no code implementations • 27 Nov 2023 • Jian Gao, Chun Gu, Youtian Lin, Hao Zhu, Xun Cao, Li Zhang, Yao Yao
We present a novel differentiable point-based rendering framework for material and lighting decomposition from multi-view images, enabling editing, ray-tracing, and real-time relighting of the 3D point cloud.
no code implementations • 23 Nov 2023 • Hao Zhu, Brice De La Crompe, Gabriel Kalweit, Artur Schneider, Maria Kalweit, Ilka Diester, Joschka Boedecker
In advancing the understanding of decision-making processes, mathematical models, particularly Inverse Reinforcement Learning (IRL), have proven instrumental in reconstructing animal's multiple intentions amidst complex behaviors.
no code implementations • 27 Oct 2023 • Yifei Zhang, Hao Zhu, Jiahong Liu, Piotr Koniusz, Irwin King
We show that in the hyperbolic space one has to address the leaf- and height-level uniformity which are related to properties of trees, whereas in the ambient space of the hyperbolic manifold, these notions translate into imposing an isotropic ring density towards boundaries of Poincar\'e ball.
no code implementations • 18 Oct 2023 • Xuhui Zhou, Hao Zhu, Leena Mathur, Ruohong Zhang, Haofei Yu, Zhengyang Qi, Louis-Philippe Morency, Yonatan Bisk, Daniel Fried, Graham Neubig, Maarten Sap
We present SOTOPIA, an open-ended environment to simulate complex social interactions between artificial agents and evaluate their social intelligence.
no code implementations • 14 Oct 2023 • Jianhui Yu, Hao Zhu, Liming Jiang, Chen Change Loy, Weidong Cai, Wayne Wu
We first propose a novel score function, Denoised Score Distillation (DSD), which directly modifies the SDS by introducing negative gradient components to iteratively correct the gradient direction and generate high-quality textures.
no code implementations • 4 Oct 2023 • Chengkang Shen, Hao Zhu, You Zhou, Yu Liu, Si Yi, Lili Dong, Weipeng Zhao, David J. Brady, Xun Cao, Zhan Ma, Yi Lin
Myocardial motion tracking stands as an essential clinical tool in the prevention and detection of Cardiovascular Diseases (CVDs), the foremost cause of death globally.
no code implementations • 2 Oct 2023 • Shaohui Liu, Hao Zhu, Vassilis Kekatos
Poorly damped oscillations pose threats to the stability and reliability of interconnected power systems.
no code implementations • 22 Sep 2023 • Hao Zhu, Fengyi Liu, Qi Zhang, Xun Cao, Zhan Ma
This connection ensures a seamless backpropagation of gradients from the network's output back to the input coordinates, thereby enhancing regularization.
no code implementations • 19 Sep 2023 • Yiyu Zhuang, Qi Zhang, Ying Feng, Hao Zhu, Yao Yao, Xiaoyu Li, Yan-Pei Cao, Ying Shan, Xun Cao
Drawing inspiration from voxel-based representations with the level of detail (LoD), we introduce a multi-scale tri-plane-based scene representation that is capable of capturing the LoD of the signed distance function (SDF) and the space radiance.
no code implementations • 25 Jul 2023 • Shuyan Zhou, Frank F. Xu, Hao Zhu, Xuhui Zhou, Robert Lo, Abishek Sridhar, Xianyi Cheng, Tianyue Ou, Yonatan Bisk, Daniel Fried, Uri Alon, Graham Neubig
Building upon our environment, we release a set of benchmark tasks focusing on evaluating the functional correctness of task completions.
no code implementations • 24 Jul 2023 • Young-ho Cho, Hao Zhu
Effective power flow modeling critically affects the ability to efficiently solve large-scale grid optimization problems, especially those with topology-related decision variables.
no code implementations • 25 Jun 2023 • Minxue Xia, Hao Zhu
Many methods employ sparse representation to learn interpretable word embeddings for better interpretability.
no code implementations • 23 Jun 2023 • Qi Yang, Hao Zhu
A suitable Markov Chain can be defined on the self-representation and it allows us to recognize the difference between inliers and outliers.
