wiki:WikiStart

Version 9 (modified by thep, 4 months ago) (diff)

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CBBP ML Journal Club

When? Where? How?

When and Where

We aim to have one session per month and meet *on site* in the Majestic conference room at THEP.

It remains to be seen if we can find a fixed slot or whether papers will be scheduled on a case-to-case basis.

Ideally there should be ample time (i.e., not just 1 hour) if there are nice discussions going.

How

Everybody should read the paper before the session. One (or multiple) people should volunteer to chair the session. The chair should have read the paper somewhat carefully. Sessions will typically begin by going through the paper and painting the big picture before digging into details. The chair should be ready to provide such a short summary, although no slides etc are expected.

Scheduled Papers

Date Time and Location Paper link Chair
2022-05-02 13.00 Majestic (tentative suggestion for first meeting) Your suggestion here? link Santa Claus

Paper Suggestions

How to suggest

Add your papers at the top of the table below. It is advisable to volunteer to chair the papers you suggest.

How to vote

Edit this page and increase the vote count on the papers you are interested in doing next.

Paper link Chair volunteer Votes
Early Stopping without a Validation Set by Maren Mahsereci, Lukas Balles, Christoph Lassner, Philipp Hennig. Max-Planck report/arXiv http patrik@thep 1
Deep Patient: An Unsupervised Representation to Predict the Future of Patients from the Electronic Health Records by Riccardo Miotto, Li Li, Brian A. Kidd & Joel T. Dudley. Nature/Scientific reports pdf http andersb@thep 2
X-LXMERT: Paint, Caption and Answer Questions with Multi-Modal Transformers by Jaemin Cho, Jiasen Lu, Dustin Schwenk, Hannaneh Hajishirzi, Aniruddha Kembhavi. Empirical Methods in Natural Language Processing 2020 pdf http arxiv andersb@thep 1
The unsuccessful self-treatment of a case of “writer's block” by Dennis Upper. Journal of Applied Behavior Analysis pdf http andersb@thep 0
DeepFake electrocardiograms using generative adversarial networks are the beginning of the end for privacy issues in medicine by Vajira Thambawita, Jonas L. Isaksen, Steven A. Hicks, Jonas Ghouse, Gustav Ahlberg, Allan Linneberg, Niels Grarup, Christina Ellervik, Morten Salling Olesen, Torben Hansen, Claus Graff, Niels-Henrik Holstein-Rathlou, Inga Strümke, Hugo L. Hammer, Mary M. Maleckar, Pål Halvorsen, Michael A. Riegler & Jørgen K. Kanters. Nature/Scientific reports, 2021 pdf http andersb@thep 1
Explaining deep neural networks for knowledge discovery in electrocardiogram analysis by Steven A. Hicks, Jonas L. Isaksen, Vajira Thambawita, Jonas Ghouse, Gustav Ahlberg, Allan Linneberg, Niels Grarup, Inga Strümke, Christina Ellervik, Morten Salling Olesen, Torben Hansen, Claus Graff, Niels-Henrik Holstein-Rathlou, Pål Halvorsen, Mary M. Maleckar, Michael A. Riegler & Jørgen K. Kanters. Nature/Scientific reports, 2021 pdf http andersb@thep 1
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding by Jacob Devlin Ming-Wei Chang Kenton Lee Kristina Toutanova. arXiv, 2018 arXiv andersb@thep 0
Improving Fairness in Machine Learning Systems: What Do Industry Practitioners Need? by Kenneth Holstein, Jennifer Wortman Vaughan, Hal Daumé III, Miroslav Dudík, Hanna Wallach. CHI 2019 pdf andersb@thep 0

Past Papers

Date Time and Location Paper link Chair
2019-04-29 15.00, Majestic Conference room TBD; something on GANs TBD linse@thep
2019-04-12 10.30, Majestic Conference room A Fast and Accurate Dependency Parser using Neural Networks by Danqi Chen, Christopher Manning. EMNLP 2014 pdf andersb@thep