← Authors

Mingsheng Long

99 papers · 2013–2025 · 10 conferences · across top CS/AI conferences

Achievements

🐝 Cross-Pollinator (5) 🌍 Conference Polyglot (10) πŸƒ Academic Marathon (12) 🌈 Renaissance Researcher (8) πŸŒ‰ Interdisciplinary Bridge πŸ—ΊοΈ Taxonomy Completionist (10) 🧭 Keyword Pioneer 🐣 Hot Topic Early Bird 🏠 Conference Loyalist (27) 🌟 Keyword Trendsetter Combo (3) πŸ† Grand Slam πŸ‘‘ Triple Crown 🀝 Dynamic Duo (80) πŸ”¬ Deep Specialist (30) πŸ† Keyword Champion (7) πŸš€ Conference Pioneer πŸ—ƒοΈ Keyword Collector (295) πŸ“ˆ Trend Setter ⚑ Prolific Year (6) πŸ”₯ Unstoppable (13) πŸ’Ž Century Club (99)

Conferences

ICML (28) NIPS (27) CVPR (19) ICLR (11) ECCV (4) AAAI (3) ICCV (3) JMLR (2) CORL (1) IJCAI (1)

Top co-authors

Jianmin Wang (80) Haixu Wu (19) ZHANGJIE CAO (16) Ximei Wang (12) Yong Liu (11) Yunbo Wang (11) Jialong Wu (9) Michael I. Jordan (9) Kaichao You (9) Philip S. Yu (7)

Keywords

transfer learning (20) domain adaptation (20) adversarial learning (9) video prediction (7) representation learning (7) time series forecasting (6) unsupervised learning (6) recurrent neural network (5) pre-trained model (4) binary code (4) deep neural network (4) unsupervised domain adaptation (4) attention mechanism (4) image retrieval (4) predictive learning (4) world model (3) adversarial training (3) deep learning (3) model selection (3) knowledge transfer (3)

