Normalizing Flow-based Neural Process for Few-Shot Knowledge Graph Completion
PulseAugur coverage of Normalizing Flow-based Neural Process for Few-Shot Knowledge Graph Completion — every cluster mentioning Normalizing Flow-based Neural Process for Few-Shot Knowledge Graph Completion across labs, papers, and developer communities, ranked by signal.
-
New methods enhance conformal prediction for uncertainty quantification
Researchers have developed novel methods for conformal prediction, a technique used for uncertainty quantification in machine learning. The first approach utilizes a differentiable nonconformity score to create a flow o…
-
New discriminator-informed resampling improves Gaussian mixture filter accuracy
Researchers have developed a new method to improve the Ensemble Gaussian Mixture Filter (EnGMF) by incorporating a learned discriminator for the resampling step. This discriminator, implemented using a normalizing flow …
-
Researchers use generative modeling to solve quantum dynamics via score matching
Researchers have developed a novel method to solve the time-dependent Schrödinger equation by learning the score function on Bohmian trajectories. This approach utilizes a neural network to parametrize the score and min…