Zhijie Deng

Publication Activity (10 Years)

Years Active: 2017-2024
Publications (10 Years): 57

Top Topics

Diffusion Models

Bayesian Learning

Top Venues

Publications

Qingsong Xie, Zhenyi Liao, Chen Chen, Zhijie Deng, Shixiang Tang, Haonan Lu
MLCM: Multistep Consistency Distillation of Latent Diffusion Model. CoRR (2024)
Siqi Kou, Lanxiang Hu, Zhezhi He, Zhijie Deng, Hao Zhang
CLLMs: Consistency Large Language Models. CoRR (2024)
Hongjian Liu, Qingsong Xie, Zhijie Deng, Chen Chen, Shixiang Tang, Fueyang Fu, Zhengjun Zha, Haonan Lu
SCott: Accelerating Diffusion Models with Stochastic Consistency Distillation. CoRR (2024)
Xiaoxuan Liu, Cade Daniel, Langxiang Hu, Woosuk Kwon, Zhuohan Li, Xiangxi Mo, Alvin Cheung, Zhijie Deng, Ion Stoica, Hao Zhang
Optimizing Speculative Decoding for Serving Large Language Models Using Goodput. CoRR (2024)
Siqi Kou, Lei Gan, Dequan Wang, Chongxuan Li, Zhijie Deng
BayesDiff: Estimating Pixel-wise Uncertainty in Diffusion via Bayesian Inference. ICLR (2024)
Kang You, Zekai Xu, Chen Nie, Zhijie Deng, Qinghai Guo, Xiang Wang, Zhezhi He
SpikeZIP-TF: Conversion is All You Need for Transformer-based SNN. CoRR (2024)
Zhenyi Liao, Qingsong Xie, Chen Chen, Hannan Lu, Zhijie Deng
Fine-tuning Diffusion Models for Enhancing Face Quality in Text-to-image Generation. CoRR (2024)
Yibo Miao, Yu Lei, Feng Zhou, Zhijie Deng
Bayesian Exploration of Pre-trained Models for Low-shot Image Classification. CoRR (2024)
Yibo Miao, Hongcheng Gao, Hao Zhang, Zhijie Deng
Efficient Detection of LLM-generated Texts with a Bayesian Surrogate Model. ACL (Findings) (2024)
Zihao Zeng, Yibo Miao, Hongcheng Gao, Hao Zhang, Zhijie Deng
AdaMoE: Token-Adaptive Routing with Null Experts for Mixture-of-Experts Language Models. CoRR (2024)
Yuzi Yan, Yibo Miao, Jialian Li, Yipin Zhang, Jian Xie, Zhijie Deng, Dong Yan
3D-Properties: Identifying Challenges in DPO and Charting a Path Forward. CoRR (2024)
Xiaoxuan Liu, Lanxiang Hu, Peter Bailis, Ion Stoica, Zhijie Deng, Alvin Cheung, Hao Zhang
Online Speculative Decoding. CoRR (2023)
Peng Cui, Dan Zhang, Zhijie Deng, Yinpeng Dong, Jun Zhu
Learning Sample Difficulty from Pre-trained Models for Reliable Prediction. NeurIPS (2023)
Tianyu Pang, Cheng Lu, Chao Du, Min Lin, Shuicheng Yan, Zhijie Deng
On Calibrating Diffusion Probabilistic Models. NeurIPS (2023)
Peng Cui, Dan Zhang, Zhijie Deng, Yinpeng Dong, Jun Zhu
Learning Sample Difficulty from Pre-trained Models for Reliable Prediction. CoRR (2023)
Feng Zhou, Quyu Kong, Zhijie Deng, Fengxiang He, Peng Cui, Jun Zhu
Heterogeneous Multi-Task Gaussian Cox Processes. CoRR (2023)
Zhenyi Liao, Zhijie Deng
LOVECon: Text-driven Training-Free Long Video Editing with ControlNet. CoRR (2023)
Zhijie Deng, Yucen Luo
Learning Neural Eigenfunctions for Unsupervised Semantic Segmentation. ICCV (2023)
Zipeng Xiao, Zhongkai Hao, Bokai Lin, Zhijie Deng, Hang Su
Improved Operator Learning by Orthogonal Attention. CoRR (2023)
Tianyu Pang, Cheng Lu, Chao Du, Min Lin, Shuicheng Yan, Zhijie Deng
On Calibrating Diffusion Probabilistic Models. CoRR (2023)
Hongcheng Gao, Hao Zhang, Yinpeng Dong, Zhijie Deng
Evaluating the Robustness of Text-to-image Diffusion Models against Real-world Attacks. CoRR (2023)
Feng Zhou, Quyu Kong, Zhijie Deng, Fengxiang He, Peng Cui, Jun Zhu
Heterogeneous multi-task Gaussian Cox processes. Mach. Learn. 112 (12) (2023)
Siqi Kou, Lei Gan, Dequan Wang, Chongxuan Li, Zhijie Deng
BayesDiff: Estimating Pixel-wise Uncertainty in Diffusion via Bayesian Inference. CoRR (2023)
Peng Cui, Yang Yue, Zhijie Deng, Jun Zhu
Confidence-based Reliable Learning under Dual Noises. CoRR (2023)
Zhijie Deng, Yucen Luo
Learning Neural Eigenfunctions for Unsupervised Semantic Segmentation. CoRR (2023)
Zhijie Deng, Peng Cui, Jun Zhu
Towards Accelerated Model Training via Bayesian Data Selection. CoRR (2023)
Zhijie Deng, Peng Cui, Jun Zhu
Towards Accelerated Model Training via Bayesian Data Selection. NeurIPS (2023)
Zhijie Deng, Yinpeng Dong, Jun Zhu
