We have accepted 24 papers to be included in the Volume 136 of the Proceedings of Machine Learning Research. These are listed below, with links to posters. Numbers indicate poster session IDs.

See the NeurIPS workshop page for live video, chat links, and the most updated schedule. We have also created a Guide for Poster Presenters and a Livestream Guide for Attendees

Session 1

2. Improved Clinical Abbreviation Expansion via Non-Sense-Based Approaches

Juyong Kim, Linyuan Gong, Justin Khim, Jeremy C. Weiss, Pradeep Ravikumar

4. DeepHeartBeat: Sequence modelling for medical data

Fabian Laumer*, Gabriel Fringeli*, Alina Dubatovka, Laura Manduchi, Joachim M. Buhmann

7. Evaluation of Contrastive Predictive Coding for Histopathology Applications

Karin Stacke, Claes Lundström, Jonas Unger, Gabriel Eilertsen

9. Confounding Feature Acquisition for Causal Effect Estimation

Shirly Wang*, Seung Eun Yi*, Shalmali Joshi, Marzyeh Ghassemi

14. Zero-Shot Clinical Acronym Expansion via Latent Meaning Cells

Griffin Adams, Mert Ketenci, Shreyas Bhave, Adler Perotte, Noémie Elhadad

21. Neural Temporal Point Processes For Modelling Electronic Health Records

Joseph Enguehard*, Dan Busbridge*, Adam Bozson, Claire Woodcock, Nils Hammerla

28. A Neural SIR Model for Global Forecasting

Philip Nadler; Rossella Arcucci; Yike Guo

Session 2

48. sEMG Gesture Recognition with a Simple Model of Attention

David Josephs*, Carson Drake*, Andrew Heroy, John Santerre

49. Addressing the Real-world Class Imbalance Problem in Dermatology

Wei-Hung Weng, Jonathan Deaton, Vivek Natarajan, Gamaleldin F. Elsayed, Yuan Liu

50. Appropriate Evaluation of Diagnostic Utility of Machine Learning Algorithm Generated Images

Young Joon (Fred) Kwon, Danielle Toussie, Lea Azour, Jose Concepcion, Corey Eber, G Anthony Reina, Ping Tak Peter Tang, Amish H Doshi, Eric K Oermann, Anthony B Costa

52. Contrastive Representation Learning for Electroencephalogram Classification

Mostafa Mohsenvand, Mohammad Rasool Izadi, Pattie Maes

55. Interpretable Epilepsy Detection in Routine, Interictal EEG Data using Deep Learning

Thomas Uyttenhove, Aren Maes, Tom Van Steenkiste, Dirk Deschrijver, Tom Dhaene

56. ML4H Auditing: From Paper to Practice

Luis Oala, Jana Fehr, Luca Gilli, Pradeep Balachandaran, Alixandro Werneck Leite, Saul Calderon-Ramirez, Danny Xie Li, Gabriel Nobis, Erick Alejandro Muñoz Alvarado, Giovanna Jaramillo-Gutierrez, Christian Matek, Arun Shroff, Ferath Kherif, Bruno Sanguinetti, Thomas Wiegand

65. CheXphoto: 10,000+ Photos and Transformations of Chest X-rays for Benchmarking Deep Learning Robustness

Nicholas Phillips, Pranav Rajpurkar, Mark Sabini, Rayan Krishnan, Sharon Zhou, Anuj Pareek, Nguyet Minh Phu, Chris Wang, Mudit Jain, Nguyễn Dương Du, Steven QH Truong, Andrew Y. Ng, Matthew P. Lungren

72. Attend and Decode: 4D fMRI Task State Decoding Using Attention Models

Sam Nguyen, Brenda Ng, Alan D. Kaplan, Priyadip Ray

73. An Empirical Study of Representation Learning for Reinforcement Learning in Healthcare

Taylor W. Killian, Haoran Zhang, Jayakumar Subramanian, Mehdi Fatemi, Marzyeh Ghassemi

78. 3D Photography Based Neural Network Craniosynostosis Triaging System

Pouria Mashouri; Marta Skreta; John Phillips; Dianna McAllister; Melissa Roy; Senthujan Senkaiahliyan; Michael Brudno; Devin Singh