Ying Nian Wu

ORCID

Publication Activity (10 Years)

Years Active: 1996-2024
Publications (10 Years): 200

Top Venues

Publications

Peiyu Yu, Dinghuai Zhang, Hengzhi He, Xiaojian Ma, Ruiyao Miao, Yifan Lu, Yasi Zhang, Deqian Kong, Ruiqi Gao, Jianwen Xie, Guang Cheng, Ying Nian Wu
Latent Energy-Based Odyssey: Black-Box Optimization via Expanded Exploration in the Energy-Based Latent Space. CoRR (2024)
Yasi Zhang, Peiyu Yu, Yaxuan Zhu, Yingshan Chang, Feng Gao, Ying Nian Wu, Oscar Leong
Flow Priors for Linear Inverse Problems via Iterative Corrupted Trajectory Matching. CoRR (2024)
Tianyang Zhao, Kunwar Yashraj Singh, Srikar Appalaraju, Peng Tang, Vijay Mahadevan, R. Manmatha, Ying Nian Wu
No Head Left Behind - Multi-Head Alignment Distillation for Transformers. AAAI (2024)
Cheng Han, James Chenhao Liang, Qifan Wang, Majid Rabbani, Sohail A. Dianat, Raghuveer Rao, Ying Nian Wu, Dongfang Liu
Image Translation as Diffusion Visual Programmers. CoRR (2024)
Yunuo Chen, Tianyi Xie, Zeshun Zong, Xuan Li, Feng Gao, Yin Yang, Ying Nian Wu, Chenfanfu Jiang
Atlas3D: Physically Constrained Self-Supporting Text-to-3D for Simulation and Fabrication. CoRR (2024)
Sirui Xie, Zhisheng Xiao, Diederik P. Kingma, Tingbo Hou, Ying Nian Wu, Kevin Patrick Murphy, Tim Salimans, Ben Poole, Ruiqi Gao
EM Distillation for One-step Diffusion Models. CoRR (2024)
Qing Li, Yixin Zhu, Yitao Liang, Ying Nian Wu, Song-Chun Zhu, Siyuan Huang
Neural-Symbolic Recursive Machine for Systematic Generalization. ICLR (2024)
Yaxuan Zhu, Jianwen Xie, Ying Nian Wu, Ruiqi Gao
Learning Energy-Based Models by Cooperative Diffusion Recovery Likelihood. ICLR (2024)
Qin Zhang, Linghan Xu, Jun Fang, Qingming Tang, Ying Nian Wu, Joseph Tighe, Yifan Xing
Threshold-Consistent Margin Loss for Open-World Deep Metric Learning. ICLR (2024)
Deqian Kong, Dehong Xu, Minglu Zhao, Bo Pang, Jianwen Xie, Andrew Lizarraga, Yuhao Huang, Sirui Xie, Ying Nian Wu
Latent Plan Transformer: Planning as Latent Variable Inference. CoRR (2024)
Shu Wang, Muzhi Han, Ziyuan Jiao, Zeyu Zhang, Ying Nian Wu, Song-Chun Zhu, Hangxin Liu
LLM3: Large Language Model-based Task and Motion Planning with Motion Failure Reasoning. CoRR (2024)
Cheng Han, James Chenhao Liang, Qifan Wang, Majid Rabbani, Sohail A. Dianat, Raghuveer Rao, Ying Nian Wu, Dongfang Liu
Image Translation as Diffusion Visual Programmers. ICLR (2024)
Mingkai Chen, Taowen Wang, James Chenhao Liang, Chuan Liu, Chunshu Wu, Qifan Wang, Ying Nian Wu, Michael Huang, Chuang Ren, Ang Li, Tong Geng, Dongfang Liu
Inertial Confinement Fusion Forecasting via LLMs. CoRR (2024)
Deqian Kong, Yuhao Huang, Jianwen Xie, Edouardo Honig, Ming Xu, Shuanghong Xue, Pei Lin, Sanping Zhou, Sheng Zhong, Nanning Zheng, Ying Nian Wu
Dual-Space Optimization: Improved Molecule Sequence Design by Latent Prompt Transformer. CoRR (2024)
Yasi Zhang, Peiyu Yu, Ying Nian Wu
