Search Results for author: Ting Li

Found 18 papers, 2 papers with code

Deep MSFOP: Multiple Spectral filter Operators Preservation in Deep Functional Maps for Unsupervised Shape Matching

no code implementations6 Feb 2024 Feifan Luo, Qingsong Li, Ling Hu, Xinru Liu, Haojun Xu, Haibo Wang, Ting Li, Shengjun Liu

We propose a novel constraint called Multiple Spectral filter Operators Preservation (MSFOR) to compute functional maps and based on it, develop an efficient deep functional map architecture called Deep MSFOP for shape matching.

Conditional Stochastic Interpolation for Generative Learning

no code implementations9 Dec 2023 Ding Huang, Jian Huang, Ting Li, Guohao Shen

We propose a conditional stochastic interpolation (CSI) approach to learning conditional distributions.

Image Generation

Optimal Clustering of Discrete Mixtures: Binomial, Poisson, Block Models, and Multi-layer Networks

no code implementations27 Nov 2023 Zhongyuan Lyu, Ting Li, Dong Xia

Under the mixture multi-layer stochastic block model (MMSBM), we show that the minimax optimal network clustering error rate, which takes an exponential form and is characterized by the Renyi divergence between the edge probability distributions of the component networks.

Clustering Community Detection +1

IBoxCLA: Towards Robust Box-supervised Segmentation of Polyp via Improved Box-dice and Contrastive Latent-anchors

no code implementations11 Oct 2023 Zhiwei Wang, Qiang Hu, Hongkuan Shi, Li He, Man He, Wenxuan Dai, Ting Li, Yitong Zhang, Dun Li, Mei Liu, Qiang Li

In response, we propose two innovative learning fashions, Improved Box-dice (IBox) and Contrastive Latent-Anchors (CLA), and combine them to train a robust box-supervised model IBoxCLA.


Spatio-Temporal Contrastive Self-Supervised Learning for POI-level Crowd Flow Inference

no code implementations6 Sep 2023 Songyu Ke, Ting Li, Li Song, Yanping Sun, Qintian Sun, Junbo Zhang, Yu Zheng

To address these challenges, we recast the crowd flow inference problem as a self-supervised attributed graph representation learning task and introduce a novel Contrastive Self-learning framework for Spatio-Temporal data (CSST).

Contrastive Learning Graph Representation Learning +2

GPU Accelerated Color Correction and Frame Warping for Real-time Video Stitching

no code implementations17 Aug 2023 Lu Yang, Zhenglun Kong, Ting Li, Xinyi Bai, Zhiye Lin, Hong Cheng

Traditional image stitching focuses on a single panorama frame without considering the spatial-temporal consistency in videos.

Camera Calibration Image Stitching +1

Evaluating Dynamic Conditional Quantile Treatment Effects with Applications in Ridesharing

no code implementations17 May 2023 Ting Li, Chengchun Shi, Zhaohua Lu, Yi Li, Hongtu Zhu

However, assessing dynamic quantile treatment effects (QTE) remains a challenge, particularly when dealing with data from ride-sourcing platforms that involve sequential decision-making across time and space.

Decision Making

DUFormer: Solving Power Line Detection Task in Aerial Images using Semantic Segmentation

no code implementations12 Apr 2023 Deyu An, Qiang Zhang, Jianshu Chao, Ting Li, Feng Qiao, Yong Deng, ZhenPeng Bian

Unmanned aerial vehicles (UAVs) are frequently used for inspecting power lines and capturing high-resolution aerial images.

Inductive Bias Line Detection +2

Regularized Graph Structure Learning with Semantic Knowledge for Multi-variates Time-Series Forecasting

1 code implementation12 Oct 2022 Hongyuan Yu, Ting Li, Weichen Yu, Jianguo Li, Yan Huang, Liang Wang, Alex Liu

In this paper, we propose Regularized Graph Structure Learning (RGSL) model to incorporate both explicit prior structure and implicit structure together, and learn the forecasting deep networks along with the graph structure.

Graph Generation Graph structure learning +2

A Deep Learning Approach to Predicting Ventilator Parameters for Mechanically Ventilated Septic Patients

no code implementations21 Feb 2022 Zhijun Zeng, Zhen Hou, Ting Li, Lei Deng, Jianguo Hou, Xinran Huang, Jun Li, Meirou Sun, Yunhan Wang, Qiyu Wu, Wenhao Zheng, Hua Jiang, Qi Wang

We develop a deep learning approach to predicting a set of ventilator parameters for a mechanically ventilated septic patient using a long and short term memory (LSTM) recurrent neural network (RNN) model.

