龙明盛

2026

“风清”人工智能天气预报模型业务应用性能评估

《气象》

2026

面向富信息时序预测的元数据变换器网络

《中国科学:信息科学》

2026

TimeAgent: A Training-Free LLM Agent for Time Series Foundation Models

IEEE Transactions on Knowledge and Data Engineering

DOI

2026

Deep Time Series Models: A Comprehensive Survey and Benchmark

IEEE Transactions on Pattern Analysis and Machine Intelligence

DOI

2025

临近气象预报大模型“风雷”V1版本检验及个例评估

《气象》

2025

生成式设计：复杂装备设计智能化的新引擎

《计算》

2025

Jenga: Effective Memory Management for Serving LLM with Heterogeneity

Symposium on Operating Systems Principles

DOI

2025

RLVR-World: Training World Models with Reinforcement Learning

neural information processing systems

DOI

2025

FlashBias: Fast Computation of Attention with Bias

neural information processing systems

DOI

2025

PhySense: Sensor Placement Optimization for Accurate Physics Sensing

neural information processing systems

DOI

2024

Editorial: Learning With Fewer Labels in Computer Vision

IEEE Transactions on Pattern Analysis and Machine Intelligence

DOI

2023

基于深度强化学习和知识迁移的飞机装配脉动生产线调度方法

Scientia Sinica Informationis

DOI

2023

Skilful nowcasting of extreme precipitation with NowcastNet

Nature

DOI

2023

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

Neural Information Processing Systems

DOI

2023

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

Neural Information Processing Systems

DOI

2023

Estimating Heterogeneous Treatment Effects: Mutual Information Bounds and Learning Algorithms

International Conference on Machine Learning

2023

Interpretable weather forecasting for worldwide stations with a unified deep model

Nature Machine Intelligence

DOI

2023

Solving High-Dimensional PDEs with Latent Spectral Models

International Conference on Machine Learning

DOI

2022

基于无标签视频数据的深度预测学习方法综述

《电子学报》

2021

Journal of Computational Science and Technology: Preface

Journal of Computational Science and Technology

DOI

2021

Regressive Domain Adaptation for Unsupervised Keypoint Detection

Computer Vision and Pattern Recognition

DOI

2021

LogME: Practical Assessment of Pre-trained Models for Transfer Learning

International Conference on Machine Learning

2021

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

Computer Vision and Pattern Recognition

DOI

2021

Self-Tuning for Data-Efficient Deep Learning

International Conference on Machine Learning

2021

Cycle Self-Training for Domain Adaptation

Neural Information Processing Systems

2021

Representation Subspace Distance for Domain Adaptation Regression

International Conference on Machine Learning

2020

面向季节性时空数据的预测式循环网络及其在城市计算中的应用

《计算机学报》

2020

Probabilistic Video Prediction From Noisy Data With a Posterior Confidence

Computer Vision and Pattern Recognition

DOI

2020

Bi-tuning of Pre-trained Representations

arXiv.org

2020

Negative Margin Matters: Understanding Margin in Few-shot Classification

European Conference on Computer Vision

DOI

2020

Co-Tuning for Transfer Learning

Neural Information Processing Systems

2020

Transferable Calibration with Lower Bias and Variance in Domain Adaptation

Neural Information Processing Systems

2020

Stochastic Normalization

Neural Information Processing Systems

2020

Unsupervised Transfer Learning for Spatiotemporal Predictive Networks

International Conference on Machine Learning

2020

Resource Efficient Domain Adaptation

ACM Multimedia

DOI

2020

Transferring Pretrained Networks to Small Data via Category Decorrelation

British Machine Vision Conference

DOI

2020

Learning to Adapt to Evolving Domains

Neural Information Processing Systems

2020

On Localized Discrepancy for Domain Adaptation

arXiv.org

2020

Simultaneous Learning of Pivots and Representations for Cross-Domain Sentiment Classification

AAAI Conference on Artificial Intelligence

DOI

2020

Supplementary : Learning to Detect Open Classes for Universal Domain Adaptation

2020

Progressive Adversarial Networks for Fine-Grained Domain Adaptation

Computer Vision and Pattern Recognition

DOI

2020

Domain Adaptation in Computer Vision with Deep Learning

DOI

2019

循环神经网络在雷达临近预报中的应用

《应用气象学报》

2019

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

International Conference on Machine Learning

2019

Extracting Process Graphs from Texts via Multi-Granularity Text Classification

2019

Adversarial Pyramid Network for Video Domain Generalization

arXiv.org

2019

Unit Frame 3 : T + 2 Frame 1 : T Frame 2 : T + 1 FrameT + 1 FrameT + 2 FrameT + 3

2019

Learning Stages: Phenomenon, Root Cause, Mechanism Hypothesis, and Implications

arXiv.org

2019

Transferable Curriculum for Weakly-Supervised Domain Adaptation

AAAI Conference on Artificial Intelligence

DOI

2019

Transferable Adversarial Training: A General Approach to Adapting Deep Classifiers