Object-Conditioned Energy-Based Attention Map Alignment in Text-to-Image Diffusion Models. CoRR (2024)
Muzhi Han, Yifeng Zhu, Song-Chun Zhu, Ying Nian Wu, Yuke Zhu
InterPreT: Interactive Predicate Learning from Language Feedback for Generalizable Task Planning. CoRR (2024)
Huixin Zhan, Ying Nian Wu, Zijun Zhang
Efficient and Scalable Fine-Tune of Language Models for Genome Understanding. CoRR (2024)
Hengzhi He, Peiyu Yu, Junpeng Ren, Ying Nian Wu, Guang Cheng
Watermarking Generative Tabular Data. CoRR (2024)
Deqian Kong, Furqan Khan, Xu Zhang, Prateek Singhal, Ying Nian Wu
Long-Term Social Interaction Context: The Key to Egocentric Addressee Detection. ICASSP (2024)
Dehong Xu, Ruiqi Gao, Wen-Hao Zhang, Xue-Xin Wei, Ying Nian Wu
An Investigation of Conformal Isometry Hypothesis for Grid Cells. CoRR (2024)
Qing Li, Siyuan Huang, Yining Hong, Yixin Zhu, Ying Nian Wu, Song-Chun Zhu
A Minimalist Dataset for Systematic Generalization of Perception, Syntax, and Semantics. ICLR (2023)
Jiali Cui, Ying Nian Wu, Tian Han
Learning Joint Latent Space EBM Prior Model for Multi-layer Generator. CVPR (2023)
Yan Xu, Deqian Kong, Dehong Xu, Ziwei Ji, Bo Pang, Pascale Fung, Ying Nian Wu
Diverse and Faithful Knowledge-Grounded Dialogue Generation via Sequential Posterior Inference. CoRR (2023)
Tan Hao, Ying Nian Wu, Zhang Jiaxing, Zhang Jing
Study on a hybrid algorithm combining enhanced ant colony optimization and double improved simulated annealing via clustering in the Traveling Salesman Problem (TSP). PeerJ Comput. Sci. 9 (2023)
Peiyu Yu, Yaxuan Zhu, Sirui Xie, Xiaojian Ma, Ruiqi Gao, Song-Chun Zhu, Ying Nian Wu
Learning Energy-Based Prior Model with Diffusion-Amortized MCMC. CoRR (2023)
Junfeng Zuo, Xiao Liu, Ying Nian Wu, Si Wu, Wenhao Zhang
A Recurrent Neural Circuit Mechanism of Temporal-scaling Equivariant Representation. NeurIPS (2023)
Jiali Cui, Ying Nian Wu, Tian Han
Learning Hierarchical Features with Joint Latent Space Energy-Based Prior. ICCV (2023)
Jiali Cui, Ying Nian Wu, Tian Han
Learning Hierarchical Features with Joint Latent Space Energy-Based Prior. CoRR (2023)
Andrew Lizarraga, Brandon Taraku, Edouardo Honig, Ying Nian Wu, Shantanu H. Joshi
Differentiable VQ-VAE's for Robust White Matter Streamline Encodings. CoRR (2023)
Yu-Zhe Shi, Manjie Xu, John E. Hopcroft, Kun He, Joshua B. Tenenbaum, Song-Chun Zhu, Ying Nian Wu, Wenjuan Han, Yixin Zhu
On the Complexity of Bayesian Generalization. ICML (2023)
Pan Lu, Baolin Peng, Hao Cheng, Michel Galley, Kai-Wei Chang, Ying Nian Wu, Song-Chun Zhu, Jianfeng Gao
Chameleon: Plug-and-Play Compositional Reasoning with Large Language Models. NeurIPS (2023)
Deqian Kong, Yuhao Huang, Jianwen Xie, Ying Nian Wu
Molecule Design by Latent Prompt Transformer. CoRR (2023)
Deqian Kong, Bo Pang, Tian Han, Ying Nian Wu
Molecule Design by Latent Space Energy-Based Modeling and Gradual Distribution Shifting. CoRR (2023)
