Our paper on
- Survival-oriented embeddings was accepted at the NeurIPS workshop for Bridging the Gap: From Machine Learning Research to Clinical Practice;
- Modelling hazard factors in unstructured data spaces was accepted at the NeurIPS workshop for Deep Generative Models and Downstream Applications;
- Identifying the atmospheric drivers of drought and heat using a smoothed deep learning approach was accepted at the NeurIPS workshop for Tackling Climate Change with Machine Learning.