no code implementations • 5 Apr 2024 • Mingyuan Zhou, Huangjie Zheng, Zhendong Wang, Mingzhang Yin, Hai Huang
We introduce Score identity Distillation (SiD), an innovative data-free method that distills the generative capabilities of pretrained diffusion models into a single-step generator.
1 code implementation • 22 Feb 2024 • Xuxi Chen, Zhendong Wang, Daouda Sow, Junjie Yang, Tianlong Chen, Yingbin Liang, Mingyuan Zhou, Zhangyang Wang
Our study starts from an empirical strategy for the light continual training of LLMs using their original pre-training data sets, with a specific focus on selective retention of samples that incur moderately high losses.
1 code implementation • 12 Feb 2024 • Yueqin Yin, Zhendong Wang, Yi Gu, Hai Huang, Weizhu Chen, Mingyuan Zhou
In the field of large language models (LLMs), aligning models with the diverse preferences of users is a critical challenge.
no code implementations • 30 Jan 2024 • Chen Bai, Zeman Shao, Guoxiang Zhang, Di Liang, Jie Yang, Zhuorui Zhang, Yujian Guo, Chengzhang Zhong, Yiqiao Qiu, Zhendong Wang, Yichen Guan, Xiaoyin Zheng, Tao Wang, Cheng Lu
Our proposed general framework encompasses three key processes: 1) integrating a realistic object into a given scene video with proper placement to ensure geometric realism; 2) estimating the sky and environmental lighting distribution and simulating realistic shadows to enhance the light realism; 3) employing a style transfer network that refines the final video output to maximize photorealism.
no code implementations • 3 Dec 2023 • Tianqi Chen, Yongfei Liu, Zhendong Wang, Jianbo Yuan, Quanzeng You, Hongxia Yang, Mingyuan Zhou
In light of the remarkable success of in-context learning in large language models, its potential extension to the vision domain, particularly with visual foundation models like Stable Diffusion, has sparked considerable interest.
1 code implementation • 12 Oct 2023 • Zhendong Wang, Ioanna Miliou, Isak Samsten, Panagiotis Papapetrou
In this paper, we formulate the novel problem of counterfactual generation for time series forecasting, and propose an algorithm, called ForecastCF, that solves the problem by applying gradient-based perturbations to the original time series.
no code implementations • 10 Oct 2023 • Huangjie Zheng, Zhendong Wang, Jianbo Yuan, Guanghan Ning, Pengcheng He, Quanzeng You, Hongxia Yang, Mingyuan Zhou
Diffusion models excel at generating photo-realistic images but come with significant computational costs in both training and sampling.
1 code implementation • NeurIPS 2023 • Mingyuan Zhou, Tianqi Chen, Zhendong Wang, Huangjie Zheng
We introduce beta diffusion, a novel generative modeling method that integrates demasking and denoising to generate data within bounded ranges.
1 code implementation • CVPR 2023 • Zhendong Wang, Jianmin Bao, Wengang Zhou, Weilun Wang, Houqiang Li
In this paper, we propose to capture both spatial and temporal artifacts in one model for face forgery detection.
no code implementations • 12 Jun 2023 • Xing Wang, Zhendong Wang, Kexin Yang, Junlan Feng, Zhiyan Song, Chao Deng, Lin Zhu
To capture the intrinsic patterns of time series, we propose a novel deep learning network architecture, named Multi-resolution Periodic Pattern Network (MPPN), for long-term series forecasting.
1 code implementation • NeurIPS 2023 • Zhendong Wang, Yifan Jiang, Yadong Lu, Yelong Shen, Pengcheng He, Weizhu Chen, Zhangyang Wang, Mingyuan Zhou
We present Prompt Diffusion, a framework for enabling in-context learning in diffusion-based generative models.
1 code implementation • NeurIPS 2023 • Zhendong Wang, Yifan Jiang, Huangjie Zheng, Peihao Wang, Pengcheng He, Zhangyang Wang, Weizhu Chen, Mingyuan Zhou
Patch Diffusion meanwhile improves the performance of diffusion models trained on relatively small datasets, $e. g.$, as few as 5, 000 images to train from scratch.
no code implementations • 17 Apr 2023 • Yuchao Chang, Wen Chen, Jun Li, Jianpo Liu, Haoran Wei, Zhendong Wang, Naofal Al-Dhahir
Network energy efficiency is a main pillar in the design and operation of wireless communication systems.
no code implementations • 12 Apr 2023 • Haojia Yu, Han Hu, Bo Xu, Qisen Shang, Zhendong Wang, Qing Zhu
Most urban applications necessitate building footprints in the form of concise vector graphics with sharp boundaries rather than pixel-wise raster images.
1 code implementation • ICCV 2023 • Zhendong Wang, Jianmin Bao, Wengang Zhou, Weilun Wang, Hezhen Hu, Hong Chen, Houqiang Li
We find that existing detectors struggle to detect images generated by diffusion models, even if we include generated images from a specific diffusion model in their training data.
1 code implementation • 28 Feb 2023 • Xing Wang, Kexin Yang, Zhendong Wang, Junlan Feng, Lin Zhu, Juan Zhao, Chao Deng
First, we apply adaptive hybrid graph learning to learn the compound spatial correlations among cell towers.
1 code implementation • Artificial Intelligence in Medicine 2023 • Zhendong Wang, Isak Samsten, Vasiliki Kougia, Panagiotis Papapetrou
In this paper, we propose a counterfactual solution MedSeqCF for preventing the mortality of three cohorts of ICU patients, by representing their electronic health records as medical event sequences, and generating counterfactuals by adopting and employing a text style-transfer technique.
