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Found 7 papers, 1 papers with code
Borrowing Treasures from Neighbors: In-Context Learning for Multimodal Learning with Missing Modalities and Data Scarcity
The proposed data-dependent framework exhibits a higher degree of sample efficiency and is empirically demonstrated to enhance the classification model's performance on both full- and missing-modality data in the low-data regime across various multimodal learning tasks.
PROSAC: Provably Safe Certification for Machine Learning Models under Adversarial Attacks
Our paper offers a new approach to certify the performance of machine learning models in the presence of adversarial attacks with population level risk guarantees.
HgbNet: predicting hemoglobin level/anemia degree from EHR data
EHR-based hemoglobin level/anemia degree prediction is non-invasive and rapid but still faces some challenges due to the fact that EHR data is typically an irregular multivariate time series containing a significant number of missing values and irregular time intervals.
Generative Scene Graph Networks
We formulate GSGN as a variational autoencoder in which the latent representation is a tree-structured probabilistic scene graph.
Volctrans Parallel Corpus Filtering System for WMT 2020
In this paper, we describe our submissions to the WMT20 shared task on parallel corpus filtering and alignment for low-resource conditions.
Extended Answer and Uncertainty Aware Neural Question Generation
In this paper, we study automatic question generation, the task of creating questions from corresponding text passages where some certain spans of the text can serve as the answers.
Generative Hierarchical Models for Parts, Objects, and Scenes
Compositional structures between parts and objects are inherent in natural scenes.
