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2020 – today
- 2024
[j40]Zhibo Wei, Yongze Liu, Yingnian Wu
, Wenbai Chen, Qing-Kui Li:
T-S fuzzy model based event-triggered change control for product and supply chain systems. Int. J. Syst. Sci. 55(3): 426-439 (2024)- [c99]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: 7514-7524 - [c98]Deqian Kong, Furqan Khan, Xu Zhang, Prateek Singhal, Ying Nian Wu:
Long-Term Social Interaction Context: The Key to Egocentric Addressee Detection. ICASSP 2024: 8250-8254 - [c97]Qing Li, Yixin Zhu, Yitao Liang, Ying Nian Wu, Song-Chun Zhu, Siyuan Huang:
Neural-Symbolic Recursive Machine for Systematic Generalization. ICLR 2024 - [c96]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 - [c95]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 - [c94]Yaxuan Zhu, Jianwen Xie, Ying Nian Wu, Ruiqi Gao:
Learning Energy-Based Models by Cooperative Diffusion Recovery Likelihood. ICLR 2024 - [c93]Andrew Lizarraga, Brandon Taraku, Edouardo Honig, Ying Nian Wu, Shantanu H. Joshi:
Differentiable VQ-VAE's for Robust White Matter Streamline Encodings. ISBI 2024: 1-5 - [i114]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 abs/2401.09742 (2024) - [i113]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 abs/2402.04647 (2024) - [i112]Huixin Zhan, Ying Nian Wu, Zijun Zhang:
Efficient and Scalable Fine-Tune of Language Models for Genome Understanding. CoRR abs/2402.08075 (2024) - [i111]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 abs/2402.17179 (2024) - [i110]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 abs/2403.11552 (2024) - [i109]Yingshan Chang, Yasi Zhang, Zhiyuan Fang, Yingnian Wu, Yonatan Bisk, Feng Gao:
Skews in the Phenomenon Space Hinder Generalization in Text-to-Image Generation. CoRR abs/2403.16394 (2024) - [i108]Yasi Zhang, Peiyu Yu, Ying Nian Wu:
Object-Conditioned Energy-Based Attention Map Alignment in Text-to-Image Diffusion Models. CoRR abs/2404.07389 (2024) - [i107]Hengzhi He, Peiyu Yu, Junpeng Ren, Ying Nian Wu, Guang Cheng:
Watermarking Generative Tabular Data. CoRR abs/2405.14018 (2024) - [i106]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 abs/2405.16730 (2024) - [i105]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 abs/2405.16852 (2024) - [i104]Dehong Xu, Ruiqi Gao, Wen-Hao Zhang, Xue-Xin Wei, Ying Nian Wu:
An Investigation of Conformal Isometry Hypothesis for Grid Cells. CoRR abs/2405.16865 (2024) - [i103]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 abs/2405.18515 (2024) - [i102]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 abs/2405.18816 (2024) - [i101]Muzhi Han, Yifeng Zhu, Song-Chun Zhu, Ying Nian Wu, Yuke Zhu:
InterPreT: Interactive Predicate Learning from Language Feedback for Generalizable Task Planning. CoRR abs/2405.19758 (2024) - [i100]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 abs/2407.11098 (2024) - 2023
- [j39]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: e1609 (2023) - [j38]Yingnian Wu, Jing Zhang, Qingkui Li, Hao Tan:
Research on Real-Time Robust Optimization of Perishable Supply-Chain Systems Based on Digital Twins. Sensors 23(4): 1850 (2023) - [j37]Jing Zhang, Yingnian Wu, Qingkui Li:
Production Change Optimization Model of Nonlinear Supply Chain System under Emergencies. Sensors 23(7): 3718 (2023) - [j36]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): 10563-10577 (2023) - [c92]Jiali Cui, Ying Nian Wu, Tian Han:
Learning Joint Latent Space EBM Prior Model for Multi-layer Generator. CVPR 2023: 3603-3612 - [c91]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: 29-42 - [c90]Jiali Cui, Ying Nian Wu, Tian Han:
Learning Hierarchical Features with Joint Latent Space Energy-Based Prior. ICCV 2023: 2218-2227 - [c89]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 - [c88]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 - [c87]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: 31389-31407 - [c86]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: 38518-38534 - [c85]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 - [c84]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 - [c83]Junfeng Zuo, Xiao Liu, Ying Nian Wu, Si Wu, Wenhao Zhang:
A Recurrent Neural Circuit Mechanism of Temporal-scaling Equivariant Representation. NeurIPS 2023 - [c82]Quanshi Zhang, Xu Cheng, Xin Wang, Yu Yang, Yingnian Wu:
Network Transplanting for the Functionally Modular Architecture. PRCV (3) 2023: 69-83 - [c81]Deqian Kong, Bo Pang, Tian Han, Ying Nian Wu:
Molecule Design by Latent Space Energy-Based Modeling and Gradual Distribution Shifting. UAI 2023: 1109-1120 - [i99]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 abs/2304.09842 (2023) - [i98]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 abs/2305.12039 (2023) - [i97]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 abs/2306.01153 (2023) - [i96]Jiali Cui, Ying Nian Wu, Tian Han:
Learning Joint Latent Space EBM Prior Model for Multi-layer Generator. CoRR abs/2306.06323 (2023) - [i95]Weinan Song, Yaxuan Zhu, Lei He, Yingnian Wu, Jianwen Xie:
Progressive Energy-Based Cooperative Learning for Multi-Domain Image-to-Image Translation. CoRR abs/2306.14448 (2023) - [i94]Deqian Kong, Bo Pang, Tian Han, Ying Nian Wu:
Molecule Design by Latent Space Energy-Based Modeling and Gradual Distribution Shifting. CoRR abs/2306.14902 (2023) - [i93]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 abs/2307.04047 (2023) - [i92]Yizhou Zhao, Yuanhong Zeng, Qian Long, Ying Nian Wu, Song-Chun Zhu:
Sim2Plan: Robot Motion Planning via Message Passing between Simulation and Reality. CoRR abs/2307.07862 (2023) - [i91]Yaxuan Zhu, Jianwen Xie, Yingnian Wu, Ruiqi Gao:
Learning Energy-Based Models by Cooperative Diffusion Recovery Likelihood. CoRR abs/2309.05153 (2023) - [i90]Yuanhong Zeng, Yizhou Zhao, Ying Nian Wu:
Triple Regression for Camera Agnostic Sim2Real Robot Grasping and Manipulation Tasks. CoRR abs/2309.09017 (2023) - [i89]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 abs/2310.03218 (2023) - [i88]Deqian Kong, Yuhao Huang, Jianwen Xie, Ying Nian Wu:
Molecule Design by Latent Prompt Transformer. CoRR abs/2310.03253 (2023) - [i87]Yilue Qian, Peiyu Yu, Ying Nian Wu, Wei Wang, Lifeng Fan:
Learning Concept-Based Visual Causal Transition and Symbolic Reasoning for Visual Planning. CoRR abs/2310.03325 (2023) - [i86]Jiali Cui, Ying Nian Wu, Tian Han:
Learning Hierarchical Features with Joint Latent Space Energy-Based Prior. CoRR abs/2310.09604 (2023) - [i85]Dehong Xu, Ruiqi Gao, Wen-Hao Zhang, Xue-Xin Wei, Ying Nian Wu:
Conformal Normalization in Recurrent Neural Network of Grid Cells. CoRR abs/2310.19192 (2023) - [i84]Andrew Lizarraga, Brandon Taraku, Edouardo Honig, Ying Nian Wu, Shantanu H. Joshi:
Differentiable VQ-VAE's for Robust White Matter Streamline Encodings. CoRR abs/2311.06212 (2023) - [i83]Ziheng Zhou, Yingnian Wu, Song-Chun Zhu, Demetri Terzopoulos:
Aligner: One Global Token is Worth Millions of Parameters When Aligning Large Language Models. CoRR abs/2312.05503 (2023) - 2022
- [j35]Rui Yang, Yingnian Wu, Xiaolong Liu, Wenbai Chen:
GACSNet: A Lightweight Network for the Noninvasive Blood Glucose Detection. Appl. Artif. Intell. 36(1) (2022) - [j34]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): 1162-1179 (2022) - [j33]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): 2468-2484 (2022) - [j32]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): 3957-3973 (2022) - [j31]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) - [c80]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: 6674-6684 - [c79]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: 11586-11594 - [c78]Cristian I. Challu, Peihong Jiang, Ying Nian Wu, Laurent Callot:
Deep Generative model with Hierarchical Latent Factors for Time Series Anomaly Detection. AISTATS 2022: 1643-1654 - [c77]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: 5057-5067 - [c76]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: 692-709 - [c75]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 - [c74]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: 25702-25720 - [c73]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: 370-387 - [c72]Wenhao Zhang, Ying Nian Wu, Si Wu:
Translation-equivariant Representation in Recurrent Networks with a Continuous Manifold of Attractors. NeurIPS 2022 - [i82]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 abs/2201.05299 (2022) - [i81]Cristian Challu, Peihong Jiang, Ying Nian Wu, Laurent Callot:
Deep Generative model with Hierarchical Latent Factors for Time Series Anomaly Detection. CoRR abs/2202.07586 (2022) - [i80]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 abs/2206.05895 (2022) - [i79]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 abs/2209.14610 (2022) - [i78]Qing Li, Yixin Zhu, Yitao Liang, Ying Nian Wu, Song-Chun Zhu, Siyuan Huang:
Neural-Symbolic Recursive Machine for Systematic Generalization. CoRR abs/2210.01603 (2022) - [i77]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 abs/2210.02684 (2022) - [i76]Cristian Challu, Peihong Jiang, Ying Nian Wu, Laurent Callot:
SpectraNet: Multivariate Forecasting and Imputation under Distribution Shifts and Missing Data. CoRR abs/2210.12515 (2022) - [i75]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 abs/2211.11033 (2022) - 2021
- [j30]Jianwen Xie, Song-Chun Zhu, Ying Nian Wu:
Learning Energy-Based Spatial-Temporal Generative ConvNets for Dynamic Patterns. IEEE Trans. Pattern Anal. Mach. Intell. 43(2): 516-531 (2021) - [j29]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): 3416-3431 (2021) - [j28]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): 3863-3877 (2021) - [j27]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): 3949-3963 (2021) - [c71]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: 10430-10440 - [c70]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: 658-670 - [c69]Wenjuan Han, Bo Pang, Ying Nian Wu:
Robust Transfer Learning with Pretrained Language Models through Adapters. ACL/IJCNLP (2) 2021: 854-861 - [c68]Yunqi Guo, Zhaowei Tan, Kaiyuan Chen, Songwu Lu, Ying Nian Wu:
A Model Obfuscation Approach to IoT Security. CNS 2021: 1-9 - [c67]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: 9959-9968 - [c66]Bo Pang, Tianyang Zhao, Xu Xie, Ying Nian Wu:
Trajectory Prediction With Latent Belief Energy-Based Model. CVPR 2021: 11814-11824 - [c65]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: 14976-14985 - [c64]Bo Pang, Erik Nijkamp, Tian Han, Ying Nian Wu:
Generative Text Modeling through Short Run Inference. EACL 2021: 1156-1165 - [c63]Ruiqi Gao, Yang Song, Ben Poole, Ying Nian Wu, Diederik P. Kingma:
Learning Energy-Based Models by Diffusion Recovery Likelihood. ICLR 2021 - [c62]Bo Pang, Ying Nian Wu:
Latent Space Energy-Based Model of Symbol-Vector Coupling for Text Generation and Classification. ICML 2021: 8359-8370 - [c61]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: 10257-10263 - [c60]Xu Xie, Chi Zhang, Yixin Zhu, Ying Nian Wu, Song-Chun Zhu:
Congestion-aware Multi-agent Trajectory Prediction for Collision Avoidance. ICRA 2021: 13693-13700 - [c59]Yangzi Guo, Ying Nian Wu, Adrian Barbu:
A Study of Local Optima for Learning Feature Interactions using Neural Networks. IJCNN 2021: 1-8 - [c58]Erik Nijkamp, Bo Pang, Ying Nian Wu, Caiming Xiong:
SCRIPT: Self-Critic PreTraining of Transformers. NAACL-HLT 2021: 5196-5202 - [c57]Peiyu Yu, Sirui Xie, Xiaojian Ma, Yixin Zhu, Ying Nian Wu, Song-Chun Zhu:
Unsupervised Foreground Extraction via Deep Region Competition. NeurIPS 2021: 14264-14279 - [c56]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: 28623-28635 - [c55]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: 29231-29245 - [i74]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 abs/2102.11344 (2021) - [i73]Qing Li, Siyuan Huang, Yining Hong, Yixin Zhu, Ying Nian Wu, Song-Chun Zhu:
A HINT from Arithmetic: On Systematic Generalization of Perception, Syntax, and Semantics. CoRR abs/2103.01403 (2021) - [i72]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 abs/2103.04285 (2021) - [i71]Xu Xie, Chi Zhang, Yixin Zhu, Ying Nian Wu, Song-Chun Zhu:
Congestion-aware Multi-agent Trajectory Prediction for Collision Avoidance. CoRR abs/2103.14231 (2021) - [i70]Yaxuan Zhu, Ruiqi Gao, Siyuan Huang, Song-Chun Zhu, Yingnian Wu:
Learning Neural Representation of Camera Pose with Matrix Representation of Pose Shift via View Synthesis. CoRR abs/2104.01508 (2021) - [i69]Bo Pang, Tianyang Zhao, Xu Xie, Ying Nian Wu:
Trajectory Prediction with Latent Belief Energy-Based Model. CoRR abs/2104.03086 (2021) - [i68]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 abs/2106.01006 (2021) - [i67]Bo Pang, Erik Nijkamp, Tian Han, Ying Nian Wu:
Generative Text Modeling through Short Run Inference. CoRR abs/2106.02513 (2021) - [i66]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 abs/2106.07176 (2021) - [i65]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 abs/2106.09127 (2021) - [i64]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 abs/2107.08821 (2021) - [i63]