Papers

Domain Guidance: A Simple Transfer Approach for a Pre-trained Diffusion Model ICLR 2025
Dynamical Diffusion: Learning Temporal Dynamics with Diffusion Models ICLR 2025
Long-Sequence Recommendation Models Need Decoupled Embeddings ICLR 2025
depyf: Open the Opaque Box of PyTorch Compiler for Machine Learning Researchers JMLR 2025
Unisolver: PDE-Conditional Transformers Towards Universal Neural PDE Solvers ICML 2025
Trajectory World Models for Heterogeneous Environments ICML 2025
Transolver++: An Accurate Neural Solver for PDEs on Million-Scale Geometries ICML 2025
Sundial: A Family of Highly Capable Time Series Foundation Models ICML 2025
Timer-XL: Long-Context Transformers for Unified Time Series Forecasting ICLR 2025
Transolver: A Fast Transformer Solver for PDEs on General Geometries ICML 2024
Timer: Generative Pre-trained Transformers Are Large Time Series Models ICML 2024
On the Embedding Collapse when Scaling up Recommendation Models ICML 2024
TimeSiam: A Pre-Training Framework for Siamese Time-Series Modeling ICML 2024
Diffusion Tuning: Transferring Diffusion Models via Chain of Forgetting NIPS 2024
AutoTimes: Autoregressive Time Series Forecasters via Large Language Models NIPS 2024
DeepLag: Discovering Deep Lagrangian Dynamics for Intuitive Fluid Prediction NIPS 2024
iTransformer: Inverted Transformers Are Effective for Time Series Forecasting ICLR 2024
Efficient ConvBN Blocks for Transfer Learning and Beyond ICLR 2024
Mobile Attention: Mobile-Friendly Linear-Attention for Vision Transformers ICML 2024
HelmFluid: Learning Helmholtz Dynamics for Interpretable Fluid Prediction ICML 2024
HarmonyDream: Task Harmonization Inside World Models ICML 2024
CogDPM: Diffusion Probabilistic Models via Cognitive Predictive Coding ICML 2024
TimeXer: Empowering Transformers for Time Series Forecasting with Exogenous Variables NIPS 2024
iVideoGPT: Interactive VideoGPTs are Scalable World Models NIPS 2024
RoPINN: Region Optimized Physics-Informed Neural Networks NIPS 2024
Estimating Heterogeneous Treatment Effects: Mutual Information Bounds and Learning Algorithms ICML 2023
TimesNet: Temporal 2D-Variation Modeling for General Time Series Analysis ICLR 2023
Solving High-Dimensional PDEs with Latent Spectral Models ICML 2023
CLIPood: Generalizing CLIP to Out-of-Distributions ICML 2023
Koopa: Learning Non-stationary Time Series Dynamics with Koopman Predictors NIPS 2023
SimMTM: A Simple Pre-Training Framework for Masked Time-Series Modeling NIPS 2023
ForkMerge: Mitigating Negative Transfer in Auxiliary-Task Learning NIPS 2023
Pre-training Contextualized World Models with In-the-wild Videos for Reinforcement Learning NIPS 2023
Continual Predictive Learning From Videos CVPR 2022
Non-stationary Transformers: Exploring the Stationarity in Time Series Forecasting NIPS 2022
Supported Policy Optimization for Offline Reinforcement Learning NIPS 2022
Debiased Self-Training for Semi-Supervised Learning NIPS 2022
Hub-Pathway: Transfer Learning from A Hub of Pre-trained Models NIPS 2022
Out-of-Dynamics Imitation Learning from Multimodal Demonstrations CORL 2022
Decoupled Adaptation for Cross-Domain Object Detection ICLR 2022
X-model: Improving Data Efficiency in Deep Learning with A Minimax Model ICLR 2022
Anomaly Transformer: Time Series Anomaly Detection with Association Discrepancy ICLR 2022
Flowformer: Linearizing Transformers with Conservation Flows ICML 2022
Ranking and Tuning Pre-trained Models: A New Paradigm for Exploiting Model Hubs JMLR 2022
Zoo-Tuning: Adaptive Transfer from A Zoo of Models ICML 2021
Representation Subspace Distance for Domain Adaptation Regression ICML 2021
Regressive Domain Adaptation for Unsupervised Keypoint Detection CVPR 2021
MetaSets: Meta-Learning on Point Sets for Generalizable Representations CVPR 2021
MotionRNN: A Flexible Model for Video Prediction With Spacetime-Varying Motions CVPR 2021
Transferable Query Selection for Active Domain Adaptation CVPR 2021
Autoformer: Decomposition Transformers with Auto-Correlation for Long-Term Series Forecasting NIPS 2021
Cycle Self-Training for Domain Adaptation NIPS 2021
Open Domain Generalization with Domain-Augmented Meta-Learning CVPR 2021
LogME: Practical Assessment of Pre-trained Models for Transfer Learning ICML 2021
Self-Tuning for Data-Efficient Deep Learning ICML 2021
Transferable Calibration with Lower Bias and Variance in Domain Adaptation NIPS 2020
Unsupervised Transfer Learning for Spatiotemporal Predictive Networks ICML 2020
Learning to Adapt to Evolving Domains NIPS 2020
Simultaneous Learning of Pivots and Representations for Cross-Domain Sentiment Classification AAAI 2020
Probabilistic Video Prediction From Noisy Data With a Posterior Confidence CVPR 2020
Progressive Adversarial Networks for Fine-Grained Domain Adaptation CVPR 2020
Stochastic Normalization NIPS 2020
Negative Margin Matters: Understanding Margin in Few-shot Classification ECCV 2020
Learning to Detect Open Classes for Universal Domain Adaptation ECCV 2020
Co-Tuning for Transfer Learning NIPS 2020
Transferability vs. Discriminability: Batch Spectral Penalization for Adversarial Domain Adaptation ICML 2019
Maximum-Margin Hamming Hashing ICCV 2019
Eidetic 3D LSTM: A Model for Video Prediction and Beyond ICLR 2019
Universal Domain Adaptation CVPR 2019
Transferable Adversarial Training: A General Approach to Adapting Deep Classifiers ICML 2019
Towards Accurate Model Selection in Deep Unsupervised Domain Adaptation ICML 2019
Bridging Theory and Algorithm for Domain Adaptation ICML 2019
Transferable Attention for Domain Adaptation AAAI 2019
Transferable Curriculum for Weakly-Supervised Domain Adaptation AAAI 2019
Transferable Normalization: Towards Improving Transferability of Deep Neural Networks NIPS 2019
Catastrophic Forgetting Meets Negative Transfer: Batch Spectral Shrinkage for Safe Transfer Learning NIPS 2019
Separate to Adapt: Open Set Domain Adaptation via Progressive Separation CVPR 2019
Learning to Transfer Examples for Partial Domain Adaptation CVPR 2019
Memory in Memory: A Predictive Neural Network for Learning Higher-Order Non-Stationarity From Spatiotemporal Dynamics CVPR 2019
HashGAN: Deep Learning to Hash With Pair Conditional Wasserstein GAN CVPR 2018
Partial Transfer Learning With Selective Adversarial Networks CVPR 2018
Partial Adversarial Domain Adaptation ECCV 2018
Conditional Adversarial Domain Adaptation NIPS 2018
PredCNN: Predictive Learning with Cascade Convolutions IJCAI 2018
Generalized Zero-Shot Learning with Deep Calibration Network NIPS 2018
PredRNN++: Towards A Resolution of the Deep-in-Time Dilemma in Spatiotemporal Predictive Learning ICML 2018
Cross-Modal Hamming Hashing ECCV 2018
Deep Cauchy Hashing for Hamming Space Retrieval CVPR 2018
Spatiotemporal Pyramid Network for Video Action Recognition CVPR 2017
Deep Transfer Learning with Joint Adaptation Networks ICML 2017
Deep Visual-Semantic Quantization for Efficient Image Retrieval CVPR 2017
Learning Multiple Tasks with Multilinear Relationship Networks NIPS 2017
PredRNN: Recurrent Neural Networks for Predictive Learning using Spatiotemporal LSTMs NIPS 2017
HashNet: Deep Learning to Hash by Continuation ICCV 2017
Unsupervised Domain Adaptation with Residual Transfer Networks NIPS 2016
Learning Transferable Features with Deep Adaptation Networks ICML 2015
Transfer Joint Matching for Unsupervised Domain Adaptation CVPR 2014
Transfer Feature Learning with Joint Distribution Adaptation ICCV 2013
Transfer Sparse Coding for Robust Image Representation CVPR 2013