1 code implementation • 26 Apr 2024 • Boyang Sun, Yu Yao, Huangyuan Hao, Yumou Qiu, Kun Zhang
Applying existing test methods to the observations of $X_1$, $\tilde{X}_2$ and $X_3$ can lead to a false conclusion about the underlying conditional independence of variables $X_1$, $X_2$ and $X_3$.
1 code implementation • 13 Mar 2024 • Linjie Fu, Xia Li, Xiuding Cai, Yingkai Wang, Xueyao Wang, Yali Shen, Yu Yao
To tackle these challenges, we introduce a novel diffusion model, MD-Dose, based on the Mamba architecture for predicting radiation therapy dose distribution in thoracic cancer patients.
1 code implementation • 10 Mar 2024 • Yaoyao Zhu, Xiuding Cai, Xueyao Wang, Yu Yao
However, these approaches encounter notable limitations: image transformation-based and automated data augmentation techniques cannot implement semantic transformations, leading to a constrained variety of augmented samples, and generative data augmentation methods are computationally expensive.
no code implementations • 11 Dec 2023 • Linjie Fu, Xia Li, Xiuding Cai, Yingkai Wang, Xueyao Wang, Yu Yao, Yali Shen
To address these limitations, we propose a dose prediction diffusion model based on SwinTransformer and a projector, SP-DiffDose.
1 code implementation • 9 Oct 2023 • Yaosen Chen, Yu Yao, Zhiqiang Li, Wei Wang, Yanru Zhang, Han Yang, Xuming Wen
First, FaceEncoder is used to obtain latent code by extracting features from the visual face information taken from the video source containing the face frame. Then, HyperConv, which weighting parameters are updated by HyperNet with the audio features as input, will modify the latent code to synchronize the lip movement with the audio.
no code implementations • 11 Sep 2023 • Ali Keysan, Andreas Look, Eitan Kosman, Gonca Gürsun, Jörg Wagner, Yu Yao, Barbara Rakitsch
In autonomous driving tasks, scene understanding is the first step towards predicting the future behavior of the surrounding traffic participants.
no code implementations • 7 Aug 2023 • Linjie Fu, Xia Li, Xiuding Cai, Dong Miao, Yu Yao, Yali Shen
Cone Beam CT (CBCT) plays a crucial role in Adaptive Radiation Therapy (ART) by accurately providing radiation treatment when organ anatomy changes occur.
1 code implementation • 26 Jul 2023 • Wenjie Xuan, Shanshan Zhao, Yu Yao, Juhua Liu, Tongliang Liu, Yixin Chen, Bo Du, DaCheng Tao
Exploiting the estimated noise transitions, our model, named PNT-Edge, is able to fit the prediction to clean labels.
no code implementations • 17 Mar 2023 • Xiuding Cai, Jiao Chen, Yaoyao Zhu, Beimin Wang, Yu Yao
In this paper, Policy Constraint Q-Learning (PCQL), a data-driven reinforcement learning algorithm for solving the problem of learning anesthesia strategies on real clinical datasets, is proposed.
1 code implementation • 20 Nov 2022 • Xiuding Cai, Yaoyao Zhu, Dong Miao, Linjie Fu, Yu Yao
In this paper, we propose EnCo, a simple but efficient way to maintain the content by constraining the representational similarity in the latent space of patch-level features from the same stage of the \textbf{En}coder and de\textbf{Co}der of the generator.
no code implementations • 13 Sep 2022 • Hao Luan, Yu Yao, Chang Huang
A domain specific memory architecture is essential to achieve the above goals.
no code implementations • 16 Jun 2022 • Lianyang Ma, Yu Yao, Tao Liang, Tongliang Liu
On the whole, the "multi-scale" mechanism is capable of exploiting the different levels of semantic information of each modality which are used for fine-grained crossmodal interactions.
