Mingsheng Long

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