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Found 8 papers, 4 papers with code
Remote Inference of Cognitive Scores in ALS Patients Using a Picture Description
In this paper, we focused on another important aspect, cognitive impairment, which affects 35-50% of the ALS population.
Efficiently predicting high resolution mass spectra with graph neural networks
Identifying a small molecule from its mass spectrum is the primary open problem in computational metabolomics.
Adaptive Bias Correction for Improved Subseasonal Forecasting
Subseasonal forecasting -- predicting temperature and precipitation 2 to 6 weeks ahead -- is critical for effective water allocation, wildfire management, and drought and flood mitigation.
SubseasonalClimateUSA: A Dataset for Subseasonal Forecasting and Benchmarking
To streamline this process and accelerate future development, we introduce SubseasonalClimateUSA, a curated dataset for training and benchmarking subseasonal forecasting models in the United States.
Investigating the Utility of Multimodal Conversational Technology and Audiovisual Analytic Measures for the Assessment and Monitoring of Amyotrophic Lateral Sclerosis at Scale
Our results provide encouraging evidence of the utility of automatically extracted audiovisual analytics for scalable remote patient assessment and monitoring in ALS.
Graph-Sparse Logistic Regression
We introduce Graph-Sparse Logistic Regression, a new algorithm for classification for the case in which the support should be sparse but connected on a graph.
Unsupervised learning of transcriptional regulatory networks via latent tree graphical models
We use a latent tree graphical model to analyze gene expression without relying on transcription factor expression as a proxy for regulator activity.
Discovering Neuronal Cell Types and Their Gene Expression Profiles Using a Spatial Point Process Mixture Model
Single-cell RNA sequencing can now be used to measure the gene expression profiles of individual neurons and to categorize neurons based on their gene expression profiles.