no code implementations • 16 Jun 2023 • Yifei Zeng, Yuanxun Lu, Xinya Ji, Yao Yao, Hao Zhu, Xun Cao
Unlike previous approaches that can only synthesize avatars based on simple text descriptions, our method enables the creation of personalized avatars from casually captured face or body images, while still supporting text-based model generation and editing.
no code implementations • 3 Jun 2023 • Xuhui Zhou, Hao Zhu, Akhila Yerukola, Thomas Davidson, Jena D. Hwang, Swabha Swayamdipta, Maarten Sap
To study the contextual dynamics of offensiveness, we train models to generate COBRA explanations, with and without access to the context.
1 code implementation • 23 May 2023 • Abishek Sridhar, Robert Lo, Frank F. Xu, Hao Zhu, Shuyan Zhou
Large language models (LLMs) struggle on processing complicated observations in interactive decision making tasks.
1 code implementation • CVPR 2023 • Menghua Wu, Hao Zhu, Linjia Huang, Yiyu Zhuang, Yuanxun Lu, Xun Cao
Synthesizing high-quality 3D face models from natural language descriptions is very valuable for many applications, including avatar creation, virtual reality, and telepresence.
1 code implementation • CVPR 2023 • Hao Zhu, Piotr Koniusz
In this paper, we propose a novel prototype-based label propagation to solve these issues.
no code implementations • 18 Apr 2023 • Yiyu Zhuang, Qi Zhang, Xuan Wang, Hao Zhu, Ying Feng, Xiaoyu Li, Ying Shan, Xun Cao
Recent advances in implicit neural representation have demonstrated the ability to recover detailed geometry and material from multi-view images.
no code implementations • 6 Apr 2023 • Changsheng Lu, Hao Zhu, Piotr Koniusz
Unlike current deep keypoint detectors that are trained to recognize limited number of body parts, few-shot keypoint detection (FSKD) attempts to localize any keypoints, including novel or base keypoints, depending on the reference samples.
no code implementations • 3 Apr 2023 • Hao Zhu, Shaowen Xie, Zhen Liu, Fengyi Liu, Qi Zhang, You Zhou, Yi Lin, Zhan Ma, Xun Cao
However, the expressive power of INR is limited by the spectral bias in the network training.
1 code implementation • CVPR 2023 • Jianhui Yu, Hao Zhu, Liming Jiang, Chen Change Loy, Weidong Cai, Wayne Wu
This paper presents CelebV-Text, a large-scale, diverse, and high-quality dataset of facial text-video pairs, to facilitate research on facial text-to-video generation tasks.
no code implementations • 14 Mar 2023 • Yuqi Zhou, Kaarthik Sundar, Deepjyoti Deka, Hao Zhu
Wildfires pose a significant threat to the safe and reliable operation of electric power systems.
1 code implementation • 2 Mar 2023 • Andy Liu, Hao Zhu, Emmy Liu, Yonatan Bisk, Graham Neubig
We also find some evidence that increasing task difficulty in the training process results in more fluent and precise utterances in evaluation.
1 code implementation • 10 Feb 2023 • Longwei Guo, Hao Zhu, Yuanxun Lu, Menghua Wu, Xun Cao
We propose a robust and accurate non-parametric method for single-view 3D face reconstruction (SVFR).
no code implementations • CVPR 2023 • Hao Zhu, Raghav Kapoor, So Yeon Min, Winson Han, Jiatai Li, Kaiwen Geng, Graham Neubig, Yonatan Bisk, Aniruddha Kembhavi, Luca Weihs
Humans constantly explore and learn about their environment out of curiosity, gather information, and update their models of the world.
no code implementations • 19 Dec 2022 • Young-ho Cho, Shaohui Liu, Duehee Lee, Hao Zhu
Generating wind power scenarios is very important for studying the impacts of multiple wind farms that are interconnected to the grid.
no code implementations • 2 Dec 2022 • Yifei Zhang, Hao Zhu, Zixing Song, Piotr Koniusz, Irwin King
Although augmentations (e. g., perturbation of graph edges, image crops) boost the efficiency of Contrastive Learning (CL), feature level augmentation is another plausible, complementary yet not well researched strategy.
no code implementations • CVPR 2023 • Shaowen Xie, Hao Zhu, Zhen Liu, Qi Zhang, You Zhou, Xun Cao, Zhan Ma
Implicit neural representation (INR) characterizes the attributes of a signal as a function of corresponding coordinates which emerges as a sharp weapon for solving inverse problems.
