12 citations · 12 across the 2 of their papers we have counts for
3 papers
cs.CV2021
Weakly Supervised Keypoint Discovery
Serim Ryou, Pietro Perona
In this paper, we propose a method for keypoint discovery from a 2D image using image-level supervision. Recent works on unsupervised keypoint discovery reliably discover keypoints…
cs.LG2020★ 12 cited
Graph Neural Networks for the Prediction of Substrate-Specific Organic Reaction Conditions
Serim Ryou, Michael R. Maser, Alexander Y. Cui +3
We present a systematic investigation using graph neural networks (GNNs) to model organic chemical reactions. To do so, we prepared a dataset collection of four ubiquitous reaction…
cs.CV2019
Anchor Loss: Modulating Loss Scale based on Prediction Difficulty
Serim Ryou, Seong-Gyun Jeong, Pietro Perona
We propose a novel loss function that dynamically rescales the cross entropy based on prediction difficulty regarding a sample. Deep neural network architectures in image classific…