Batch virtual adversarial training for graph convolutional networks. AI Open 4 (2023)
Zhijie Deng, Hongcheng Gao, Yibo Miao, Hao Zhang
Efficient Detection of LLM-generated Texts with a Bayesian Surrogate Model. CoRR (2023)
Yinpeng Dong, Ke Xu, Xiao Yang, Tianyu Pang, Zhijie Deng, Hang Su, Jun Zhu
Exploring Memorization in Adversarial Training. ICLR (2022)
Zhijie Deng, Feng Zhou, Jun Zhu
Accelerated Linearized Laplace Approximation for Bayesian Deep Learning. CoRR (2022)
Zhijie Deng, Jiaxin Shi, Jun Zhu
NeuralEF: Deconstructing Kernels by Deep Neural Networks. CoRR (2022)
Zhijie Deng, Jun Zhu
BayesAdapter: Being Bayesian, Inexpensively and Reliably, via Bayesian Fine-tuning. ACML (2022)
Zhijie Deng, Feng Zhou, Jianfei Chen, Guoqiang Wu, Jun Zhu
Deep Ensemble as a Gaussian Process Approximate Posterior. CoRR (2022)
Zhijie Deng, Jiaxin Shi, Jun Zhu
NeuralEF: Deconstructing Kernels by Deep Neural Networks. ICML (2022)
Zhijie Deng, Feng Zhou, Jun Zhu
Accelerated Linearized Laplace Approximation for Bayesian Deep Learning. NeurIPS (2022)
Zhijie Deng, Jiaxin Shi, Hao Zhang, Peng Cui, Cewu Lu, Jun Zhu
Neural Eigenfunctions Are Structured Representation Learners. CoRR (2022)
Feng Zhou, Quyu Kong, Zhijie Deng, Jichao Kan, Yixuan Zhang, Cheng Feng, Jun Zhu
Efficient Inference for Dynamic Flexible Interactions of Neural Populations. J. Mach. Learn. Res. 23 (2022)
Peng Cui, Yang Yue, Zhijie Deng, Jun Zhu
Confidence-based Reliable Learning under Dual Noises. NeurIPS (2022)
Zhijie Deng, Xiao Yang, Shizhen Xu, Hang Su, Jun Zhu
LiBRe: A Practical Bayesian Approach to Adversarial Detection. CoRR (2021)
Peng Cui, Zhijie Deng, Wenbo Hu, Jun Zhu
Accurate and Reliable Forecasting using Stochastic Differential Equations. CoRR (2021)
Yinpeng Dong, Xiao Yang, Zhijie Deng, Tianyu Pang, Zihao Xiao, Hang Su, Jun Zhu
Black-box Detection of Backdoor Attacks with Limited Information and Data. CoRR (2021)
Zhijie Deng, Xiao Yang, Shizhen Xu, Hang Su, Jun Zhu
LiBRe: A Practical Bayesian Approach to Adversarial Detection. CVPR (2021)
Yinpeng Dong, Xiao Yang, Zhijie Deng, Tianyu Pang, Zihao Xiao, Hang Su, Jun Zhu
Black-box Detection of Backdoor Attacks with Limited Information and Data. ICCV (2021)
Yinpeng Dong, Ke Xu, Xiao Yang, Tianyu Pang, Zhijie Deng, Hang Su, Jun Zhu
Exploring Memorization in Adversarial Training. CoRR (2021)
Zhijie Deng, Yinpeng Dong, Tianyu Pang, Hang Su, Jun Zhu
Adversarial Distributional Training for Robust Deep Learning. CoRR (2020)
Yinpeng Dong, Zhijie Deng, Tianyu Pang, Jun Zhu, Hang Su
Adversarial Distributional Training for Robust Deep Learning. NeurIPS (2020)
Zhijie Deng, Yinpeng Dong, Shifeng Zhang, Jun Zhu
Understanding and Exploring the Network with Stochastic Architectures. NeurIPS (2020)
Hao Zhang, Yuan Li, Zhijie Deng, Xiaodan Liang, Lawrence Carin, Eric P. Xing
AutoSync: Learning to Synchronize for Data-Parallel Distributed Deep Learning. NeurIPS (2020)
Zhijie Deng, Xiao Yang, Hao Zhang, Yinpeng Dong, Jun Zhu
BayesAdapter: Being Bayesian, Inexpensively and Robustly, via Bayeisan Fine-tuning. CoRR (2020)
Zhijie Deng, Yucen Luo, Jun Zhu
Cluster Alignment With a Teacher for Unsupervised Domain Adaptation. ICCV (2019)
Zhijie Deng, Yucen Luo, Jun Zhu, Bo Zhang
DBSN: Measuring Uncertainty through Bayesian Learning of Deep Neural Network Structures. CoRR (2019)
Zhijie Deng, Yucen Luo, Jun Zhu
Cluster Alignment with a Teacher for Unsupervised Domain Adaptation. CoRR (2019)
Zhijie Deng, Yinpeng Dong, Jun Zhu
Batch Virtual Adversarial Training for Graph Convolutional Networks. CoRR (2019)
Shizhen Xu, Hao Zhang, Graham Neubig, Wei Dai, Jin Kyu Kim, Zhijie Deng, Qirong Ho, Guangwen Yang, Eric P. Xing
Cavs: An Efficient Runtime System for Dynamic Neural Networks. USENIX Annual Technical Conference (2018)
Zhijie Deng, Hao Zhang, Xiaodan Liang, Luona Yang, Shizhen Xu, Jun Zhu, Eric P. Xing
Structured Generative Adversarial Networks. NIPS (2017)
Zhijie Deng, Hao Zhang, Xiaodan Liang, Luona Yang, Shizhen Xu, Jun Zhu, Eric P. Xing
Structured Generative Adversarial Networks. CoRR (2017)