1 code implementation • 10 Oct 2022 • So Yeon Min, Hao Zhu, Ruslan Salakhutdinov, Yonatan Bisk
We provide empirical comparisons of metrics, analysis of three models, and make suggestions for how the field might best progress.
1 code implementation • 22 Sep 2022 • Shaohui Liu, Hao Zhu, Vassilis Kekatos
Wide-area dynamic studies are of paramount importance to ensure the stability and reliability of power grids.
1 code implementation • 25 Jul 2022 • Hao Zhu, Wayne Wu, Wentao Zhu, Liming Jiang, Siwei Tang, Li Zhang, Ziwei Liu, Chen Change Loy
Large-scale datasets have played indispensable roles in the recent success of face generation/editing and significantly facilitated the advances of emerging research fields.
Ranked #1 on
Unconditional Video Generation
on CelebV-HQ
no code implementations • 12 Jun 2022 • Hao Zhu, Wan-Jing Nie, Yue-Jie Hou, Qi-Meng Du, Si-Jing Li, Chi-Chun Zhou
In this paper, based on the convolutional auto-encoder with constraints (CCAE), an unsupervised deep-learning model proposed in the classification of the fingerprint, we propose this model for the classification of the bone age and baptize it BA-CCAE.
1 code implementation • 9 Jun 2022 • Yifei Zhang, Hao Zhu, Zixing Song, Piotr Koniusz, Irwin King
In this paper, we show that the node embedding obtained via the graph augmentations is highly biased, somewhat limiting contrastive models from learning discriminative features for downstream tasks.
1 code implementation • 16 May 2022 • Shaohui Liu, Chengyang Wu, Hao Zhu
We develop a new topology-informed graph neural network (GNN) approach for predicting the optimal solutions of real-time ac-OPF problem.
1 code implementation • 13 Apr 2022 • Haiming Yu, Hao Zhu, Xiangju Lu, Junhui Liu
In this work, we propose MobileFSGAN, a novel lightweight GAN for face swap that can run on mobile devices with much fewer parameters while achieving competitive performance.
no code implementations • 1 Apr 2022 • Yaning Li, Xue Wang, Hao Zhu, Guoqing Zhou, Qing Wang
Existing light field representations, such as epipolar plane image (EPI) and sub-aperture images, do not consider the structural characteristics across the views, so they usually require additional disparity and spatial structure cues for follow-up tasks.
no code implementations • 25 Mar 2022 • Xinmeng Li, Hao Zhu, Li-Ping Liu, Soha Hassoun
We show that annotation performance, for ESP and other models, is a strong function of the number of molecules in the candidate set and their similarity to the target molecule.
no code implementations • 24 Mar 2022 • Jialin Wang, Rui Gao, Haotian Zheng, Hao Zhu, C. -J. Richard Shi
Compared with the existing literature, our WNFG of EEG signals achieves up to 10 times of redundant edge reduction, and our approach achieves up to 97 times of model pruning without loss of classification accuracy.
no code implementations • 13 Feb 2022 • Yifei Zhang, Hao Zhu, Ziqiao Meng, Piotr Koniusz, Irwin King
However, in the updating stage, all nodes share the same updating function.
1 code implementation • NeurIPS 2021 • Hao Zhu, Ke Sun, Piotr Koniusz
Starting from a GAN-inspired contrastive formulation, we show that the Jensen-Shannon divergence underlying many contrastive graph embedding models fails under disjoint positive and negative distributions, which may naturally emerge during sampling in the contrastive setting.
