus |
Software | Topic and source |
---|---|
FORCE | Mass-processing of selected medium-resolution satellite image archives |