89 citations · 89 across the 5 of their papers we have counts for
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stat.ML2020
MetAL: Active Semi-Supervised Learning on Graphs via Meta Learning
Kaushalya Madhawa, Tsuyoshi Murata
The objective of active learning (AL) is to train classification models with less number of labeled instances by selecting only the most informative instances for labeling. The AL…
stat.ML2019★ 89 cited
GraphNVP: An Invertible Flow Model for Generating Molecular Graphs
Kaushalya Madhawa, Katushiko Ishiguro, Kosuke Nakago +1
We propose GraphNVP, the first invertible, normalizing flow-based molecular graph generation model. We decompose the generation of a graph into two steps: generation of (i) an adja…
stat.ML2018
Exploring Partially Observed Networks with Nonparametric Bandits
Kaushalya Madhawa, Tsuyoshi Murata
Real-world networks such as social and communication networks are too large to be observed entirely. Such networks are often partially observed such that network size, network topo…