Issues

Deep Double Descent: Where Bigger Models and More Data Hurt
greenelab/readables#20 · opened on Dec 6, 2019
A Comprehensive Survey on Graph Neural Networks
greenelab/readables#19 · opened on Sep 12, 2019
Machine learning for integrating data in biology and medicine: Principles, practice, and opportunities
greenelab/readables#18 · opened on Sep 9, 2019
Supervised-learning is an accurate method for network-based gene classification
greenelab/readables#17 · opened on Aug 8, 2019
Weighted elastic net for unsupervised domain adaptation with application to age prediction from DNA methylation data
greenelab/readables#16 · opened on Jul 25, 2019
Invariant Risk Minimization
greenelab/readables#15 · opened on Jul 12, 2019
Enhanced Expressive Power and Fast Training of Neural Networks by Random Projections
greenelab/readables#14 · opened on Jul 10, 2019
Identifying gene expression programs of cell-type identity and cellular activity with single-cell RNA-Seq
greenelab/readables#13 · opened on Jul 9, 2019
Unsupervised word embeddings capture latent knowledge from materials science literature
greenelab/readables#12 · opened on Jul 8, 2019
Learning Explainable Models Using Attribution Priors
greenelab/readables#10 · opened on Jun 27, 2019
Human and mouse essentiality screens as a resource for disease gene discovery
greenelab/readables#9 · opened on Jun 27, 2019
Learning Generative Models across Incomparable Spaces
greenelab/readables#8 · opened on Jun 26, 2019
netNMF-sc: Leveraging gene-gene interactions for imputation and dimensionality reduction in single-cell expression analysis
greenelab/readables#5 · opened on Jun 24, 2019