Search Results for author:
Found 7 papers, 4 papers with code
The Canadian Cropland Dataset: A New Land Cover Dataset for Multitemporal Deep Learning Classification in Agriculture
Monitoring land cover using remote sensing is vital for studying environmental changes and ensuring global food security through crop yield forecasting.
Prior Density Learning in Variational Bayesian Phylogenetic Parameters Inference
In this paper, we propose an approach and an implementation framework to relax the rigidity of the prior densities by learning their parameters using a gradient-based method and a neural network-based parameterization.
EvoVGM: a Deep Variational Generative Model for Evolutionary Parameter Estimation
Most evolutionary-oriented deep generative models do not explicitly consider the underlying evolutionary dynamics of biological sequences as it is performed within the Bayesian phylogenetic inference framework.
Supporting supervised learning in fungal Biosynthetic Gene Cluster discovery: new benchmark datasets
Supervised learning methods have been shown to perform well at identifying BGCs in bacteria, and could be well suited to perform the same task in fungi.
Statistical Linear Models in Virus Genomic Alignment-free Classification: Application to Hepatitis C Viruses
While linear classifiers are often used to classify viruses, there is a lack of exploration of the accuracy space of existing models in the context of alignment free approaches.
Toward an Efficient Multi-class Classification in an Open Universe
Existing classification methods are designed to classify unknown instances within a set of previously known training classes.
ProtNN: Fast and Accurate Nearest Neighbor Protein Function Prediction based on Graph Embedding in Structural and Topological Space
ProtNN assigns to the query protein the function with the highest number of votes across the set of k nearest neighbor reference proteins, where k is a user-defined parameter.