Yan Xu, Deqian Kong, Dehong Xu, Ziwei Ji, Bo Pang, Pascale Fung, Ying Nian Wu
Diverse and Faithful Knowledge-Grounded Dialogue Generation via Sequential Posterior Inference. ICML (2023)
Dehong Xu, Ruiqi Gao, Wen-Hao Zhang, Xue-Xin Wei, Ying Nian Wu
Conformal Normalization in Recurrent Neural Network of Grid Cells. CoRR (2023)
Peiyu Yu, Yaxuan Zhu, Sirui Xie, Xiaojian Ma, Ruiqi Gao, Song-Chun Zhu, Ying Nian Wu
Learning Energy-Based Prior Model with Diffusion-Amortized MCMC. NeurIPS (2023)
Qin Zhang, Dongsheng An, Tianjun Xiao, Tong He, Qingming Tang, Ying Nian Wu, Joseph Tighe, Yifan Xing
Learning for Open-World Calibration with Graph Neural Networks. CoRR (2023)
Pan Lu, Baolin Peng, Hao Cheng, Michel Galley, Kai-Wei Chang, Ying Nian Wu, Song-Chun Zhu, Jianfeng Gao
Chameleon: Plug-and-Play Compositional Reasoning with Large Language Models. CoRR (2023)
Deqian Kong, Bo Pang, Tian Han, Ying Nian Wu
Molecule Design by Latent Space Energy-Based Modeling and Gradual Distribution Shifting. UAI (2023)
Qin Zhang, Linghan Xu, Qingming Tang, Jun Fang, Ying Nian Wu, Joe Tighe, Yifan Xing
Calibration-Aware Margin Loss: Pushing the Accuracy-Calibration Consistency Pareto Frontier for Deep Metric Learning. CoRR (2023)
Yizhou Zhao, Yuanhong Zeng, Qian Long, Ying Nian Wu, Song-Chun Zhu
Sim2Plan: Robot Motion Planning via Message Passing between Simulation and Reality. CoRR (2023)
Yizhou Zhao, Yuanhong Zeng, Qian Long, Ying Nian Wu, Song-Chun Zhu
Sim2Plan: Robot Motion Planning via Message Passing Between Simulation and Reality. FTC (1) (2023)
Yifei Xu, Jianwen Xie, Tianyang Zhao, Chris L. Baker, Yibiao Zhao, Ying Nian Wu
Energy-Based Continuous Inverse Optimal Control. IEEE Trans. Neural Networks Learn. Syst. 34 (12) (2023)
Jiali Cui, Ying Nian Wu, Tian Han
Learning Joint Latent Space EBM Prior Model for Multi-layer Generator. CoRR (2023)
Yilue Qian, Peiyu Yu, Ying Nian Wu, Wei Wang, Lifeng Fan
Learning Concept-Based Visual Causal Transition and Symbolic Reasoning for Visual Planning. CoRR (2023)
Yuanhong Zeng, Yizhou Zhao, Ying Nian Wu
Triple Regression for Camera Agnostic Sim2Real Robot Grasping and Manipulation Tasks. CoRR (2023)
Pan Lu, Liang Qiu, Kai-Wei Chang, Ying Nian Wu, Song-Chun Zhu, Tanmay Rajpurohit, Peter Clark, Ashwin Kalyan
Dynamic Prompt Learning via Policy Gradient for Semi-structured Mathematical Reasoning. ICLR (2023)
Dehong Xu, Ruiqi Gao, Wen-Hao Zhang, Xue-Xin Wei, Ying Nian Wu
Conformal Isometry of Lie Group Representation in Recurrent Network of Grid Cells. NeurReps (2022)
Ruiqi Gao, Jianwen Xie, Siyuan Huang, Yufan Ren, Song-Chun Zhu, Ying Nian Wu
Learning V1 Simple Cells with Vector Representation of Local Content and Matrix Representation of Local Motion. AAAI (2022)
Luyao Yuan, Xiaofeng Gao, Zilong Zheng, Mark Edmonds, Ying Nian Wu, Federico Rossano, Hongjing Lu, Yixin Zhu, Song-Chun Zhu
