Jianmin Wang

52

Papers

1,760

Total Citations

Papers (52)

Unsupervised Domain Adaptation with Residual Transfer Networks

NeurIPS 2016arXiv

Learning Multiple Tasks with Multilinear Relationship Networks

NeurIPS 2017arXiv

Sundial: A Family of Highly Capable Time Series Foundation Models

Transolver++: An Accurate Neural Solver for PDEs on Million-Scale Geometries

HarmonyDream: Task Harmonization Inside World Models

Transolver: A Fast Transformer Solver for PDEs on General Geometries

HelmFluid: Learning Helmholtz Dynamics for Interpretable Fluid Prediction

Semantics-Preserving Hashing for Cross-View Retrieval

Deep Visual-Semantic Quantization for Efficient Image Retrieval

Spatiotemporal Pyramid Network for Video Action Recognition

Deep Cauchy Hashing for Hamming Space Retrieval

Partial Transfer Learning With Selective Adversarial Networks

Universal Domain Adaptation

Separate to Adapt: Open Set Domain Adaptation via Progressive Separation

Learning to Transfer Examples for Partial Domain Adaptation

Memory in Memory: A Predictive Neural Network for Learning Higher-Order Non-Stationarity From Spatiotemporal Dynamics

Progressive Adversarial Networks for Fine-Grained Domain Adaptation

Regressive Domain Adaptation for Unsupervised Keypoint Detection

MotionRNN: A Flexible Model for Video Prediction With Spacetime-Varying Motions

Transferable Query Selection for Active Domain Adaptation

Open Domain Generalization with Domain-Augmented Meta-Learning

MetaSets: Meta-Learning on Point Sets for Generalizable Representations

HashNet: Deep Learning to Hash by Continuation

Maximum-Margin Hamming Hashing

Learning to Detect Open Classes for Universal Domain Adaptation

Minimum Class Confusion for Versatile Domain Adaptation

PredRNN: Recurrent Neural Networks for Predictive Learning using Spatiotemporal LSTMs

HashGAN: Deep Learning to Hash With Pair Conditional Wasserstein GAN

CogDPM: Diffusion Probabilistic Models via Cognitive Predictive Coding

TimeSiam: A Pre-Training Framework for Siamese Time-Series Modeling

Timer: Generative Pre-trained Transformers Are Large Time Series Models

Generalized Zero-Shot Learning with Deep Calibration Network

Conditional Adversarial Domain Adaptation

Catastrophic Forgetting Meets Negative Transfer: Batch Spectral Shrinkage for Safe Transfer Learning

Transferable Normalization: Towards Improving Transferability of Deep Neural Networks

Stochastic Normalization

Co-Tuning for Transfer Learning

Transferable Calibration with Lower Bias and Variance in Domain Adaptation

Learning to Adapt to Evolving Domains

Autoformer: Decomposition Transformers with Auto-Correlation for Long-Term Series Forecasting

Cycle Self-Training for Domain Adaptation

Non-stationary Transformers: Exploring the Stationarity in Time Series Forecasting

Supported Policy Optimization for Offline Reinforcement Learning

Debiased Self-Training for Semi-Supervised Learning

Hub-Pathway: Transfer Learning from A Hub of Pre-trained Models

Koopa: Learning Non-stationary Time Series Dynamics with Koopman Predictors

SimMTM: A Simple Pre-Training Framework for Masked Time-Series Modeling

Learning Transferable Features with Deep Adaptation Networks

Deep Transfer Learning with Joint Adaptation Networks

PredRNN++: Towards A Resolution of the Deep-in-Time Dilemma in Spatiotemporal Predictive Learning

Transferability vs. Discriminability: Batch Spectral Penalization for Adversarial Domain Adaptation

Transferable Adversarial Training: A General Approach to Adapting Deep Classifiers