1 code implementation • 4 Jan 2022 • Yunze Xiao, Hao Zhu, Haotian Yang, Zhengyu Diao, Xiangju Lu, Xun Cao
By fitting a 3D morphable model from multi-view images, the features of multiple images are extracted and aggregated in the mesh-attached UV space, which makes the implicit function more effective in recovering detailed facial shape.
1 code implementation • CVPR 2022 • Hao Zhu, Piotr Koniusz
We present an unsupErvised discriminAnt Subspace lEarning (EASE) that improves transductive few-shot learning performance by learning a linear projection onto a subspace built from features of the support set and the unlabeled query set in the test time.
1 code implementation • 4 Dec 2021 • Yiyu Zhuang, Hao Zhu, Xusen Sun, Xun Cao
To the best of our knowledge, our work is the first facial parametric model built upon a neural radiance field that can be used in fitting, generation and manipulation.
no code implementations • 23 Nov 2021 • Yuqi Zhou, Jeehyun Park, Hao Zhu
Effective and timely responses to unexpected contingencies are crucial for enhancing the resilience of power grids.
no code implementations • 23 Nov 2021 • Yuqi Zhou, Arun Sukumaran Nair, David Ganger, Abhinandan Tripathi, Chaitanya Baone, Hao Zhu
Accurate load forecasting is critical for electricity market operations and other real-time decision-making tasks in power systems.
1 code implementation • 1 Nov 2021 • Hao Zhu, Haotian Yang, Longwei Guo, Yidi Zhang, Yanru Wang, Mingkai Huang, Menghua Wu, Qiu Shen, Ruigang Yang, Xun Cao
By training on FaceScape data, a novel algorithm is proposed to predict elaborate riggable 3D face models from a single image input.
no code implementations • 14 Oct 2021 • Lintao Ye, Hao Zhu, Vijay Gupta
We study the problem of control policy design for decentralized state-feedback linear quadratic control with a partially nested information structure, when the system model is unknown.
1 code implementation • 4 Oct 2021 • Shanny Lin, Shaohui Liu, Hao Zhu
Real-time coordination of distributed energy resources (DERs) is crucial for regulating the voltage profile in distribution grids.
no code implementations • 29 Sep 2021 • Hao Zhu, Mahashweta Das, Mangesh Bendre, Fei Wang, Hao Yang, Soha Hassoun
In this work, we propose an adversarial training based modification to the current state-of-the-arts link prediction method to solve this problem.
1 code implementation • CoNLL (EMNLP) 2021 • Ruisi Su, Shruti Rijhwani, Hao Zhu, Junxian He, Xinyu Wang, Yonatan Bisk, Graham Neubig
Our experiments find that concreteness is a strong indicator for learning dependency grammars, improving the direct attachment score (DAS) by over 50\% as compared to state-of-the-art models trained on pure text.
no code implementations • 24 Aug 2021 • Hao Zhu, Piotr Koniusz
Moreover, we design a simple but efficient spectral filter for network enhancement to obtain higher-order information for node representation.
1 code implementation • 20 Aug 2021 • Xiaopeng Lu, Lynnette Ng, Jared Fernandez, Hao Zhu
Instead of generating an image based on text as in text-image generation, this task requires the generation of an image from a textual description and an image prompt.
no code implementations • 18 Aug 2021 • Shanny Lin, Hao Zhu
Accurately modeling power distribution grids is crucial for designing effective monitoring and decision making algorithms.
no code implementations • 7 Aug 2021 • Kyung-bin Kwon, Hao Zhu
Effectively operating electrical vehicle charging station (EVCS) is crucial for enabling the rapid transition of electrified transportation.
no code implementations • 6 Aug 2021 • Hao Zhu, Xinxin Zuo, Haotian Yang, Sen Wang, Xun Cao, Ruigang Yang
In this paper, we propose a novel learning-based framework that combines the robustness of the parametric model with the flexibility of free-form 3D deformation.
no code implementations • 24 Jul 2021 • Hao Zhu, Piotr Koniusz
Although Graph Convolutional Networks (GCNs) have demonstrated their power in various applications, the graph convolutional layers, as the most important component of GCN, are still using linear transformations and a simple pooling step.
no code implementations • 12 Jul 2021 • Hao Zhu, Graham Neubig, Yonatan Bisk
Positive results from our experiments hint at the importance of explicitly modeling communication as a socio-pragmatic progress.
