NeurIPS(NIPS) 2020 论文列表
Machine Learning for Health Workshop, ML4H@NeurIPS 2020, Virtual Event, 11 December 2020.
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Addressing the Real-world Class Imbalance Problem in Dermatology.
TL-Lite: Temporal Visualization and Learning for Clinical Forecasting.
Confounding Feature Acquisition for Causal Effect Estimation.
EEG-GCNN: Augmenting Electroencephalogram-based Neurological Disease Diagnosis using a Domain-guided Graph Convolutional Neural Network.
Interpretable Epilepsy Detection in Routine, Interictal EEG Data using Deep Learning.
Trust Issues: Uncertainty Estimation Does Not Enable Reliable OOD Detection On Medical Tabular Data.
Evaluation of Contrastive Predictive Coding for Histopathology Applications.
CheXphoto: 10, 000+ Photos and Transformations of Chest X-rays for Benchmarking Deep Learning Robustness.
ML4H Auditing: From Paper to Practice.
Attend and Decode: 4D fMRI Task State Decoding Using Attention Models.
A Neural SIR Model for Global Forecasting.
Contrastive Representation Learning for Electroencephalogram Classification.
3D Photography Based Neural Network Craniosynostosis Triaging System.
Spectral discontinuity design: Interrupted time series with spectral mixture kernels.
DeepHeartBeat: Latent trajectory learning of cardiac cycles using cardiac ultrasounds.
Appropriate Evaluation of Diagnostic Utility of Machine Learning Algorithm Generated Images.
Improved Clinical Abbreviation Expansion via Non-Sense-Based Approaches.
An Empirical Study of Representation Learning for Reinforcement Learning in Healthcare.
sEMG Gesture Recognition with a Simple Model of Attention.
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Neural Temporal Point Processes For Modelling Electronic Health Records.
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Quantifying Common Support between Multiple Treatment Groups Using a Contrastive-VAE.
Zero-Shot Clinical Acronym Expansion via Latent Meaning Cells.
Machine Learning for Health (ML4H) 2020: Advancing Healthcare for All.
