Search Results for author: Weicheng Zhu

Found 7 papers, 4 papers with code

Interpretable Prediction of Lung Squamous Cell Carcinoma Recurrence With Self-supervised Learning

1 code implementation23 Mar 2022 Weicheng Zhu, Carlos Fernandez-Granda, Narges Razavian

The resulting representations and clusters from self-supervision are used as features of a survival model for recurrence prediction at the patient level.

Multiple Instance Learning Self-Supervised Learning +1

Deep Probability Estimation

no code implementations21 Nov 2021 Sheng Liu, Aakash Kaku, Weicheng Zhu, Matan Leibovich, Sreyas Mohan, Boyang Yu, Haoxiang Huang, Laure Zanna, Narges Razavian, Jonathan Niles-Weed, Carlos Fernandez-Granda

Reliable probability estimation is of crucial importance in many real-world applications where there is inherent (aleatoric) uncertainty.

Autonomous Vehicles Weather Forecasting

Adaptive Early-Learning Correction for Segmentation from Noisy Annotations

2 code implementations CVPR 2022 Sheng Liu, Kangning Liu, Weicheng Zhu, Yiqiu Shen, Carlos Fernandez-Granda

We discover a phenomenon that has been previously reported in the context of classification: the networks tend to first fit the clean pixel-level labels during an "early-learning" phase, before eventually memorizing the false annotations.

Classification Medical Image Segmentation +4

Variationally Regularized Graph-based Representation Learning for Electronic Health Records

1 code implementation8 Dec 2019 Weicheng Zhu, Narges Razavian

A feasible approach to improving the representation learning of EHR data is to associate relevant medical concepts and utilize these connections.

Graph structure learning Representation Learning

Baidu Apollo EM Motion Planner

1 code implementation20 Jul 2018 Haoyang Fan, Fan Zhu, Changchun Liu, Liangliang Zhang, Li Zhuang, Dong Li, Weicheng Zhu, Jiangtao Hu, Hongye Li, Qi Kong

In this manuscript, we introduce a real-time motion planning system based on the Baidu Apollo (open source) autonomous driving platform.

Autonomous Driving Motion Planning

Variational hybridization and transformation for large inaccurate noisy-or networks

no code implementations20 May 2016 Yusheng Xie, Nan Du, Wei Fan, Jing Zhai, Weicheng Zhu

In addition, we propose a transformation ranking algorithm that is very stable to large variances in network prior probabilities, a common issue that arises in medical applications of Bayesian networks.

Variational Inference

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