International Conference on Machine Learning

2019

Z-Order Recurrent Neural Networks for Video Prediction

IEEE International Conference on Multimedia and Expo

DOI

2019

Eidetic 3D LSTM: A Model for Video Prediction and Beyond

International Conference on Learning Representations

2019

Transferable Representation Learning with Deep Adaptation Networks

IEEE Transactions on Pattern Analysis and Machine Intelligence

DOI

2019

Bridging Theory and Algorithm for Domain Adaptation

International Conference on Machine Learning

2019

How Does Learning Rate Decay Help Modern Neural Networks

2019

Towards Understanding the Transferability of Deep Representations

arXiv.org

2019

WaveletFCNN: A Deep Time Series Classification Model for Wind Turbine Blade Icing Detection

arXiv.org

2019

Universal Domain Adaptation

Computer Vision and Pattern Recognition

DOI

2019

Maximum-Margin Hamming Hashing

IEEE International Conference on Computer Vision

DOI

2019

Process Extraction from Texts via Multi-Task Architecture

arXiv.org

2019

WaveletAE: A Wavelet-enhanced Autoencoder for Wind Turbine Blade Icing Detection

2019

Towards Accurate Model Selection in Deep Unsupervised Domain Adaptation

International Conference on Machine Learning

DOI

2019

Learning to Transfer Examples for Partial Domain Adaptation

Computer Vision and Pattern Recognition

DOI

2019

Separate to Adapt: Open Set Domain Adaptation via Progressive Separation

Computer Vision and Pattern Recognition

DOI

2019

Transferable Normalization: Towards Improving Transferability of Deep Neural Networks

Neural Information Processing Systems

2019

Minimum Class Confusion for Versatile Domain Adaptation

European Conference on Computer Vision

DOI

2019

Transferable Attention for Domain Adaptation

AAAI Conference on Artificial Intelligence

DOI

2018

MICAPS4服务端系统架构设计

《应用气象学报》

2018

Deep Cauchy Hashing for Hamming Space Retrieval

2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition

DOI

2018

HashGAN: Deep Learning to Hash with Pair Conditional Wasserstein GAN

2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition

DOI

2018

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

Computer Vision and Pattern Recognition

DOI

2018

PredCNN: Predictive Learning with Cascade Convolutions

International Joint Conference on Artificial Intelligence

DOI

2018

Multi-Task Learning of Generalizable Representations for Video Action Recognition

IEEE International Conference on Multimedia and Expo

DOI

2018

Partial Adversarial Domain Adaptation

European Conference on Computer Vision

DOI

2018

Reversing Two-Stream Networks with Decoding Discrepancy Penalty for Robust Action Recognition

arXiv.org

2018

Deep Priority Hashing

ACM Multimedia

DOI

2018

Deep Triplet Quantization

ACM Multimedia

DOI

2018

Unsupervised Domain Adaptation With Distribution Matching Machines

AAAI Conference on Artificial Intelligence

DOI

2018

Cross-Modal Hamming Hashing

European Conference on Computer Vision

DOI

2018

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

International Conference on Machine Learning

2018

Generalized Zero-Shot Learning with Deep Calibration Network

Neural Information Processing Systems

2018

Multi-Adversarial Domain Adaptation

AAAI Conference on Artificial Intelligence

DOI

2018

3 Conditional Adversarial Domain Adaptation

2017

面向近似近邻查询的分布式哈希学习方法

《计算机学报》

2017

Partial Transfer Learning with Selective Adversarial Networks

2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition

DOI

2017

Domain Adaptation with Randomized Multilinear Adversarial Networks

arXiv.org

2017

PredRNN: Recurrent Neural Networks for Predictive Learning using Spatiotemporal LSTMs

