default search action
Mingsheng Long
Person information
Refine list
refinements active!
zoomed in on ?? of ?? records
view refined list in
export refined list as
2020 – today
- 2024
- [j16]Li Liu, Timothy M. Hospedales, Yann LeCun, Mingsheng Long, Jiebo Luo, Wanli Ouyang, Matti Pietikäinen, Tinne Tuytelaars:
Editorial: Learning With Fewer Labels in Computer Vision. IEEE Trans. Pattern Anal. Mach. Intell. 46(3): 1319-1326 (2024) - [j15]Ying Jin, Zhangjie Cao, Ximei Wang, Jianmin Wang, Mingsheng Long:
One Fits Many: Class Confusion Loss for Versatile Domain Adaptation. IEEE Trans. Pattern Anal. Mach. Intell. 46(11): 7251-7266 (2024) - [c112]Yong Liu, Tengge Hu, Haoran Zhang, Haixu Wu, Shiyu Wang, Lintao Ma, Mingsheng Long:
iTransformer: Inverted Transformers Are Effective for Time Series Forecasting. ICLR 2024 - [c111]Kaichao You, Guo Qin, Anchang Bao, Meng Cao, Ping Huang, Jiulong Shan, Mingsheng Long:
Efficient ConvBN Blocks for Transfer Learning and Beyond. ICLR 2024 - [c110]Kaiyuan Chen, Xingzhuo Guo, Yu Zhang, Jianmin Wang, Mingsheng Long:
CogDPM: Diffusion Probabilistic Models via Cognitive Predictive Coding. ICML 2024 - [c109]Jiaxiang Dong, Haixu Wu, Yuxuan Wang, Yunzhong Qiu, Li Zhang, Jianmin Wang, Mingsheng Long:
TimeSiam: A Pre-Training Framework for Siamese Time-Series Modeling. ICML 2024 - [c108]Xingzhuo Guo, Junwei Pan, Ximei Wang, Baixu Chen, Jie Jiang, Mingsheng Long:
On the Embedding Collapse when Scaling up Recommendation Models. ICML 2024 - [c107]Yong Liu, Haoran Zhang, Chenyu Li, Xiangdong Huang, Jianmin Wang, Mingsheng Long:
Timer: Generative Pre-trained Transformers Are Large Time Series Models. ICML 2024 - [c106]Haoyu Ma, Jialong Wu, Ningya Feng, Chenjun Xiao, Dong Li, Jianye Hao, Jianmin Wang, Mingsheng Long:
HarmonyDream: Task Harmonization Inside World Models. ICML 2024 - [c105]Haixu Wu, Huakun Luo, Haowen Wang, Jianmin Wang, Mingsheng Long:
Transolver: A Fast Transformer Solver for PDEs on General Geometries. ICML 2024 - [c104]Lanxiang Xing, Haixu Wu, Yuezhou Ma, Jianmin Wang, Mingsheng Long:
HelmFluid: Learning Helmholtz Dynamics for Interpretable Fluid Prediction. ICML 2024 - [c103]Zhiyu Yao, Jian Wang, Haixu Wu, Jingdong Wang, Mingsheng Long:
Mobile Attention: Mobile-Friendly Linear-Attention for Vision Transformers. ICML 2024 - [c102]Zhongyi Pei, Zhiyao Cen, Yipeng Huang, Chen Wang, Lin Liu, Philip S. Yu, Mingsheng Long, Jianmin Wang:
BTTackler: A Diagnosis-based Framework for Efficient Deep Learning Hyperparameter Optimization. KDD 2024: 2340-2351 - [c101]Zhiyu Yao, Xinyang Chen, Sinan Wang, Qinyan Dai, Yumeng Li, Tanchao Zhu, Mingsheng Long:
Recommender Transformers with Behavior Pathways. WWW 2024: 3643-3654 - [i87]Haixu Wu, Huakun Luo, Haowen Wang, Jianmin Wang, Mingsheng Long:
Transolver: A Fast Transformer Solver for PDEs on General Geometries. CoRR abs/2402.02366 (2024) - [i86]Yong Liu, Haoran Zhang, Chenyu Li, Xiangdong Huang, Jianmin Wang, Mingsheng Long:
Timer: Transformers for Time Series Analysis at Scale. CoRR abs/2402.02368 (2024) - [i85]Yong Liu, Guo Qin, Xiangdong Huang, Jianmin Wang, Mingsheng Long:
AutoTimes: Autoregressive Time Series Forecasters via Large Language Models. CoRR abs/2402.02370 (2024) - [i84]Qilong Ma, Haixu Wu, Lanxiang Xing, Jianmin Wang, Mingsheng Long:
EuLagNet: Eulerian Fluid Prediction with Lagrangian Dynamics. CoRR abs/2402.02425 (2024) - [i83]Jiaxiang Dong, Haixu Wu, Yuxuan Wang, Yunzhong Qiu, Li Zhang, Jianmin Wang, Mingsheng Long:
TimeSiam: A Pre-Training Framework for Siamese Time-Series Modeling. CoRR abs/2402.02475 (2024) - [i82]Yuxuan Wang, Haixu Wu, Jiaxiang Dong, Yong Liu, Yunzhong Qiu, Haoran Zhang, Jianmin Wang, Mingsheng Long:
TimeXer: Empowering Transformers for Time Series Forecasting with Exogenous Variables. CoRR abs/2402.19072 (2024) - [i81]Kaichao You, Runsheng Bai, Meng Cao, Jianmin Wang, Ion Stoica, Mingsheng Long:
depyf: Open the Opaque Box of PyTorch Compiler for Machine Learning Researchers. CoRR abs/2403.13839 (2024) - [i80]Jialong Wu, Chaoyi Deng, Jianmin Wang, Mingsheng Long:
Supercompiler Code Optimization with Zero-Shot Reinforcement Learning. CoRR abs/2404.16077 (2024) - [i79]Kaiyuan Chen, Xingzhuo Guo, Yu Zhang, Jianmin Wang, Mingsheng Long:
CogDPM: Diffusion Probabilistic Models via Cognitive Predictive Coding. CoRR abs/2405.02384 (2024) - [i78]Haixu Wu, Huakun Luo, Yuezhou Ma, Jianmin Wang, Mingsheng Long:
RoPINN: Region Optimized Physics-Informed Neural Networks. CoRR abs/2405.14369 (2024) - [i77]Jialong Wu, Shaofeng Yin, Ningya Feng, Xu He, Dong Li, Jianye Hao, Mingsheng Long:
iVideoGPT: Interactive VideoGPTs are Scalable World Models. CoRR abs/2405.15223 (2024) - [i76]Hang Zhou, Yuezhou Ma, Haixu Wu, Haowen Wang, Mingsheng Long:
Unisolver: PDE-Conditional Transformers Are Universal PDE Solvers. CoRR abs/2405.17527 (2024) - [i75]Jincheng Zhong, Xingzhuo Guo, Jiaxiang Dong, Mingsheng Long:
Diffusion Tuning: Transferring Diffusion Models via Chain of Forgetting. CoRR abs/2406.00773 (2024) - [i74]Yuxuan Wang, Haixu Wu, Jiaxiang Dong, Yong Liu, Mingsheng Long, Jianmin Wang:
Deep Time Series Models: A Comprehensive Survey and Benchmark. CoRR abs/2407.13278 (2024) - [i73]Ningya Feng, Junwei Pan, Jialong Wu, Baixu Chen, Ximei Wang, Qian Li, Xian Hu, Jie Jiang, Mingsheng Long:
Long-Sequence Recommendation Models Need Decoupled Embeddings. CoRR abs/2410.02604 (2024) - [i72]Jiaxiang Dong, Haixu Wu, Yuxuan Wang, Li Zhang, Jianmin Wang, Mingsheng Long:
Metadata Matters for Time Series: Informative Forecasting with Transformers. CoRR abs/2410.03806 (2024) - [i71]Yong Liu, Guo Qin, Xiangdong Huang, Jianmin Wang, Mingsheng Long:
Timer-XL: Long-Context Transformers for Unified Time Series Forecasting. CoRR abs/2410.04803 (2024) - 2023
- [j14]Haixu Wu, Hang Zhou, Mingsheng Long, Jianmin Wang:
Interpretable weather forecasting for worldwide stations with a unified deep model. Nat. Mac. Intell. 5(6): 602-611 (2023) - [j13]Yuchen Zhang, Mingsheng Long, Kaiyuan Chen, Lanxiang Xing, Ronghua Jin, Michael I. Jordan, Jianmin Wang:
Skilful nowcasting of extreme precipitation with NowcastNet. Nat. 619(7970): 526-532 (2023) - [j12]Zhangjie Cao, Kaichao You, Ziyang Zhang, Jianmin Wang, Mingsheng Long:
From Big to Small: Adaptive Learning to Partial-Set Domains. IEEE Trans. Pattern Anal. Mach. Intell. 45(2): 1766-1780 (2023) - [j11]Yunbo Wang, Haixu Wu, Jianjin Zhang, Zhifeng Gao, Jianmin Wang, Philip S. Yu, Mingsheng Long:
PredRNN: A Recurrent Neural Network for Spatiotemporal Predictive Learning. IEEE Trans. Pattern Anal. Mach. Intell. 45(2): 2208-2225 (2023) - [j10]Zhiyu Yao, Yunbo Wang, Haixu Wu, Jianmin Wang, Mingsheng Long:
ModeRNN: Harnessing Spatiotemporal Mode Collapse in Unsupervised Predictive Learning. IEEE Trans. Pattern Anal. Mach. Intell. 45(11): 13281-13296 (2023) - [j9]Yang Shu, Zhangjie Cao, Jinghan Gao, Jianmin Wang, Philip S. Yu, Mingsheng Long:
Omni-Training: Bridging Pre-Training and Meta-Training for Few-Shot Learning. IEEE Trans. Pattern Anal. Mach. Intell. 45(12): 15275-15291 (2023) - [c100]Haixu Wu, Tengge Hu, Yong Liu, Hang Zhou, Jianmin Wang, Mingsheng Long:
TimesNet: Temporal 2D-Variation Modeling for General Time Series Analysis. ICLR 2023 - [c99]Xingzhuo Guo, Yuchen Zhang, Jianmin Wang, Mingsheng Long:
Estimating Heterogeneous Treatment Effects: Mutual Information Bounds and Learning Algorithms. ICML 2023: 12108-12121 - [c98]Yang Shu, Xingzhuo Guo, Jialong Wu, Ximei Wang, Jianmin Wang, Mingsheng Long:
CLIPood: Generalizing CLIP to Out-of-Distributions. ICML 2023: 31716-31731 - [c97]Haixu Wu, Tengge Hu, Huakun Luo, Jianmin Wang, Mingsheng Long:
Solving High-Dimensional PDEs with Latent Spectral Models. ICML 2023: 37417-37438 - [c96]Jialong Wu, Haoyu Ma, Chaoyi Deng, Mingsheng Long:
Pre-training Contextualized World Models with In-the-wild Videos for Reinforcement Learning. NeurIPS 2023 - [c95]Jiaxiang Dong, Haixu Wu, Haoran Zhang, Li Zhang, Jianmin Wang, Mingsheng Long:
SimMTM: A Simple Pre-Training Framework for Masked Time-Series Modeling. NeurIPS 2023 - [c94]Junguang Jiang, Baixu Chen, Junwei Pan, Ximei Wang, Dapeng Liu, Jie Jiang, Mingsheng Long:
ForkMerge: Mitigating Negative Transfer in Auxiliary-Task Learning. NeurIPS 2023 - [c93]Yong Liu, Chenyu Li, Jianmin Wang, Mingsheng Long:
Koopa: Learning Non-stationary Time Series Dynamics with Koopman Predictors. NeurIPS 2023 - [c92]Jincheng Zhong, Haoyu Ma, Ximei Wang, Zhi Kou, Mingsheng Long:
Bi-tuning: Efficient Transfer from Pre-trained Models. ECML/PKDD (5) 2023: 357-373 - [i70]Junguang Jiang, Baixu Chen, Junwei Pan, Ximei Wang, Dapeng Liu, Jie Jiang, Mingsheng Long:
ForkMerge: Overcoming Negative Transfer in Multi-Task Learning. CoRR abs/2301.12618 (2023) - [i69]Haixu Wu, Tengge Hu, Huakun Luo, Jianmin Wang, Mingsheng Long:
Solving High-Dimensional PDEs with Latent Spectral Models. CoRR abs/2301.12664 (2023) - [i68]Jiaxiang Dong, Haixu Wu, Haoran Zhang, Li Zhang, Jianmin Wang, Mingsheng Long:
SimMTM: A Simple Pre-Training Framework for Masked Time-Series Modeling. CoRR abs/2302.00861 (2023) - [i67]Yang Shu, Xingzhuo Guo, Jialong Wu, Ximei Wang, Jianmin Wang, Mingsheng Long:
CLIPood: Generalizing CLIP to Out-of-Distributions. CoRR abs/2302.00864 (2023) - [i66]Kaichao You, Anchang Bao, Guo Qin, Meng Cao, Ping Huang, Jiulong Shan, Mingsheng Long:
Tune-Mode ConvBN Blocks For Efficient Transfer Learning. CoRR abs/2305.11624 (2023) - [i65]Jialong Wu, Haoyu Ma, Chaoyi Deng, Mingsheng Long:
Pre-training Contextualized World Models with In-the-wild Videos for Reinforcement Learning. CoRR abs/2305.18499 (2023) - [i64]Yong Liu, Chenyu Li, Jianmin Wang, Mingsheng Long:
Koopa: Learning Non-stationary Time Series Dynamics with Koopman Predictors. CoRR abs/2305.18803 (2023) - [i63]Haoyu Ma, Jialong Wu, Ningya Feng, Jianmin Wang, Mingsheng Long:
Harmony World Models: Boosting Sample Efficiency for Model-based Reinforcement Learning. CoRR abs/2310.00344 (2023) - [i62]Xingzhuo Guo, Junwei Pan, Ximei Wang, Baixu Chen, Jie Jiang, Mingsheng Long:
On the Embedding Collapse when Scaling up Recommendation Models. CoRR abs/2310.04400 (2023) - [i61]Yong Liu, Tengge Hu, Haoran Zhang, Haixu Wu, Shiyu Wang, Lintao Ma, Mingsheng Long:
iTransformer: Inverted Transformers Are Effective for Time Series Forecasting. CoRR abs/2310.06625 (2023) - [i60]Lanxiang Xing, Haixu Wu, Yuezhou Ma, Jianmin Wang, Mingsheng Long:
HelmSim: Learning Helmholtz Dynamics for Interpretable Fluid Simulation. CoRR abs/2310.10565 (2023) - 2022
- [j8]Kaichao You, Yong Liu, Ziyang Zhang, Jianmin Wang, Michael I. Jordan, Mingsheng Long:
Ranking and Tuning Pre-trained Models: A New Paradigm for Exploiting Model Hubs. J. Mach. Learn. Res. 23: 209:1-209:47 (2022) - [j7]Zhiyu Yao, Yunbo Wang, Jianmin Wang, Philip S. Yu, Mingsheng Long:
VideoDG: Generalizing Temporal Relations in Videos to Novel Domains. IEEE Trans. Pattern Anal. Mach. Intell. 44(11): 7989-8004 (2022) - [c91]Yiwen Qiu, Jialong Wu, Zhangjie Cao, Mingsheng Long:
Out-of-Dynamics Imitation Learning from Multimodal Demonstrations. CoRL 2022: 1071-1080 - [c90]Geng Chen, Wendong Zhang, Han Lu, Siyu Gao, Yunbo Wang, Mingsheng Long, Xiaokang Yang:
Continual Predictive Learning from Videos. CVPR 2022: 10718-10727 - [c89]Junguang Jiang, Baixu Chen, Jianmin Wang, Mingsheng Long:
Decoupled Adaptation for Cross-Domain Object Detection. ICLR 2022 - [c88]Ximei Wang, Xinyang Chen, Jianmin Wang, Mingsheng Long:
X-model: Improving Data Efficiency in Deep Learning with A Minimax Model. ICLR 2022 - [c87]Jiehui Xu, Haixu Wu, Jianmin Wang, Mingsheng Long:
Anomaly Transformer: Time Series Anomaly Detection with Association Discrepancy. ICLR 2022 - [c86]Haixu Wu, Jialong Wu, Jiehui Xu, Jianmin Wang, Mingsheng Long:
Flowformer: Linearizing Transformers with Conservation Flows. ICML 2022: 24226-24242 - [c85]Jialong Wu, Haixu Wu, Zihan Qiu, Jianmin Wang, Mingsheng Long:
Supported Policy Optimization for Offline Reinforcement Learning. NeurIPS 2022 - [c84]Baixu Chen, Junguang Jiang, Ximei Wang, Pengfei Wan, Jianmin Wang, Mingsheng Long:
Debiased Self-Training for Semi-Supervised Learning. NeurIPS 2022 - [c83]Yong Liu, Haixu Wu, Jianmin Wang, Mingsheng Long:
Non-stationary Transformers: Exploring the Stationarity in Time Series Forecasting. NeurIPS 2022 - [c82]Yang Shu, Zhangjie Cao, Ziyang Zhang, Jianmin Wang, Mingsheng Long:
Hub-Pathway: Transfer Learning from A Hub of Pre-trained Models. NeurIPS 2022 - [i59]Junguang Jiang, Yang Shu, Jianmin Wang, Mingsheng Long:
Transferability in Deep Learning: A Survey. CoRR abs/2201.05867 (2022) - [i58]Jialong Wu, Haixu Wu, Zihan Qiu, Jianmin Wang, Mingsheng Long:
Supported Policy Optimization for Offline Reinforcement Learning. CoRR abs/2202.06239 (2022) - [i57]Haixu Wu, Jialong Wu, Jiehui Xu, Jianmin Wang, Mingsheng Long:
Flowformer: Linearizing Transformers with Conservation Flows. CoRR abs/2202.06258 (2022) - [i56]Baixu Chen, Junguang Jiang, Ximei Wang, Jianmin Wang, Mingsheng Long:
Debiased Pseudo Labeling in Self-Training. CoRR abs/2202.07136 (2022) - [i55]Zhangjie Cao, Kaichao You, Ziyang Zhang, Jianmin Wang, Mingsheng Long:
From Big to Small: Adaptive Learning to Partial-Set Domains. CoRR abs/2203.07375 (2022) - [i54]Geng Chen, Wendong Zhang, Han Lu, Siyu Gao, Yunbo Wang, Mingsheng Long, Xiaokang Yang:
Continual Predictive Learning from Videos. CoRR abs/2204.05624 (2022) - [i53]Chao Huang, Zhangjie Cao, Yunbo Wang, Jianmin Wang, Mingsheng Long:
MetaSets: Meta-Learning on Point Sets for Generalizable Representations. CoRR abs/2204.07311 (2022) - [i52]Yong Liu, Haixu Wu, Jianmin Wang, Mingsheng Long:
Non-stationary Transformers: Rethinking the Stationarity in Time Series Forecasting. CoRR abs/2205.14415 (2022) - [i51]Yang Shu, Zhangjie Cao, Ziyang Zhang, Jianmin Wang, Mingsheng Long:
Hub-Pathway: Transfer Learning from A Hub of Pre-trained Models. CoRR abs/2206.03726 (2022) - [i50]Zhiyu Yao, Xinyang Chen, Sinan Wang, Qinyan Dai, Yumeng Li, Tanchao Zhu, Mingsheng Long:
Recommender Transformers with Behavior Pathways. CoRR abs/2206.06804 (2022) - [i49]Haixu Wu, Tengge Hu, Yong Liu, Hang Zhou, Jianmin Wang, Mingsheng Long:
TimesNet: Temporal 2D-Variation Modeling for General Time Series Analysis. CoRR abs/2210.02186 (2022) - [i48]Yiwen Qiu, Jialong Wu, Zhangjie Cao, Mingsheng Long:
Out-of-Dynamics Imitation Learning from Multimodal Demonstrations. CoRR abs/2211.06839 (2022) - 2021
- [j6]Min-Ling Zhang, Sheng-Jun Huang, Mingsheng Long:
Preface. J. Comput. Sci. Technol. 36(3): 588-589 (2021) - [c81]Junguang Jiang, Yifei Ji, Ximei Wang, Yufeng Liu, Jianmin Wang, Mingsheng Long:
Regressive Domain Adaptation for Unsupervised Keypoint Detection. CVPR 2021: 6780-6789 - [c80]Bo Fu, Zhangjie Cao, Jianmin Wang, Mingsheng Long:
Transferable Query Selection for Active Domain Adaptation. CVPR 2021: 7272-7281 - [c79]Chao Huang, Zhangjie Cao, Yunbo Wang, Jianmin Wang, Mingsheng Long:
MetaSets: Meta-Learning on Point Sets for Generalizable Representations. CVPR 2021: 8863-8872 - [c78]Yang Shu, Zhangjie Cao, Chenyu Wang, Jianmin Wang, Mingsheng Long:
Open Domain Generalization with Domain-Augmented Meta-Learning. CVPR 2021: 9624-9633 - [c77]Haixu Wu, Zhiyu Yao, Jianmin Wang, Mingsheng Long:
MotionRNN: A Flexible Model for Video Prediction With Spacetime-Varying Motions. CVPR 2021: 15435-15444 - [c76]Xinyang Chen, Sinan Wang, Jianmin Wang, Mingsheng Long:
Representation Subspace Distance for Domain Adaptation Regression. ICML 2021: 1749-1759 - [c75]Yang Shu, Zhi Kou, Zhangjie Cao, Jianmin Wang, Mingsheng Long:
Zoo-Tuning: Adaptive Transfer from A Zoo of Models. ICML 2021: 9626-9637 - [c74]Ximei Wang, Jinghan Gao, Mingsheng Long, Jianmin Wang:
Self-Tuning for Data-Efficient Deep Learning. ICML 2021: 10738-10748 - [c73]Kaichao You, Yong Liu, Jianmin Wang, Mingsheng Long:
LogME: Practical Assessment of Pre-trained Models for Transfer Learning. ICML 2021: 12133-12143 - [c72]Haixu Wu, Jiehui Xu, Jianmin Wang, Mingsheng Long:
Autoformer: Decomposition Transformers with Auto-Correlation for Long-Term Series Forecasting. NeurIPS 2021: 22419-22430 - [c71]Hong Liu, Jianmin Wang, Mingsheng Long:
Cycle Self-Training for Domain Adaptation. NeurIPS 2021: 22968-22981 - [i47]Kaichao You, Yong Liu, Mingsheng Long, Jianmin Wang:
LogME: Practical Assessment of Pre-trained Models for Transfer Learning. CoRR abs/2102.11005 (2021) - [i46]Ximei Wang, Jinghan Gao, Jianmin Wang, Mingsheng Long:
Self-Tuning for Data-Efficient Deep Learning. CoRR abs/2102.12903 (2021) - [i45]Haixu Wu, Zhiyu Yao, Mingsheng Long, Jianmin Wang:
MotionRNN: A Flexible Model for Video Prediction with Spacetime-Varying Motions. CoRR abs/2103.02243 (2021) - [i44]Hong Liu, Jianmin Wang, Mingsheng Long:
Cycle Self-Training for Domain Adaptation. CoRR abs/2103.03571 (2021) - [i43]Junguang Jiang, Yifei Ji, Ximei Wang, Yufeng Liu, Jianmin Wang, Mingsheng Long:
Regressive Domain Adaptation for Unsupervised Keypoint Detection. CoRR abs/2103.06175 (2021) - [i42]Yunbo Wang, Haixu Wu, Jianjin Zhang, Zhifeng Gao, Jianmin Wang, Philip S. Yu, Mingsheng Long:
PredRNN: A Recurrent Neural Network for Spatiotemporal Predictive Learning. CoRR abs/2103.09504 (2021) - [i41]Yang Shu, Zhangjie Cao, Chenyu Wang, Jianmin Wang, Mingsheng Long:
Open Domain Generalization with Domain-Augmented Meta-Learning. CoRR abs/2104.03620 (2021) - [i40]Haixu Wu, Jiehui Xu, Jianmin Wang, Mingsheng Long:
Autoformer: Decomposition Transformers with Auto-Correlation for Long-Term Series Forecasting. CoRR abs/2106.13008 (2021) - [i39]Yang Shu, Zhi Kou, Zhangjie Cao, Jianmin Wang, Mingsheng Long:
Zoo-Tuning: Adaptive Transfer from a Zoo of Models. CoRR abs/2106.15434 (2021) - [i38]Junguang Jiang, Baixu Chen, Jianmin Wang, Mingsheng Long:
Decoupled Adaptation for Cross-Domain Object Detection. CoRR abs/2110.02578 (2021) - [i37]Jiehui Xu, Haixu Wu, Jianmin Wang, Mingsheng Long:
Anomaly Transformer: Time Series Anomaly Detection with Association Discrepancy. CoRR abs/2110.02642 (2021) - [i36]Zhiyu Yao, Yunbo Wang, Haixu Wu, Jianmin Wang, Mingsheng Long:
ModeRNN: Harnessing Spatiotemporal Mode Collapse in Unsupervised Predictive Learning. CoRR abs/2110.03882 (2021) - [i35]Ximei Wang, Xinyang Chen, Jianmin Wang, Mingsheng Long:
X-model: Improving Data Efficiency in Deep Learning with A Minimax Model. CoRR abs/2110.04572 (2021) - [i34]Yang Shu, Zhangjie Cao, Jinghan Gao, Jianmin Wang, Mingsheng Long:
Omni-Training for Data-Efficient Deep Learning. CoRR abs/2110.07510 (2021) - [i33]Kaichao You, Yong Liu, Jianmin Wang, Michael I. Jordan, Mingsheng Long:
Ranking and Tuning Pre-trained Models: A New Paradigm of Exploiting Model Hubs. CoRR abs/2110.10545 (2021) - 2020
- [c70]Liang Li, Weirui Ye, Mingsheng Long, Yateng Tang, Jin Xu, Jianmin Wang:
Simultaneous Learning of Pivots and Representations for Cross-Domain Sentiment Classification. AAAI 2020: 8220-8227 - [c69]Ying Jin, Zhangjie Cao, Mingsheng Long, Jianmin Wang:
Transferring Pretrained Networks to Small Data via Category Decorrelation. BMVC 2020 - [c68]Sinan Wang, Xinyang Chen, Yunbo Wang, Mingsheng Long, Jianmin Wang:
Progressive Adversarial Networks for Fine-Grained Domain Adaptation. CVPR 2020: 9210-9219 - [c67]Yunbo Wang, Jiajun Wu, Mingsheng Long, Joshua B. Tenenbaum:
Probabilistic Video Prediction From Noisy Data With a Posterior Confidence. CVPR 2020: 10827-10836 - [c66]Bin Liu, Yue Cao, Yutong Lin, Qi Li, Zheng Zhang, Mingsheng Long, Han Hu:
Negative Margin Matters: Understanding Margin in Few-Shot Classification. ECCV (4) 2020: 438-455 - [c65]Ying Jin, Ximei Wang, Mingsheng Long, Jianmin Wang:
Minimum Class Confusion for Versatile Domain Adaptation. ECCV (21) 2020: 464-480 - [c64]Bo Fu, Zhangjie Cao, Mingsheng Long, Jianmin Wang:
Learning to Detect Open Classes for Universal Domain Adaptation. ECCV (15) 2020: 567-583 - [c63]Ying Jin, Yunbo Wang, Mingsheng Long, Jianmin Wang, Philip S. Yu, Jiaguang Sun:
A Multi-Player Minimax Game for Generative Adversarial Networks. ICME 2020: 1-6 - [c62]Zhiyu Yao, Yunbo Wang, Mingsheng Long, Jianmin Wang, Philip S. Yu, Jiaguang Sun:
Multi-Task Learning of Generalizable Representations for Video Action Recognition. ICME 2020: 1-6 - [c61]Zhiyu Yao, Yunbo Wang, Mingsheng Long, Jianmin Wang:
Unsupervised Transfer Learning for Spatiotemporal Predictive Networks. ICML 2020: 10778-10788 - [c60]Junguang Jiang, Ximei Wang, Mingsheng Long, Jianmin Wang:
Resource Efficient Domain Adaptation. ACM Multimedia 2020: 2220-2228 - [c59]Zhi Kou, Kaichao You, Mingsheng Long, Jianmin Wang:
Stochastic Normalization. NeurIPS 2020 - [c58]Hong Liu, Mingsheng Long, Jianmin Wang, Yu Wang:
Learning to Adapt to Evolving Domains. NeurIPS 2020 - [c57]Ximei Wang, Mingsheng Long, Jianmin Wang, Michael I. Jordan:
Transferable Calibration with Lower Bias and Variance in Domain Adaptation. NeurIPS 2020 - [c56]Kaichao You, Zhi Kou, Mingsheng Long, Jianmin Wang:
Co-Tuning for Transfer Learning. NeurIPS 2020 - [i32]Bin Liu, Yue Cao, Yutong Lin, Qi Li, Zheng Zhang, Mingsheng Long, Han Hu:
Negative Margin Matters: Understanding Margin in Few-shot Classification. CoRR abs/2003.12060 (2020) - [i31]Ximei Wang, Mingsheng Long, Jianmin Wang, Michael I. Jordan:
Transferable Calibration with Lower Bias and Variance in Domain Adaptation. CoRR abs/2007.08259 (2020) - [i30]Yuchen Zhang, Mingsheng Long, Jianmin Wang, Michael I. Jordan:
On Localized Discrepancy for Domain Adaptation. CoRR abs/2008.06242 (2020) - [i29]Zhiyu Yao, Yunbo Wang, Mingsheng Long, Jianmin Wang:
Unsupervised Transfer Learning for Spatiotemporal Predictive Networks. CoRR abs/2009.11763 (2020) - [i28]Jincheng Zhong, Ximei Wang, Zhi Kou, Jianmin Wang, Mingsheng Long:
Bi-tuning of Pre-trained Representations. CoRR abs/2011.06182 (2020)
2010 – 2019
- 2019
- [j5]Mingsheng Long, Yue Cao, Zhangjie Cao, Jianmin Wang, Michael I. Jordan:
Transferable Representation Learning with Deep Adaptation Networks. IEEE Trans. Pattern Anal. Mach. Intell. 41(12): 3071-3085 (2019) - [c55]Yang Shu, Zhangjie Cao, Mingsheng Long, Jianmin Wang:
Transferable Curriculum for Weakly-Supervised Domain Adaptation. AAAI 2019: 4951-4958 - [c54]Ximei Wang, Liang Li, Weirui Ye, Mingsheng Long, Jianmin Wang:
Transferable Attention for Domain Adaptation. AAAI 2019: 5345-5352 - [c53]Kaichao You, Mingsheng Long, Zhangjie Cao, Jianmin Wang, Michael I. Jordan:
Universal Domain Adaptation. CVPR 2019: 2720-2729 - [c52]Hong Liu, Zhangjie Cao, Mingsheng Long, Jianmin Wang, Qiang Yang:
Separate to Adapt: Open Set Domain Adaptation via Progressive Separation. CVPR 2019: 2927-2936 - [c51]Zhangjie Cao, Kaichao You, Mingsheng Long, Jianmin Wang, Qiang Yang:
Learning to Transfer Examples for Partial Domain Adaptation. CVPR 2019: 2985-2994 - [c50]Yunbo Wang, Jianjin Zhang, Hongyu Zhu, Mingsheng Long, Jianmin Wang, Philip S. Yu:
Memory in Memory: A Predictive Neural Network for Learning Higher-Order Non-Stationarity From Spatiotemporal Dynamics. CVPR 2019: 9154-9162 - [c49]Rong Kang, Yue Cao, Mingsheng Long, Jianmin Wang, Philip S. Yu:
Maximum-Margin Hamming Hashing. ICCV 2019: 8251-8260 - [c48]Yunbo Wang, Lu Jiang, Ming-Hsuan Yang, Li-Jia Li, Mingsheng Long, Li Fei-Fei:
Eidetic 3D LSTM: A Model for Video Prediction and Beyond. ICLR (Poster) 2019 - [c47]Jianjin Zhang, Yunbo Wang, Mingsheng Long, Jianmin Wang, Philip S. Yu:
Z-Order Recurrent Neural Networks for Video Prediction. ICME 2019: 230-235 - [c46]Xinyang Chen, Sinan Wang, Mingsheng Long, Jianmin Wang:
Transferability vs. Discriminability: Batch Spectral Penalization for Adversarial Domain Adaptation. ICML 2019: 1081-1090 - [c45]Hong Liu, Mingsheng Long, Jianmin Wang, Michael I. Jordan:
Transferable Adversarial Training: A General Approach to Adapting Deep Classifiers. ICML 2019: 4013-4022 - [c44]Kaichao You, Ximei Wang, Mingsheng Long, Michael I. Jordan:
Towards Accurate Model Selection in Deep Unsupervised Domain Adaptation. ICML 2019: 7124-7133 - [c43]Yuchen Zhang, Tianle Liu, Mingsheng Long, Michael I. Jordan:
Bridging Theory and Algorithm for Domain Adaptation. ICML 2019: 7404-7413 - [c42]Xinyang Chen, Sinan Wang, Bo Fu, Mingsheng Long, Jianmin Wang:
Catastrophic Forgetting Meets Negative Transfer: Batch Spectral Shrinkage for Safe Transfer Learning. NeurIPS 2019: 1906-1916 - [c41]Ximei Wang, Ying Jin, Mingsheng Long, Jianmin Wang, Michael I. Jordan:
Transferable Normalization: Towards Improving Transferability of Deep Neural Networks. NeurIPS 2019: 1951-1961 - [i27]Bin Liu, Yue Cao, Mingsheng Long, Jianmin Wang, Jingdong Wang:
Deep Triplet Quantization. CoRR abs/1902.00153 (2019) - [i26]Binhang Yuan, Chen Wang, Fei Jiang, Mingsheng Long, Philip S. Yu, Yuan Liu:
WaveletFCNN: A Deep Time Series Classification Model for Wind Turbine Blade Icing Detection. CoRR abs/1902.05625 (2019) - [i25]Yunbo Wang, Mingsheng Long, Jianmin Wang, Philip S. Yu:
Spatiotemporal Pyramid Network for Video Action Recognition. CoRR abs/1903.01038 (2019) - [i24]Zhangjie Cao, Kaichao You, Mingsheng Long, Jianmin Wang, Qiang Yang:
Learning to Transfer Examples for Partial Domain Adaptation. CoRR abs/1903.12230 (2019) - [i23]Yuchen Zhang, Tianle Liu, Mingsheng Long, Michael I. Jordan:
Bridging Theory and Algorithm for Domain Adaptation. CoRR abs/1904.05801 (2019) - [i22]Chen Qian, Lijie Wen, Mingsheng Long, Yanwei Li, Akhil Kumar, Jianmin Wang:
Process Extraction from Texts via Multi-Task Architecture. CoRR abs/1906.02127 (2019) - [i21]Kaichao You, Mingsheng Long, Michael I. Jordan, Jianmin Wang:
Learning Stages: Phenomenon, Root Cause, Mechanism Hypothesis, and Implications. CoRR abs/1908.01878 (2019) - [i20]Hong Liu, Mingsheng Long, Jianmin Wang, Michael I. Jordan:
Towards Understanding the Transferability of Deep Representations. CoRR abs/1909.12031 (2019) - [i19]Ying Jin, Ximei Wang, Mingsheng Long, Jianmin Wang:
Less Confusion More Transferable: Minimum Class Confusion for Versatile Domain Adaptation. CoRR abs/1912.03699 (2019) - [i18]Zhiyu Yao, Yunbo Wang, Xingqiang Du, Mingsheng Long, Jianmin Wang:
Adversarial Pyramid Network for Video Domain Generalization. CoRR abs/1912.03716 (2019) - 2018
- [c40]Yue Cao, Mingsheng Long, Jianmin Wang:
Unsupervised Domain Adaptation With Distribution Matching Machines. AAAI 2018: 2795-2802 - [c39]Zhongyi Pei, Zhangjie Cao, Mingsheng Long, Jianmin Wang:
Multi-Adversarial Domain Adaptation. AAAI 2018: 3934-3941 - [c38]Zhangjie Cao, Mingsheng Long, Chao Huang, Jianmin Wang:
Transfer Adversarial Hashing for Hamming Space Retrieval. AAAI 2018: 6698-6705 - [c37]Yue Cao, Mingsheng Long, Bin Liu, Jianmin Wang:
Deep Cauchy Hashing for Hamming Space Retrieval. CVPR 2018: 1229-1237 - [c36]Yue Cao, Bin Liu, Mingsheng Long, Jianmin Wang:
HashGAN: Deep Learning to Hash With Pair Conditional Wasserstein GAN. CVPR 2018: 1287-1296 - [c35]Zhangjie Cao, Mingsheng Long, Jianmin Wang, Michael I. Jordan:
Partial Transfer Learning With Selective Adversarial Networks. CVPR 2018: 2724-2732 - [c34]Zhangjie Cao, Lijia Ma, Mingsheng Long, Jianmin Wang:
Partial Adversarial Domain Adaptation. ECCV (8) 2018: 139-155 - [c33]Yue Cao, Bin Liu, Mingsheng Long, Jianmin Wang:
Cross-Modal Hamming Hashing. ECCV (1) 2018: 207-223 - [c32]Yunbo Wang, Zhifeng Gao, Mingsheng Long, Jianmin Wang, Philip S. Yu:
PredRNN++: Towards A Resolution of the Deep-in-Time Dilemma in Spatiotemporal Predictive Learning. ICML 2018: 5110-5119 - [c31]Ziru Xu, Yunbo Wang, Mingsheng Long, Jianmin Wang:
PredCNN: Predictive Learning with Cascade Convolutions. IJCAI 2018: 2940-2947 - [c30]Bin Liu, Yue Cao, Mingsheng Long, Jianmin Wang, Jingdong Wang:
Deep Triplet Quantization. ACM Multimedia 2018: 755-763 - [c29]Zhangjie Cao, Ziping Sun, Mingsheng Long, Jianmin Wang, Philip S. Yu:
Deep Priority Hashing. ACM Multimedia 2018: 1653-1661 - [c28]Mingsheng Long, Zhangjie Cao, Jianmin Wang, Michael I. Jordan:
Conditional Adversarial Domain Adaptation. NeurIPS 2018: 1647-1657 - [c27]Shichen Liu, Mingsheng Long, Jianmin Wang, Michael I. Jordan:
Generalized Zero-Shot Learning with Deep Calibration Network. NeurIPS 2018: 2009-2019 - [i17]Yunbo Wang, Zhifeng Gao, Mingsheng Long, Jianmin Wang, Philip S. Yu:
PredRNN++: Towards A Resolution of the Deep-in-Time Dilemma in Spatiotemporal Predictive Learning. CoRR abs/1804.06300 (2018) - [i16]Zhangjie Cao, Lijia Ma, Mingsheng Long, Jianmin Wang:
