Data Science Journal Club
We discuss exciting applications of data science techniques or promising methodological developments
Journal Club of the Data Science for SHaPE group is a monthly meeting for anyone with an interest in Data Science and its applications to societally beneficial causes. We cover a very wide range of topics but try to always provide appropriate context and assumptions, and highlight the relevant high-level message. We find that coming from a range of backgrounds and being a fairly interdisciplinary audience makes for very interesting discussions - so anyone welcome to join!
If you would like to attend, please contact us at datascienceunit@inf.ed.ac.uk
Next Journal Club
TBA
List of previously discussed papers
Paper(s): A Unified Approach to Interpreting Model Predictions
Presenter: Jorge Gaete
Date: 08/11/2024
Paper(s): Inferring Cultural Landscapes with the Inverse Ising Model
Presenter: Guillermo Romero
Date: 11/10/2024
Paper(s): Segment Anything, Segment Anything in Medical Images
Presenter: Karthik Mohan
Date: 09/02/2024
Paper(s): Improving Language Understanding by Generative Pre-Training, GPT-4 Technical Report, A Survey on Evaluation of Large Language Models
Presenter: Lara Johnson
Date: 08/12/2023
Paper(s): A Real Time Regional Model for COVID-9: Probabilistic situational awareness and forecasting (if you are interested in reading more about Approximate Bayesian Computation beforehand, these are useful: 1, 2 and 3)
Presenter: Kieran Richards
Date: 13/10/2023
Supplementary Reading: Approximate Bayesian Computation tutorials / overviews: 1, 2 and 3
Paper(s): ttps://arxiv.org/pdf/2304.13157.pdf, http://marksanderson.org/publications/my_papers/SIGIR_23_GPT.pdf and potentially also https://arxiv.org/pdf/2304.09161.pdf
Presenter: Anirban Chakraborty
Date: 09/06/2023
Paper(s): https://www.nature.com/articles/s41588-022-01042-x#Sec9
Presenter: Nikos Avramidis
Date: 14/04/2023
Paper(s): https://www.science.org/doi/10.1126/sciadv.abk0644 and https://www.sciencedirect.com/science/article/abs/pii/S0021999118307125
Presenter: Daga Panas
Date: 10/03/2023
Presentation: Link to the PowerPoint [UUN login required]
Paper(s): https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3979639/ and https://dl.acm.org/doi/10.1145/1015330.1015360
Presenter: Luwei Wang
Date: 10/02/2023
Paper(s): https://link.springer.com/chapter/10.1007/978-3-031-08341-9_35
Presenter: Sury Manocha
Date: 13/01/2023
Paper(s): https://www.nature.com/articles/s41598-022-09954-8 and https://dl.acm.org/doi/abs/10.1145/3465416.3483305
Presenter: Chima Eke
Date: 11/11/2022
Paper(s): https://papers.nips.cc/paper/2018/hash/e347c51419ffb23ca3fd5050202f9c3d-Abstract.html and https://proceedings.neurips.cc/paper/2021/hash/e987eff4a7c7b7e580d659feb6f60c1a-Abstract.html
Presenter: Oisín Nolan
Date: 09/09/2022
Supplementary reading: https://list01.bio.ens.psl.eu/wws/d_read/machine_learning/BayesianNetworks/koller.pdf
and https://www.bradyneal.com/Introduction_to_Causal_Inference-Dec17_2020-Neal.pdf
Paper(s): https://arxiv.org/abs/1711.08611, https://dl.acm.org/doi/10.1145/3269206.3271800 and https://dl.acm.org/doi/10.1145/3397271.3401075
Presenter: Anirban Chakraborty
Date: 12/08/2022
Supplementary reading: https://nlp.stanford.edu/IR-book/
Paper(s): https://doi.org/10.48550/arXiv.1706.03762, https://doi.org/10.48550/arXiv.2010.11929 and https://doi.org/10.1109/jtehm.2021.3134096
Presenter: Karthik Mohan
Date: 08/07/2022