melodi-lab Goto Github PK
Name: Melodi Lab @ The University of Washington
Type: Organization
Bio: MELODI (MachinE Learning, Optimization, and Data Interpretation)
Location: Seattle, Washington
Melodi Lab @ The University of Washington's Projects
dataperf-vision-selection
Alpha version of our data-centric visual benchmark for training data selection
dihcl
divfl
Diverse Client Selection for Federated Learning via Submodular Maximization
docl
Code for "Curriculum Learning by Optimizing Learning Dynamics" (AISTATS 2021)
driptoolkit
The DRIP Toolkit (DTK) identifies tandem mass spectra utilizing a Dynamic Bayesian network for Rapid Identification of Peptides (DRIP). DTK performs efficient dynamic Bayesian network (DBN) inference using the Graphical Models Toolkit (GMTK).
gmtk
gmtk - the graphical models toolkit
gui_interface_for_submodular_data_selection
ilmsf_old
MATLAB code by Kai Wei : Interactive Learning of Mixtures of Submodular Functions, for Image Summarization
kmers-selection
mcl
sgm
Bipartite matching generalizations for peptide identification in tandem mass spectrometry
sgmvisualization
submodular-selection-of-assays
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