Partial Adversarial Domain Adaptation. CoRR abs/1808.04205 (2018) - [i15]Zhangjie Cao, Ziping Sun, Mingsheng Long, Jianmin Wang, Philip S. Yu:
Deep Priority Hashing. CoRR abs/1809.01238 (2018) - [i14]Zhongyi Pei, Zhangjie Cao, Mingsheng Long, Jianmin Wang:
Multi-Adversarial Domain Adaptation. CoRR abs/1809.02176 (2018) - [i13]Yunbo Wang, Jianjin Zhang, Hongyu Zhu, Mingsheng Long, Jianmin Wang, Philip S. Yu:
Memory In Memory: A Predictive Neural Network for Learning Higher-Order Non-Stationarity from Spatiotemporal Dynamics. CoRR abs/1811.07490 (2018) - [i12]Yunbo Wang, Zhiyu Yao, Hongyu Zhu, Mingsheng Long, Jianmin Wang, Philip S. Yu:
Reversing Two-Stream Networks with Decoding Discrepancy Penalty for Robust Action Recognition. CoRR abs/1811.08362 (2018) - 2017
- [c26]Zhangjie Cao, Mingsheng Long, Jianmin Wang, Qiang Yang:
Transitive Hashing Network for Heterogeneous Multimedia Retrieval. AAAI 2017: 81-87 - [c25]Yue Cao, Mingsheng Long, Jianmin Wang, Shichen Liu:
Collective Deep Quantization for Efficient Cross-Modal Retrieval. AAAI 2017: 3974-3980 - [c24]Yue Cao, Mingsheng Long, Jianmin Wang:
Correlation Hashing Network for Efficient Cross-Modal Retrieval. BMVC 2017 - [c23]Yue Cao, Mingsheng Long, Jianmin Wang, Shichen Liu:
Deep Visual-Semantic Quantization for Efficient Image Retrieval. CVPR 2017: 916-925 - [c22]Yunbo Wang, Mingsheng Long, Jianmin Wang, Philip S. Yu:
Spatiotemporal Pyramid Network for Video Action Recognition. CVPR 2017: 2097-2106 - [c21]Zhangjie Cao, Mingsheng Long, Jianmin Wang, Philip S. Yu:
HashNet: Deep Learning to Hash by Continuation. ICCV 2017: 5609-5618 - [c20]Mingsheng Long, Han Zhu, Jianmin Wang, Michael I. Jordan:
Deep Transfer Learning with Joint Adaptation Networks. ICML 2017: 2208-2217 - [c19]Yunbo Wang, Mingsheng Long, Jianmin Wang, Zhifeng Gao, Philip S. Yu:
PredRNN: Recurrent Neural Networks for Predictive Learning using Spatiotemporal LSTMs. NIPS 2017: 879-888 - [c18]Mingsheng Long, Zhangjie Cao, Jianmin Wang, Philip S. Yu:
Learning Multiple Tasks with Multilinear Relationship Networks. NIPS 2017: 1594-1603 - [i11]Zhangjie Cao, Mingsheng Long, Jianmin Wang, Philip S. Yu:
HashNet: Deep Learning to Hash by Continuation. CoRR abs/1702.00758 (2017) - [i10]Mingsheng Long, Zhangjie Cao, Jianmin Wang, Michael I. Jordan:
Domain Adaptation with Randomized Multilinear Adversarial Networks. CoRR abs/1705.10667 (2017) - [i9]Zhangjie Cao, Mingsheng Long, Jianmin Wang, Michael I. Jordan:
Partial Transfer Learning with Selective Adversarial Networks. CoRR abs/1707.07901 (2017) - [i8]Zhangjie Cao, Mingsheng Long, Chao Huang, Jianmin Wang:
Transfer Adversarial Hashing for Hamming Space Retrieval. CoRR abs/1712.04616 (2017) - 2016
- [j4]Mingsheng Long, Jianmin Wang, Yue Cao, Jia-Guang Sun, Philip S. Yu:
Deep Learning of Transferable Representation for Scalable Domain Adaptation. IEEE Trans. Knowl. Data Eng. 28(8): 2027-2040 (2016) - [c17]Han Zhu, Mingsheng Long, Jianmin Wang, Yue Cao:
Deep Hashing Network for Efficient Similarity Retrieval. AAAI 2016: 2415-2421 - [c16]Yue Cao, Mingsheng Long, Jianmin Wang, Han Zhu, Qingfu Wen:
Deep Quantization Network for Efficient Image Retrieval. AAAI 2016: 3457-3463 - [c15]Yue Cao, Mingsheng Long, Jianmin Wang, Qiang Yang, Philip S. Yu:
Deep Visual-Semantic Hashing for Cross-Modal Retrieval. KDD 2016: 1445-1454 - [c14]Yue Cao, Mingsheng Long, Jianmin Wang, Han Zhu:
Correlation Autoencoder Hashing for Supervised Cross-Modal Search. ICMR 2016: 197-204 - [c13]Mingsheng Long, Han Zhu, Jianmin Wang, Michael I. Jordan:
Unsupervised Domain Adaptation with Residual Transfer Networks. NIPS 2016: 136-144 - [c12]Mingsheng Long, Yue Cao, Jianmin Wang, Philip S. Yu:
Composite Correlation Quantization for Efficient Multimodal Retrieval. SIGIR 2016: 579-588 - [i7]Mingsheng Long, Jianmin Wang, Michael I. Jordan:
Unsupervised Domain Adaptation with Residual Transfer Networks. CoRR abs/1602.04433 (2016) - [i6]Yue Cao, Mingsheng Long, Jianmin Wang:
Correlation Hashing Network for Efficient Cross-Modal Retrieval. CoRR abs/1602.06697 (2016) - [i5]Mingsheng Long, Jianmin Wang, Michael I. Jordan:
Deep Transfer Learning with Joint Adaptation Networks. CoRR abs/1605.06636 (2016) - [i4]Zhangjie Cao, Mingsheng Long, Qiang Yang:
Transitive Hashing Network for Heterogeneous Multimedia Retrieval. CoRR abs/1608.04307 (2016) - 2015
- [j3]Mingsheng Long, Jianmin Wang, Jia-Guang Sun, Philip S. Yu:
Domain Invariant Transfer Kernel Learning. IEEE Trans. Knowl. Data Eng. 27(6): 1519-1532 (2015) - [c11]Mingsheng Long, Yue Cao, Jianmin Wang, Michael I. Jordan:
Learning Transferable Features with Deep Adaptation Networks. ICML 2015: 97-105 - [i3]Mingsheng Long, Jianmin Wang:
Learning Transferable Features with Deep Adaptation Networks. CoRR abs/1502.02791 (2015) - [i2]Mingsheng Long, Jianmin Wang, Philip S. Yu:
Compositional Correlation Quantization for Large-Scale Multimodal Search. CoRR abs/1504.04818 (2015) - [i1]Mingsheng Long, Jianmin Wang:
Learning Multiple Tasks with Deep Relationship Networks. CoRR abs/1506.02117 (2015) - 2014
- [j2]Mingsheng Long, Jianmin Wang, Guiguang Ding, Sinno Jialin Pan, Philip S. Yu:
Adaptation Regularization: A General Framework for Transfer Learning. IEEE Trans. Knowl. Data Eng. 26(5): 1076-1089 (2014) - [j1]Mingsheng Long, Jianmin Wang, Guiguang Ding, Dou Shen, Qiang Yang:
Transfer Learning with Graph Co-Regularization. IEEE Trans. Knowl. Data Eng. 26(7): 1805-1818 (2014) - [c10]Xiangdong Huang, Jianmin Wang, Jian Bai, Guiguang Ding, Mingsheng Long:
Inherent Replica Inconsistency in Cassandra. BigData Congress 2014: 740-747 - [c9]Mingsheng Long, Jianmin Wang, Guiguang Ding, Jiaguang Sun, Philip S. Yu:
Transfer Joint Matching for Unsupervised Domain Adaptation. CVPR 2014: 1410-1417 - [c8]Wu Xiang, Jianmin Wang, Mingsheng Long:
Local Hybrid Coding for Image Classification. ICPR 2014: 3744-3749 - 2013
- [c7]Mingsheng Long, Guiguang Ding, Jianmin Wang, Jiaguang Sun, Yuchen Guo, Philip S. Yu:
Transfer Sparse Coding for Robust Image Representation. CVPR 2013: 407-414 - [c6]Mingsheng Long, Jianmin Wang, Guiguang Ding, Jiaguang Sun, Philip S. Yu:
Transfer Feature Learning with Joint Distribution Adaptation. ICCV 2013: 2200-2207 - [c5]Jiangfeng Shi, Mingsheng Long, Qiang Liu, Guiguang Ding, Jianmin Wang:
Twin Bridge Transfer Learning for Sparse Collaborative Filtering. PAKDD (1) 2013: 496-507 - 2012
- [c4]Lianghao Li, Xiaoming Jin, Mingsheng Long:
Topic Correlation Analysis for Cross-Domain Text Classification. AAAI 2012: 998-1004 - [c3]Mingsheng Long, Jianmin Wang, Guiguang Ding, Dou Shen, Qiang Yang:
Transfer Learning with Graph Co-Regularization. AAAI 2012: 1033-1039 - [c2]Mingsheng Long, Jianmin Wang, Guiguang Ding, Wei Cheng, Xiang Zhang, Wei Wang:
Dual Transfer Learning. SDM 2012: 540-551 - 2010
- [c1]Mingsheng Long, Wei Cheng, Xiaoming Jin, Jianmin Wang, Dou Shen:
Transfer Learning via Cluster Correspondence Inference. ICDM 2010: 917-922
Coauthor Index
manage site settings
To protect your privacy, all features that rely on external API calls from your browser are turned off by default. You need to opt-in for them to become active. All settings here will be stored as cookies with your web browser. For more information see our F.A.Q.
Unpaywalled article links
Add open access links from to the list of external document links (if available).
Privacy notice: By enabling the option above, your browser will contact the API of unpaywall.org to load hyperlinks to open access articles. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Unpaywall privacy policy.
Archived links via Wayback Machine
For web page which are no longer available, try to retrieve content from the of the Internet Archive (if available).
Privacy notice: By enabling the option above, your browser will contact the API of archive.org to check for archived content of web pages that are no longer available. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Internet Archive privacy policy.
Reference lists
Add a list of references from , , and to record detail pages.
load references from crossref.org and opencitations.net
Privacy notice: By enabling the option above, your browser will contact the APIs of crossref.org, opencitations.net, and semanticscholar.org to load article reference information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Crossref privacy policy and the OpenCitations privacy policy, as well as the AI2 Privacy Policy covering Semantic Scholar.
Citation data
Add a list of citing articles from and to record detail pages.
load citations from opencitations.net
Privacy notice: By enabling the option above, your browser will contact the API of opencitations.net and semanticscholar.org to load citation information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the OpenCitations privacy policy as well as the AI2 Privacy Policy covering Semantic Scholar.
OpenAlex data
Load additional information about publications from .
Privacy notice: By enabling the option above, your browser will contact the API of openalex.org to load additional information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the information given by OpenAlex.
last updated on 2024-12-04 20:09 CET by the dblp team
all metadata released as open data under CC0 1.0 license
see also: Terms of Use | Privacy Policy | Imprint