1 code implementation • 19 Jun 2021 • Shaohui Liu, Chengyang Wu, Hao Zhu
Solving the optimal power flow (OPF) problem in real-time electricity market improves the efficiency and reliability in the integration of low-carbon energy resources into the power grids.
no code implementations • 26 May 2021 • Mana Jalali, Vassilis Kekatos, Siddharth Bhela, Hao Zhu, Virgilio Centeno
Synchrophasor data provide unprecedented opportunities for inferring power system dynamics, such as estimating voltage angles, frequencies, and accelerations along with power injection at all buses.
1 code implementation • 12 Apr 2021 • Shaohui Liu, Hao Zhu, Vassilis Kekatos
Wide-area dynamic studies are of paramount importance to ensure the stability and reliability of power grids.
no code implementations • 15 Feb 2021 • Shanny Lin, Hao Zhu
The load recovery solutions can be utilized to identify the EV charging events at each load node and to infer the total behind-the-meter PV output.
no code implementations • 23 Jan 2021 • Yaning Li, Xue Wang, Hao Zhu, Guoqing Zhou, Qing Wang
Based on these two observations, we propose a learning-based FSS reconstruction approach for one-time aliasing removing over the whole focal stack.
2 code implementations • ICLR 2021 • Hao Zhu, Piotr Koniusz
Our spectral analysis shows that our simple spectral graph convolution used in S^2GC is a low-pass filter which partitions networks into a few large parts.
Ranked #1 on
Node Clustering
on Wiki
no code implementations • 23 Nov 2020 • Hao Zhu, Yang Yuan, Guosheng Hu, Xiang Wu, Neil Robertson
IR-Softmax can generalise to any softmax and its variants (which are discriminative for open-set problem) by directly setting the weights as their class centers, naturally solving the data imbalance problem.
no code implementations • 5 Nov 2020 • Hao Zhu, Yi Li, Feixia Zhu, Aihua Zheng, Ran He
We propose a new task named Audio-driven Per-formance Video Generation (APVG), which aims to synthesizethe video of a person playing a certain instrument guided bya given music audio clip.
no code implementations • NeurIPS 2020 • Hao Zhu, Chaoyou Fu, Qianyi Wu, Wayne Wu, Chen Qian, Ran He
However, due to the lack of Deepfakes datasets with large variance in appearance, which can be hardly produced by recent identity swapping methods, the detection algorithm may fail in this situation.
1 code implementation • NeurIPS 2020 • Nitin Kamra, Hao Zhu, Dweep Trivedi, Ming Zhang, Yan Liu
Trajectory prediction for scenes with multiple agents and entities is a challenging problem in numerous domains such as traffic prediction, pedestrian tracking and path planning.
no code implementations • 9 Oct 2020 • Hao Zhu, LiPing Liu, Soha Hassoun
We compare our results to NEIMS, a neural network model that utilizes molecular fingerprints as inputs.
3 code implementations • 29 Jul 2020 • Hao Zhu, Yonatan Bisk, Graham Neubig
In this paper we demonstrate that $\textit{context free grammar (CFG) based methods for grammar induction benefit from modeling lexical dependencies}$.
1 code implementation • 17 Jul 2020 • Miao Liao, Sibo Zhang, Peng Wang, Hao Zhu, Xinxin Zuo, Ruigang Yang
In this paper, we propose a novel approach to convert given speech audio to a photo-realistic speaking video of a specific person, where the output video has synchronized, realistic, and expressive rich body dynamics.
no code implementations • 14 Jul 2020 • Yifei Zhang, Hao Zhu
For this scheme, we propose a novel privacy-preserving architecture where two parties can collaboratively train a deep learning model efficiently while preserving the privacy of each party's data.
1 code implementation • CVPR 2020 • Feitong Tan, Hao Zhu, Zhaopeng Cui, Siyu Zhu, Marc Pollefeys, Ping Tan
Previous methods on estimating detailed human depth often require supervised training with `ground truth' depth data.