In situ bidirectional human-robot value alignment. Sci. Robotics 7 (68) (2022)
Wenhao Zhang, Ying Nian Wu, Si Wu
Translation-equivariant Representation in Recurrent Networks with a Continuous Manifold of Attractors. NeurIPS (2022)
Xianglei Xing, Ruiqi Gao, Tian Han, Song-Chun Zhu, Ying Nian Wu
Deformable Generator Networks: Unsupervised Disentanglement of Appearance and Geometry. IEEE Trans. Pattern Anal. Mach. Intell. 44 (3) (2022)
Cristian Challu, Peihong Jiang, Ying Nian Wu, Laurent Callot
Deep Generative model with Hierarchical Latent Factors for Time Series Anomaly Detection. CoRR (2022)
Qing Li, Yixin Zhu, Yitao Liang, Ying Nian Wu, Song-Chun Zhu, Siyuan Huang
Neural-Symbolic Recursive Machine for Systematic Generalization. CoRR (2022)
Yifei Xu, Jingqiao Zhang, Ru He, Liangzhu Ge, Chao Yang, Cheng Yang, Ying Nian Wu
SAS: Self-Augmentation Strategy for Language Model Pre-training. AAAI (2022)
Peiyu Yu, Sirui Xie, Xiaojian Ma, Baoxiong Jia, Bo Pang, Ruiqi Gao, Yixin Zhu, Song-Chun Zhu, Ying Nian Wu
Latent Diffusion Energy-Based Model for Interpretable Text Modelling. ICML (2022)
Yu-Zhe Shi, Manjie Xu, John E. Hopcroft, Kun He, Joshua B. Tenenbaum, Song-Chun Zhu, Ying Nian Wu, Wenjuan Han, Yixin Zhu
On the Complexity of Bayesian Generalization. CoRR (2022)
Dehong Xu, Ruiqi Gao, Wen-Hao Zhang, Xue-Xin Wei, Ying Nian Wu
Conformal Isometry of Lie Group Representation in Recurrent Network of Grid Cells. CoRR (2022)
Feng Gao, Qing Ping, Govind Thattai, Aishwarya N. Reganti, Ying Nian Wu, Prem Natarajan
Transform-Retrieve-Generate: Natural Language-Centric Outside-Knowledge Visual Question Answering. CVPR (2022)
Cristian Challu, Peihong Jiang, Ying Nian Wu, Laurent Callot
SpectraNet: Multivariate Forecasting and Imputation under Distribution Shifts and Missing Data. CoRR (2022)
Pan Lu, Liang Qiu, Kai-Wei Chang, Ying Nian Wu, Song-Chun Zhu, Tanmay Rajpurohit, Peter Clark, Ashwin Kalyan
Dynamic Prompt Learning via Policy Gradient for Semi-structured Mathematical Reasoning. CoRR (2022)
Cristian I. Challu, Peihong Jiang, Ying Nian Wu, Laurent Callot
Deep Generative model with Hierarchical Latent Factors for Time Series Anomaly Detection. AISTATS (2022)
Jianwen Xie, Zilong Zheng, Xiaolin Fang, Song-Chun Zhu, Ying Nian Wu
Cooperative Training of Fast Thinking Initializer and Slow Thinking Solver for Conditional Learning. IEEE Trans. Pattern Anal. Mach. Intell. 44 (8) (2022)
Chi Zhang, Sirui Xie, Baoxiong Jia, Ying Nian Wu, Song-Chun Zhu, Yixin Zhu
Learning Algebraic Representation for Systematic Generalization in Abstract Reasoning. ECCV (39) (2022)
Peiyu Yu, Sirui Xie, Xiaojian Ma, Baoxiong Jia, Bo Pang, Ruiqi Gao, Yixin Zhu, Song-Chun Zhu, Ying Nian Wu
Latent Diffusion Energy-Based Model for Interpretable Text Modeling. CoRR (2022)
Feng Gao, Qing Ping, Govind Thattai, Aishwarya N. Reganti, Ying Nian Wu, Prem Natarajan