3 code implementations • 12 Aug 2022 • Zhendong Wang, Jonathan J Hunt, Mingyuan Zhou
In our approach, we learn an action-value function and we add a term maximizing action-values into the training loss of the conditional diffusion model, which results in a loss that seeks optimal actions that are near the behavior policy.
1 code implementation • 14 Jun 2022 • Zhendong Wang, Ruijiang Gao, Mingzhang Yin, Mingyuan Zhou, David M. Blei
This paper proposes probabilistic conformal prediction (PCP), a predictive inference algorithm that estimates a target variable by a discontinuous predictive set.
3 code implementations • 5 Jun 2022 • Zhendong Wang, Huangjie Zheng, Pengcheng He, Weizhu Chen, Mingyuan Zhou
Both the observed and generated data are diffused by the same adaptive diffusion process.
Ranked #1 on Image Generation on LSUN Bedroom 256 x 256
no code implementations • 19 Apr 2022 • Zhuoran Li, Xing Wang, Ling Pan, Lin Zhu, Zhendong Wang, Junlan Feng, Chao Deng, Longbo Huang
A2C-GS consists of three novel components, including a verifier to validate the correctness of a generated network topology, a graph neural network (GNN) to efficiently approximate topology rating, and a DRL actor layer to conduct a topology search.
no code implementations • 21 Mar 2022 • Xiaodong Cun, Zhendong Wang, Chi-Man Pun, Jianzhuang Liu, Wengang Zhou, Xu Jia, Houqiang Li
Color constancy aims to restore the constant colors of a scene under different illuminants.
no code implementations • 22 Feb 2022 • Xiaoming Zeng, Zhendong Wang, Yang Hu
We also propose a Layer-sharing technique in the deep layer that can achieve better accuracy with less computational overhead.
no code implementations • 19 Feb 2022 • Shentao Yang, Zhendong Wang, Huangjie Zheng, Yihao Feng, Mingyuan Zhou
For training more effective agents, we propose a framework that supports learning a flexible yet well-regularized fully-implicit policy.
1 code implementation • International Conference on Discovery Science 2021 • Zhendong Wang, Isak Samsten, Rami Mochaourab, Panagiotis Papapetrou
Counterfactual explanations can provide sample-based explanations of features required to modify from the original sample to change the classification result from an undesired state to a desired state; hence it provides interpretability of the model.
no code implementations • 29 Sep 2021 • Shentao Yang, Zhendong Wang, Huangjie Zheng, Mingyuan Zhou
For training more effective agents, we propose a framework that supports learning a flexible and well-regularized policy, which consists of a fully implicit policy and a regularization through the state-action visitation frequency induced by the current policy and that induced by the data-collecting behavior policy.
1 code implementation • International Conference on Artificial Intelligence in Medicine 2021 • Zhendong Wang, Isak Samsten, Panagiotis Papapetrou
In recent years, machine learning methods have been rapidly implemented in the medical domain.
4 code implementations • CVPR 2022 • Zhendong Wang, Xiaodong Cun, Jianmin Bao, Wengang Zhou, Jianzhuang Liu, Houqiang Li
Powered by these two designs, Uformer enjoys a high capability for capturing both local and global dependencies for image restoration.
Ranked #2 on Deblurring on RealBlur-R (trained on GoPro)
no code implementations • 17 Oct 2020 • Yunchao Wei, Shuai Zheng, Ming-Ming Cheng, Hang Zhao, LiWei Wang, Errui Ding, Yi Yang, Antonio Torralba, Ting Liu, Guolei Sun, Wenguan Wang, Luc van Gool, Wonho Bae, Junhyug Noh, Jinhwan Seo, Gunhee Kim, Hao Zhao, Ming Lu, Anbang Yao, Yiwen Guo, Yurong Chen, Li Zhang, Chuangchuang Tan, Tao Ruan, Guanghua Gu, Shikui Wei, Yao Zhao, Mariia Dobko, Ostap Viniavskyi, Oles Dobosevych, Zhendong Wang, Zhenyuan Chen, Chen Gong, Huanqing Yan, Jun He
The purpose of the Learning from Imperfect Data (LID) workshop is to inspire and facilitate the research in developing novel approaches that would harness the imperfect data and improve the data-efficiency during training.
3 code implementations • NeurIPS 2020 • Yuguang Yue, Zhendong Wang, Mingyuan Zhou
To improve the sample efficiency of policy-gradient based reinforcement learning algorithms, we propose implicit distributional actor-critic (IDAC) that consists of a distributional critic, built on two deep generator networks (DGNs), and a semi-implicit actor (SIA), powered by a flexible policy distribution.
1 code implementation • 21 Feb 2020 • Qing Zhu, Zhendong Wang, Han Hu, Linfu Xie, Xuming Ge, Yeting Zhang
Second, aerial models are rendered to the initial ground views, in which the color, depth and normal images are obtained.
1 code implementation • ICLR 2020 • Xinjie Fan, Yizhe Zhang, Zhendong Wang, Mingyuan Zhou
To stabilize this method, we adapt to contextual generation of categorical sequences a policy gradient estimator, which evaluates a set of correlated Monte Carlo (MC) rollouts for variance control.
1 code implementation • ICML 2020 • Zhendong Wang, Mingyuan Zhou
Variational inference is used to approximate the posterior of the local variable, and semi-implicit structure is further introduced to enhance its expressiveness.