1 code implementation • CVPR 2020 • Haotian Yang, Hao Zhu, Yanru Wang, Mingkai Huang, Qiu Shen, Ruigang Yang, Xun Cao
In this paper, we present a large-scale detailed 3D face dataset, FaceScape, and propose a novel algorithm that is able to predict elaborate riggable 3D face models from a single image input.
1 code implementation • CVPR 2020 • Fanbo Xiang, Yuzhe Qin, Kaichun Mo, Yikuan Xia, Hao Zhu, Fangchen Liu, Minghua Liu, Hanxiao Jiang, Yifu Yuan, He Wang, Li Yi, Angel X. Chang, Leonidas J. Guibas, Hao Su
To achieve this task, a simulated environment with physically realistic simulation, sufficient articulated objects, and transferability to the real robot is indispensable.
no code implementations • 14 Jan 2020 • Hao Zhu, Mandi Luo, Rui Wang, Aihua Zheng, Ran He
Audio-visual learning, aimed at exploiting the relationship between audio and visual modalities, has drawn considerable attention since deep learning started to be used successfully.
no code implementations • 23 Dec 2019 • Yuxiang Ren, Hao Zhu, Jiawei Zhang, Peng Dai, Liefeng Bo
Existing fraud detection methods try to identify unexpected dense subgraphs and treat related nodes as suspicious.
1 code implementation • 31 Oct 2019 • Yuzhe Qin, Rui Chen, Hao Zhu, Meng Song, Jing Xu, Hao Su
Grasping is among the most fundamental and long-lasting problems in robotics study.
1 code implementation • IJCNLP 2019 • Tianyu Gao, Xu Han, Hao Zhu, Zhiyuan Liu, Peng Li, Maosong Sun, Jie zhou
We present FewRel 2. 0, a more challenging task to investigate two aspects of few-shot relation classification models: (1) Can they adapt to a new domain with only a handful of instances?
2 code implementations • 26 Sep 2019 • Jianqiang Wang, Hao Zhu, Zhan Ma, Tong Chen, Haojie Liu, Qiu Shen
This paper presents a novel end-to-end Learned Point Cloud Geometry Compression (a. k. a., Learned-PCGC) framework, to efficiently compress the point cloud geometry (PCG) using deep neural networks (DNN) based variational autoencoders (VAE).
1 code implementation • ACL 2019 • Weize Chen, Hao Zhu, Xu Han, Zhiyuan Liu, Maosong Sun
We introduce a conceptually simple and effective method to quantify the similarity between relations in knowledge bases.
2 code implementations • 22 Jun 2019 • Weiping Song, Zhijian Duan, Ziqing Yang, Hao Zhu, Ming Zhang, Jian Tang
Recently, a variety of methods have been developed for this problem, which generally try to learn effective representations of users and items and then match items to users according to their representations.
Ranked #1 on
Recommendation Systems
on Last.FM
no code implementations • 19 Jun 2019 • Kaiqing Zhang, Alec Koppel, Hao Zhu, Tamer Başar
Under a further strict saddle points assumption, this result establishes convergence to essentially locally-optimal policies of the underlying problem, and thus bridges the gap in existing literature on the convergence of PG methods.
1 code implementation • NAACL 2019 • Yifei Zhang, Hao Zhu
However, the discrete stochastic layer is usually incompatible with the backpropagation in the training stage, and thus causes a gradient flow problem because of non-differentiable operators.
no code implementations • NAACL 2019 • Chu-Cheng Lin, Hao Zhu, Matthew R. Gormley, Jason Eisner
We introduce neural finite state transducers (NFSTs), a family of string transduction models defining joint and conditional probability distributions over pairs of strings.
1 code implementation • CVPR 2019 • Hao Zhu, Xinxin Zuo, Sen Wang, Xun Cao, Ruigang Yang
This paper presents a novel framework to recover detailed human body shapes from a single image.
no code implementations • 15 Feb 2019 • Hao Zhu, Mantang Guo, Hongdong Li, Qing Wang, Antonio Robles-Kelly
We prove that the light field is a 2D series, thus, a specifically designed CNN-LSTM network is proposed to capture the continuity property of the EPI.