A Thousand Words Are Worth More Than a Picture: Natural Language-Centric Outside-Knowledge Visual Question Answering. CoRR (2022)
Erik Nijkamp, Ruiqi Gao, Pavel Sountsov, Srinivas Vasudevan, Bo Pang, Song-Chun Zhu, Ying Nian Wu
MCMC Should Mix: Learning Energy-Based Model with Neural Transport Latent Space MCMC. ICLR (2022)
Jianwen Xie, Zilong Zheng, Ruiqi Gao, Wenguan Wang, Song-Chun Zhu, Ying Nian Wu
Generative VoxelNet: Learning Energy-Based Models for 3D Shape Synthesis and Analysis. IEEE Trans. Pattern Anal. Mach. Intell. 44 (5) (2022)
Erik Nijkamp, Bo Pang, Ying Nian Wu, Caiming Xiong
SCRIPT: Self-Critic PreTraining of Transformers. NAACL-HLT (2021)
Yunqi Guo, Zhaowei Tan, Kaiyuan Chen, Songwu Lu, Ying Nian Wu
A Model Obfuscation Approach to IoT Security. CNS (2021)
Wenjuan Han, Bo Pang, Ying Nian Wu
Robust Transfer Learning with Pretrained Language Models through Adapters. CoRR (2021)
Bo Pang, Ying Nian Wu
Latent Space Energy-Based Model of Symbol-Vector Coupling for Text Generation and Classification. ICML (2021)
Xu Xie, Chi Zhang, Yixin Zhu, Ying Nian Wu, Song-Chun Zhu
Congestion-aware Multi-agent Trajectory Prediction for Collision Avoidance. CoRR (2021)
Quanshi Zhang, Tian Han, Lixin Fan, Zhanxing Zhu, Hang Su, Ying Nian Wu, Jie Ren, Hao Zhang
Proceedings of ICML 2021 Workshop on Theoretic Foundation, Criticism, and Application Trend of Explainable AI. CoRR (2021)
Jianwen Xie, Yifei Xu, Zilong Zheng, Song-Chun Zhu, Ying Nian Wu
Generative PointNet: Deep Energy-Based Learning on Unordered Point Sets for 3D Generation, Reconstruction and Classification. CVPR (2021)
Bo Pang, Erik Nijkamp, Tian Han, Ying Nian Wu
Generative Text Modeling through Short Run Inference. CoRR (2021)
Hung-Jui Huang, Kai-Chi Huang, Michal Cáp, Yibiao Zhao, Ying Nian Wu, Chris L. Baker
Planning on a (Risk) Budget: Safe Non-Conservative Planning in Probabilistic Dynamic Environments. ICRA (2021)
Chi Zhang, Sirui Xie, Baoxiong Jia, Ying Nian Wu, Song-Chun Zhu, Yixin Zhu
Learning Algebraic Representation for Systematic Generalization in Abstract Reasoning. CoRR (2021)
Bo Pang, Erik Nijkamp, Tian Han, Ying Nian Wu
Generative Text Modeling through Short Run Inference. EACL (2021)
Hung-Jui Huang, Kai-Chi Huang, Michal Cáp, Yibiao Zhao, Ying Nian Wu, Chris L. Baker
Planning on a (Risk) Budget: Safe Non-Conservative Planning in Probabilistic Dynamic Environments. CoRR (2021)
Quanshi Zhang, Jie Ren, Ge Huang, Ruiming Cao, Ying Nian Wu, Song-Chun Zhu
Mining Interpretable AOG Representations From Convolutional Networks via Active Question Answering. IEEE Trans. Pattern Anal. Mach. Intell. 43 (11) (2021)
Luyao Yuan, Dongruo Zhou, Junhong Shen, Jingdong Gao, Jeffrey L. Chen, Quanquan Gu, Ying Nian Wu, Song-Chun Zhu
Iterative Teacher-Aware Learning. NeurIPS (2021)
Liang Qiu, Yuan Liang, Yizhou Zhao, Pan Lu, Baolin Peng, Zhou Yu, Ying Nian Wu, Song-Chun Zhu
SocAoG: Incremental Graph Parsing for Social Relation Inference in Dialogues. CoRR (2021)
