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Found 8 papers, 7 papers with code
Prior Knowledge Injection into Deep Learning Models Predicting Gene Expression from Whole Slide Images
We design the framework to be generic and flexibly adaptable to a wide range of architectures.
Debiasing Synthetic Data Generated by Deep Generative Models
In response to these challenges, we propose a new strategy that targets synthetic data created by DGMs for specific data analyses.
From Text to Treatment Effects: A Meta-Learning Approach to Handling Text-Based Confounding
One of the central goals of causal machine learning is the accurate estimation of heterogeneous treatment effects from observational data.
SynSUM -- Synthetic Benchmark with Structured and Unstructured Medical Records
The SynSUM dataset is primarily designed to facilitate research on clinical information extraction in the presence of tabular background variables, which can be linked through domain knowledge to concepts of interest to be extracted from the text - the symptoms, in the case of SynSUM.
Clinical Reasoning over Tabular Data and Text with Bayesian Networks
Bayesian networks are well-suited for clinical reasoning on tabular data, but are less compatible with natural language data, for which neural networks provide a successful framework.
The Real Deal Behind the Artificial Appeal: Inferential Utility of Tabular Synthetic Data
Recent advances in generative models facilitate the creation of synthetic data to be made available for research in privacy-sensitive contexts.
Neural Bayesian Network Understudy
Bayesian Networks may be appealing for clinical decision-making due to their inclusion of causal knowledge, but their practical adoption remains limited as a result of their inability to deal with unstructured data.
Frozen Pretrained Transformers for Neural Sign Language Translation
Our results show that pretrained language models can be used to improve sign language translation performance and that the self-attention patterns in BERT transfer in zero-shot to the encoder and decoder of sign language translation models.
