Search Results for author: Tiantian Liu

Found 6 papers, 2 papers with code

Connectional-Style-Guided Contextual Representation Learning for Brain Disease Diagnosis

no code implementations8 Jun 2023 Gongshu Wang, Ning Jiang, Yunxiao Ma, Tiantian Liu, Duanduan Chen, Jinglong Wu, Guoqi Li, Dong Liang, Tianyi Yan

In this work, we propose a connectional style contextual representation learning model (CS-CRL) to capture the intrinsic pattern of the brain, used for multiple brain disease diagnosis.

Representation Learning

Complex Locomotion Skill Learning via Differentiable Physics

1 code implementation6 Jun 2022 Yu Fang, Jiancheng Liu, Mingrui Zhang, Jiasheng Zhang, Yidong Ma, Minchen Li, Yuanming Hu, Chenfanfu Jiang, Tiantian Liu

Differentiable physics enables efficient gradient-based optimizations of neural network (NN) controllers.

An Experimental Analysis of Indoor Spatial Queries: Modeling, Indexing, and Processing

1 code implementation8 Oct 2020 Tiantian Liu, Huan Li, Hua Lu, Muhammad Aamir Cheema, Lidan Shou

Indoor location-based services (LBS), such as POI search and routing, are often built on top of typical indoor spatial queries.

Databases Data Structures and Algorithms

Boosting Connectivity in Retinal Vessel Segmentation via a Recursive Semantics-Guided Network

no code implementations24 Apr 2020 Rui Xu, Tiantian Liu, Xinchen Ye, Yen-Wei Chen

Many deep learning based methods have been proposed for retinal vessel segmentation, however few of them focus on the connectivity of segmented vessels, which is quite important for a practical computer-aided diagnosis system on retinal images.

Retinal Vessel Segmentation Segmentation

Kernel Machines With Missing Responses

no code implementations7 Jun 2018 Tiantian Liu, Yair Goldberg

For the quadratic loss, we then propose a family of doubly-robust kernel machines.

General Classification regression

Towards Real-time Simulation of Hyperelastic Materials

no code implementations25 Apr 2016 Tiantian Liu, Sofien Bouaziz, Ladislav Kavan

In this paper, we show that Projective Dynamics can be interpreted as a quasi-Newton method.

Graphics

Cannot find the paper you are looking for? You can Submit a new open access paper.