Ruiqi Gao, Jianwen Xie, Xue-Xin Wei, Song-Chun Zhu, Ying Nian Wu
On Path Integration of Grid Cells: Group Representation and Isotropic Scaling. NeurIPS (2021)
Yifei Xu, Jingqiao Zhang, Ru He, Liangzhu Ge, Chao Yang, Cheng Yang, Ying Nian Wu
SAS: Self-Augmented Strategy for Language Model Pre-training. CoRR (2021)
Ruiqi Gao, Yang Song, Ben Poole, Ying Nian Wu, Diederik P. Kingma
Learning Energy-Based Models by Diffusion Recovery Likelihood. ICLR (2021)
Liang Qiu, Yuan Liang, Yizhou Zhao, Pan Lu, Baolin Peng, Zhou Yu, Ying Nian Wu, Song-Chun Zhu
SocAoG: Incremental Graph Parsing for Social Relation Inference in Dialogues. ACL/IJCNLP (1) (2021)
Sirui Xie, Xiaojian Ma, Peiyu Yu, Yixin Zhu, Ying Nian Wu, Song-Chun Zhu
HALMA: Humanlike Abstraction Learning Meets Affordance in Rapid Problem Solving. CoRR (2021)
Quanshi Zhang, Xin Wang, Ying Nian Wu, Huilin Zhou, Song-Chun Zhu
Interpretable CNNs for Object Classification. IEEE Trans. Pattern Anal. Mach. Intell. 43 (10) (2021)
Jianwen Xie, Zilong Zheng, Xiaolin Fang, Song-Chun Zhu, Ying Nian Wu
Learning Cycle-Consistent Cooperative Networks via Alternating MCMC Teaching for Unsupervised Cross-Domain Translation. CoRR (2021)
Bo Pang, Tianyang Zhao, Xu Xie, Ying Nian Wu
Trajectory Prediction With Latent Belief Energy-Based Model. CVPR (2021)
Bo Pang, Tianyang Zhao, Xu Xie, Ying Nian Wu
Trajectory Prediction with Latent Belief Energy-Based Model. CoRR (2021)
Bo Pang, Ying Nian Wu
Latent Space Energy-Based Model of Symbol-Vector Coupling for Text Generation and Classification. CoRR (2021)
Quanshi Zhang, Xin Wang, Ruiming Cao, Ying Nian Wu, Feng Shi, Song-Chun Zhu
Extraction of an Explanatory Graph to Interpret a CNN. IEEE Trans. Pattern Anal. Mach. Intell. 43 (11) (2021)
Peiyu Yu, Sirui Xie, Xiaojian Ma, Yixin Zhu, Ying Nian Wu, Song-Chun Zhu
Unsupervised Foreground Extraction via Deep Region Competition. CoRR (2021)
Luyao Yuan, Dongruo Zhou, Junhong Shen, Jingdong Gao, Jeffrey L. Chen, Quanquan Gu, Ying Nian Wu, Song-Chun Zhu
Iterative Teacher-Aware Learning. CoRR (2021)
Wenjuan Han, Bo Pang, Ying Nian Wu
Robust Transfer Learning with Pretrained Language Models through Adapters. ACL/IJCNLP (2) (2021)
Peiyu Yu, Sirui Xie, Xiaojian Ma, Yixin Zhu, Ying Nian Wu, Song-Chun Zhu
Unsupervised Foreground Extraction via Deep Region Competition. NeurIPS (2021)
Jianwen Xie, Zilong Zheng, Xiaolin Fang, Song-Chun Zhu, Ying Nian Wu
Learning Cycle-Consistent Cooperative Networks via Alternating MCMC Teaching for Unsupervised Cross-Domain Translation. AAAI (2021)
Yaxuan Zhu, Ruiqi Gao, Siyuan Huang, Song-Chun Zhu, Ying Nian Wu
Learning Neural Representation of Camera Pose with Matrix Representation of Pose Shift via View Synthesis. CVPR (2021)

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Publication Activity (10 Years)

Top Topics

Top Venues

Ying Nian Wu