Search Results for author:
Found 5 papers, 2 papers with code
DOME Registry: Implementing community-wide recommendations for reporting supervised machine learning in biology
Supervised machine learning (ML) is used extensively in biology and deserves closer scrutiny.
Synthetic data: How could it be used for infectious disease research?
In this commentary we aim to create an overview of the current and future position of synthetic data in infectious disease research.
Synth4bench: a framework for generating synthetic genomics data for the evaluation of tumor-only somatic variant calling algorithms
Results Using synthetic dataset as ground truth provides an excellent approach for evaluating the performance of tumor-only somatic variant calling algorithms.
Deep Residual Error and Bag-of-Tricks Learning for Gravitational Wave Surrogate Modeling
In several cases, small improvements can be observed, but the most significant improvement still comes from the addition of a second network that models the residual error.
Autoencoder-driven Spiral Representation Learning for Gravitational Wave Surrogate Modelling
Based on this finding, we design a spiral module with learnable parameters, that is used as the first layer in a neural network, which learns to map the input space to the coefficients.