1 code implementation • 19 Mar 2022 • Yu Yao, Chao Cao, Stephan Haas, Mahak Agarwal, Divyam Khanna, Marcin Abram
We focus on the question of how the emulator learns the rules of quantum dynamics from the curriculum of simple training examples and to which extent it can generalize the acquired knowledge to solve more challenging cases.
no code implementations • 30 Jan 2022 • Yexiong Lin, Yu Yao, Yuxuan Du, Jun Yu, Bo Han, Mingming Gong, Tongliang Liu
Algorithms which minimize the averaged loss have been widely designed for dealing with noisy labels.
no code implementations • 29 Sep 2021 • Yu Yao, Xuefeng Li, Tongliang Liu, Alan Blair, Mingming Gong, Bo Han, Gang Niu, Masashi Sugiyama
Existing methods for learning with noisy labels can be generally divided into two categories: (1) sample selection and label correction based on the memorization effect of neural networks; (2) loss correction with the transition matrix.
2 code implementations • NeurIPS 2021 • Yu Yao, Tongliang Liu, Mingming Gong, Bo Han, Gang Niu, Kun Zhang
In particular, we show that properly modeling the instances will contribute to the identifiability of the label noise transition matrix and thus lead to a better classifier.
1 code implementation • 10 May 2021 • Yu Yao, Ella Atkins, Matthew Johnson Roberson, Ram Vasudevan, Xiaoxiao Du
In this work, we follow the neuroscience and psychological literature to define pedestrian crossing behavior as a combination of an unobserved inner will (a probabilistic representation of binary intent of crossing vs. not crossing) and a set of multi-class actions (e. g., walking, standing, etc.).
no code implementations • 3 Jan 2021 • Ryan Feng, Yu Yao, Ella Atkins
An updated SBB pipeline is proposed for the real-time capture of driving video data.
no code implementations • 10 Dec 2020 • Yu Yao, Klaas E. Stephan
Specifically, we introduce a class of proposal distributions which aims to capture the interdependencies between the parameters of the clustering and subject-wise generative models and helps to reduce random walk behaviour of the MCMC scheme.
no code implementations • 6 Dec 2020 • Zhonghua Zheng, Joseph Ching, Jeffrey H. Curtis, Yu Yao, Peng Xu, Matthew West, Nicole Riemer
Here we developed a simple but effective unsupervised learning approach to regionalize predictions of global aerosol mixing state indices.
1 code implementation • 29 Jul 2020 • Yu Yao, Ella Atkins, Matthew Johnson-Roberson, Ram Vasudevan, Xiaoxiao Du
BiTraP estimates the goal (end-point) of trajectories and introduces a novel bi-directional decoder to improve longer-term trajectory prediction accuracy.
Ranked #2 on Trajectory Prediction on JAAD
1 code implementation • NeurIPS 2020 • Yu Yao, Tongliang Liu, Bo Han, Mingming Gong, Jiankang Deng, Gang Niu, Masashi Sugiyama
By this intermediate class, the original transition matrix can then be factorized into the product of two easy-to-estimate transition matrices.
3 code implementations • 6 Apr 2020 • Yu Yao, Xizi Wang, Mingze Xu, Zelin Pu, Ella Atkins, David Crandall
A new spatial-temporal area under curve (STAUC) evaluation metric is proposed and used with DoTA.
no code implementations • ICLR 2022 • Yu Yao, Tongliang Liu, Bo Han, Mingming Gong, Gang Niu, Masashi Sugiyama, DaCheng Tao
Hitherto, the distributional-assumption-free CPE methods rely on a critical assumption that the support of the positive data distribution cannot be contained in the support of the negative data distribution.
3 code implementations • 2 Mar 2019 • Yu Yao, Mingze Xu, Yuchen Wang, David J. Crandall, Ella M. Atkins
Recognizing abnormal events such as traffic violations and accidents in natural driving scenes is essential for successful autonomous driving and advanced driver assistance systems.
Ranked #1 on Traffic Accident Detection on A3D
2 code implementations • 19 Sep 2018 • Yu Yao, Mingze Xu, Chiho Choi, David J. Crandall, Ella M. Atkins, Behzad Dariush
Predicting the future location of vehicles is essential for safety-critical applications such as advanced driver assistance systems (ADAS) and autonomous driving.