Robust Protection of III-V Nanowires in Water Splitting by a Thin Compact TiO$_2$ Layer

no code implementations16 Dec 2020 Fan Cui, Yunyan Zhang, H. Aruni Fonseka, Premrudee Promdet, Ali Imran Channa, Mingqing Wang, Xueming Xia, Sanjayan Sathasivam, Hezhuang Liu, Ivan P. Parkin, Hui Yang, Ting Li, Kwang-Leong Choy, Jiang Wu, Chris Blackman, Ana M. Sanchez, Huiyun Liu

Working as a photocathode for water splitting, they exhibited a 45% larger photocurrent density compared with un-protected counterparts and a high Faraday efficiency of 91%, and can also maintain a record-long highly-stable performance among narrow-bandgap III-V NW photoelectrodes; after 67 hours photoelectrochemical stability test reaction in strong acid electrolyte solution (pH = 1), they show no apparent indication of corrosion, which is in stark contrast to the un-protected NWs that are fully failed after 35-hours.

Mesoscale and Nanoscale Physics Chemical Physics

Dark Energy Survey Year 1 Results: Cosmological Constraints from Cluster Abundances and Weak Lensing

no code implementations25 Feb 2020 DES Collaboration, Tim Abbott, Michel Aguena, Alex Alarcon, Sahar Allam, Steve Allen, James Annis, Santiago Avila, David Bacon, Alberto Bermeo, Gary Bernstein, Emmanuel Bertin, Sunayana Bhargava, Sebastian Bocquet, David Brooks, Dillon Brout, Elizabeth Buckley-Geer, David Burke, Aurelio Carnero Rosell, Matias Carrasco Kind, Jorge Carretero, Francisco Javier Castander, Ross Cawthon, Chihway Chang, Xinyi Chen, Ami Choi, Matteo Costanzi, Martin Crocce, Luiz da Costa, Tamara Davis, Juan De Vicente, Joseph DeRose, Shantanu Desai, H. Thomas Diehl, Jörg Dietrich, Scott Dodelson, Peter Doel, Alex Drlica-Wagner, Kathleen Eckert, Tim Eifler, Jack Elvin-Poole, Juan Estrada, Spencer Everett, August Evrard, Arya Farahi, Ismael Ferrero, Brenna Flaugher, Pablo Fosalba, Josh Frieman, Juan Garcia-Bellido, Marco Gatti, Enrique Gaztanaga, David Gerdes, Tommaso Giannantonio, Paul Giles, Sebastian Grandis, Daniel Gruen, Robert Gruendl, Julia Gschwend, Gaston Gutierrez, Will Hartley, Samuel Hinton, Devon L. Hollowood, Klaus Honscheid, Ben Hoyle, Dragan Huterer, David James, Mike Jarvis, Tesla Jeltema, Margaret Johnson, Stephen Kent, Elisabeth Krause, Richard Kron, Kyler Kuehn, Nikolay Kuropatkin, Ofer Lahav, Ting Li, Christopher Lidman, Marcos Lima, Huan Lin, Niall MacCrann, Marcio Maia, Adam Mantz, Jennifer Marshall, Paul Martini, Julian Mayers, Peter Melchior, Juan Mena, Felipe Menanteau, Ramon Miquel, Joe Mohr, Robert Nichol, Brian Nord, Ricardo Ogando, Antonella Palmese, Francisco Paz-Chinchon, Andrés Plazas Malagón, Judit Prat, Markus Michael Rau, Kathy Romer, Aaron Roodman, Philip Rooney, Eduardo Rozo, Eli Rykoff, Masao Sako, Simon Samuroff, Carles Sanchez, Alexandro Saro, Vic Scarpine, Michael Schubnell, Daniel Scolnic, Santiago Serrano, Ignacio Sevilla, Erin Sheldon, J. Allyn Smith, Eric Suchyta, Molly Swanson, Gregory Tarle, Daniel Thomas, Chun-Hao To, Michael A. Troxel, Douglas Tucker, Tamas Norbert Varga, Anja von der Linden, Alistair Walker, Risa Wechsler, Jochen Weller, Reese Wilkinson, Hao-Yi Wu, Brian Yanny, Zhuowen Zhang, Joe Zuntz

We perform a joint analysis of the counts and weak lensing signal of redMaPPer clusters selected from the Dark Energy Survey (DES) Year 1 dataset.

Cosmology and Nongalactic Astrophysics

Community Detection on Mixture Multi-layer Networks via Regularized Tensor Decomposition

no code implementations10 Feb 2020 Bing-Yi Jing, Ting Li, Zhongyuan Lyu, Dong Xia

We show that the TWIST procedure can accurately detect the communities with small misclassification error as the number of nodes and/or the number of layers increases.

Community Detection Stochastic Block Model +1

Semi-supervised learning in unbalanced and heterogeneous networks

no code implementations7 Jan 2019 Ting Li, Ningchen Ying, Xianshi Yu, Bin-Yi Jing

Community detection was a hot topic on network analysis, where the main aim is to perform unsupervised learning or clustering in networks.

Clustering Community Detection

Adaptive Scaling

no code implementations2 Sep 2017 Ting Li, Bing-Yi Jing, Ningchen Ying, Xianshi Yu

Simulations are conducted to illustrate the advantages of our new scaling method.


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