activity
20172023
most citedMentorNet: Learning Data-Driven Curriculum for Very Deep Neural Networks on Corrupted Labels

528 citations · 1.3k across the 35 of their papers we have counts for

collaborators
Showing 2019Show all

9 papers · 1 filter

cs.CV2019★ 9 cited

Controllable and Progressive Image Extrapolation

Yijun Li, Lu Jiang, Ming-Hsuan Yang

Image extrapolation aims at expanding the narrow field of view of a given image patch. Existing models mainly deal with natural scene images of homogeneous regions and have no cont…

cs.CV2019★ 9 cited

Neural Design Network: Graphic Layout Generation with Constraints

Hsin-Ying Lee, Lu Jiang, Irfan Essa +4

Graphic design is essential for visual communication with layouts being fundamental to composing attractive designs. Layout generation differs from pixel-level image synthesis and…

cs.CV2019★ 11 cited

The Garden of Forking Paths: Towards Multi-Future Trajectory Prediction

Junwei Liang, Lu Jiang, Kevin Murphy +2

This paper studies the problem of predicting the distribution over multiple possible future paths of people as they move through various visual scenes. We make two main contributio…

stat.ML2019

Confident Learning: Estimating Uncertainty in Dataset Labels

Curtis G. Northcutt, Lu Jiang, Isaac L. Chuang

Learning exists in the context of data, yet notions of confidence typically focus on model predictions, not label quality. Confident learning (CL) is an alternative approach which…

cs.LG2019★ 11 cited

Feature Partitioning for Efficient Multi-Task Architectures

Alejandro Newell, Lu Jiang, Chong Wang +2

Multi-task learning holds the promise of less data, parameters, and time than training of separate models. We propose a method to automatically search over multi-task architectures…

cs.CL2019★ 37 cited

Robust Neural Machine Translation with Doubly Adversarial Inputs

Yong Cheng, Lu Jiang, Wolfgang Macherey

Neural machine translation (NMT) often suffers from the vulnerability to noisy perturbations in the input. We propose an approach to improving the robustness of NMT models, which c…