13 citations · 24 across the 9 of their papers we have counts for
3 papers · 1 filter
NeuroMapper: In-browser Visualizer for Neural Network Training
Zhiyan Zhou, Kevin Li, Haekyu Park +4
We present our ongoing work NeuroMapper, an in-browser visualization tool that helps machine learning (ML) developers interpret the evolution of a model during training, providing…
Beyond Bayes-optimality: meta-learning what you know you don't know
Jordi Grau-Moya, Grégoire Delétang, Markus Kunesch +11
Meta-training agents with memory has been shown to culminate in Bayes-optimal agents, which casts Bayes-optimality as the implicit solution to a numerical optimization problem rath…
Concept Evolution in Deep Learning Training: A Unified Interpretation Framework and Discoveries
Haekyu Park, Seongmin Lee, Benjamin Hoover +7
We present ConceptEvo, a unified interpretation framework for deep neural networks (DNNs) that reveals the inception and evolution of learned concepts during training. Our work add…