1 code implementation • ACL 2019 • Hao Zhu, Yankai Lin, Zhiyuan Liu, Jie Fu, Tat-Seng Chua, Maosong Sun
Recently, progress has been made towards improving relational reasoning in machine learning field.
no code implementations • 17 Dec 2018 • Hao Zhu, Huaibo Huang, Yi Li, Aihua Zheng, Ran He
Talking face generation aims to synthesize a face video with precise lip synchronization as well as a smooth transition of facial motion over the entire video via the given speech clip and facial image.
3 code implementations • CVPR 2019 • Jiefeng Li, Can Wang, Hao Zhu, Yihuan Mao, Hao-Shu Fang, Cewu Lu
In this paper, we propose a novel and efficient method to tackle the problem of pose estimation in the crowd and a new dataset to better evaluate algorithms.
Ranked #6 on
Multi-Person Pose Estimation
on OCHuman
1 code implementation • EMNLP 2018 • Yihong Gu, Jun Yan, Hao Zhu, Zhiyuan Liu, Ruobing Xie, Maosong Sun, Fen Lin, Leyu Lin
Most language modeling methods rely on large-scale data to statistically learn the sequential patterns of words.
1 code implementation • EMNLP 2018 • Xu Han, Hao Zhu, Pengfei Yu, ZiYun Wang, Yuan YAO, Zhiyuan Liu, Maosong Sun
The relation of each sentence is first recognized by distant supervision methods, and then filtered by crowdworkers.
1 code implementation • EMNLP 2018 • Ji Xin, Hao Zhu, Xu Han, Zhiyuan Liu, Maosong Sun
Entity typing aims to classify semantic types of an entity mention in a specific context.
1 code implementation • EMNLP 2018 • Fanchao Qi, Yankai Lin, Maosong Sun, Hao Zhu, Ruobing Xie, Zhiyuan Liu
We propose a novel framework to model correlations between sememes and multi-lingual words in low-dimensional semantic space for sememe prediction.
1 code implementation • ACL 2018 • Huiming Jin, Hao Zhu, Zhiyuan Liu, Ruobing Xie, Maosong Sun, Fen Lin, Leyu Lin
However, existing methods of lexical sememe prediction typically rely on the external context of words to represent the meaning, which usually fails to deal with low-frequency and out-of-vocabulary words.
no code implementations • 14 Jun 2018 • Mantang Guo, Hao Zhu, Guoqing Zhou, Qing Wang
A light field records numerous light rays from a real-world scene.
no code implementations • CVPR 2018 • Hao Zhu, Hao Su, Peng Wang, Xun Cao, Ruigang Yang
We study how to synthesize novel views of human body from a single image.
no code implementations • 3 Jan 2018 • Zhiwu Lin, Jincheng Yang, Hao Zhu
The second one is to write the linearized fluid equation in a Hamiltonian form and then use an instability index theory for general Hamiltonian PDEs.
Analysis of PDEs
no code implementations • 20 Dec 2017 • Xianqiang Lv, Hao Zhu, Qing Wang
The large volume of input data and the redundancy of light field make it an open challenge.
no code implementations • CVPR 2017 • Hao Zhu, Qi Zhang, Qing Wang
Superpixel segmentation of 2D image has been widely used in many computer vision tasks.
1 code implementation • International Joint Conference on Artificial Intelligence 2017 • Hao Zhu, Ruobing Xie, Zhiyuan Liu, Maosong Sun
During this process, we can align entities according to their semantic distance in this joint semantic space.
no code implementations • 15 Aug 2016 • Hao Zhu, Qing Wang, Jingyi Yu
Occlusion is one of the most challenging problems in depth estimation.
no code implementations • 30 Mar 2015 • Georgios B. Giannakis, Qing Ling, Gonzalo Mateos, Ioannis D. Schizas, Hao Zhu
This chapter deals with decentralized learning algorithms for in-network processing of graph-valued data.