Neural Information Processing Systems

2017

HashNet: Deep Learning to Hash by Continuation

IEEE International Conference on Computer Vision

DOI

2017

Collective Deep Quantization for Efficient Cross-Modal Retrieval

AAAI Conference on Artificial Intelligence

DOI

2017

Conditional Adversarial Domain Adaptation

Neural Information Processing Systems

2017

Deep Visual-Semantic Quantization for Efficient Image Retrieval

Computer Vision and Pattern Recognition

DOI

2017

Transfer Adversarial Hashing for Hamming Space Retrieval

AAAI Conference on Artificial Intelligence

DOI

2017

Spatiotemporal Pyramid Network for Video Action Recognition

Computer Vision and Pattern Recognition

DOI

2016

基于运行数据分析的Spark任务参数优化

《计算机工程与科学》

2016

Correlation Autoencoder Hashing for Supervised Cross-Modal Search

International Conference on Multimedia Retrieval

DOI

2016

Transitive Hashing Network for Heterogeneous Multimedia Retrieval

AAAI Conference on Artificial Intelligence

DOI

2016

Correlation Hashing Network for Efficient Cross-Modal Retrieval

British Machine Vision Conference

DOI

2016

Deep Visual-Semantic Hashing for Cross-Modal Retrieval

Knowledge Discovery and Data Mining

DOI

2016

Deep Transfer Learning with Joint Adaptation Networks

International Conference on Machine Learning

2016

Unsupervised Domain Adaptation with Residual Transfer Networks

Neural Information Processing Systems

2016

Deep Quantization Network for Efficient Image Retrieval

AAAI Conference on Artificial Intelligence

DOI

2016

Deep Hashing Network for Efficient Similarity Retrieval

AAAI Conference on Artificial Intelligence

DOI

2016

Deep Learning of Transferable Representation for Scalable Domain Adaptation

IEEE Transactions on Knowledge and Data Engineering

DOI

2015

Learning Multiple Tasks with Multilinear Relationship Networks

Neural Information Processing Systems

2015

Compositional Correlation Quantization for Large-Scale Multimodal Search

arXiv.org

2015

Domain Invariant Transfer Kernel Learning. (6)(2015)

2015

Learning Transferable Features with Deep Adaptation Networks

International Conference on Machine Learning

2015

Composite Correlation Quantization for Efficient Multimodal Retrieval

Annual International ACM SIGIR Conference on Research and Development in Information Retrieval

DOI

2015

Domain Invariant Transfer Kernel Learning

IEEE Transactions on Knowledge and Data Engineering

DOI

2014

迁移学习问题与方法研究

《清华大学》

2014

Adaptation Regularization: A General Framework for Transfer Learning

IEEE Transactions on Knowledge and Data Engineering

DOI

2014

Local Hybrid Coding for Image Classification

International Conference on Pattern Recognition

DOI

2014

Transfer Joint Matching for Unsupervised Domain Adaptation

2014 IEEE Conference on Computer Vision and Pattern Recognition

DOI

2013

Twin Bridge Transfer Learning for Sparse Collaborative Filtering

Pacific-Asia Conference on Knowledge Discovery and Data Mining

DOI

2013

Transfer Feature Learning with Joint Distribution Adaptation

IEEE International Conference on Computer Vision

DOI

2013

Transfer Sparse Coding for Robust Image Representation

2013 IEEE Conference on Computer Vision and Pattern Recognition

DOI

2012

Transfer Learning with Graph Co-Regularization

IEEE Transactions on Knowledge and Data Engineering

DOI

2012

Topic Correlation Analysis for Cross-Domain Text Classification

AAAI Conference on Artificial Intelligence

DOI

2012

Dual Transfer Learning

SDM

DOI

2010

Transfer Learning via Cluster Correspondence Inference

2010 IEEE International Conference on Data Mining

DOI

2019

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

neural information processing systems

2026

Timer-S1: A Billion-Scale Time Series Foundation Model with Serial Scaling

arXiv (Cornell University)

DOI

2026

It's TIME: Towards the Next Generation of Time Series Forecasting Benchmarks

arXiv (Cornell University)

DOI

2026

Visual Generation Unlocks Human-Like Reasoning through Multimodal World Models

arXiv (Cornell University)

DOI

2026

Brep2Shape: Boundary and Shape Representation Alignment via Self-Supervised Transformers

arXiv preprint

2026

Transolver-3: Scaling Up Transformer Solvers to Industrial-Scale Geometries

arXiv preprint

2026

DiTS: Multimodal Diffusion Transformers Are Time Series Forecasters

arXiv preprint

2026

NowcastDiT: Diffusion Transformers are Effective Precipitation Nowcasters

arXiv preprint

2026

JEPA-VLA: Video Predictive Embedding is Needed for VLA Models

arXiv preprint

2026

Transolver-$σ$: Joint Spectral-Physical Subspace Modeling for Neural PDE Solving

arXiv preprint

2026

S-Space: Exploring Spatial Workspace in Multimodal Language Models

arXiv preprint

2026

GeoPT: Scaling Physics Simulation via Lifted Geometric Pre-Training

arXiv preprint

2026

PhysFieldBench: Can Multimodal Models Understand Physical Fields?

arXiv preprint

2026

TimeVista: Exploring and Exploiting Vision-Language Models as Judges for Time Series Forecasting

arXiv preprint

2026

Code as Worlds: Agentic Discovery of Executable World Representations for Physical Reasoning

arXiv preprint

2026

AgentGarten: Code Worlds for Evolving Agents

arXiv preprint

2026

BTTackler: A Diagnosis-based Framework for Efficient Deep Learning Hyperparameter Optimization

arXiv preprint

2026

Timer-M1: A Multivariate Time Series Foundation Model via Learning Primitives

arXiv preprint

2026

Harnessing AI for Inverse Partial Differential Equation Problems: Past, Present, and Prospects

arXiv preprint

2026

Regression Models Meet Foundation Models: A Hybrid-AI Approach to Practical Electricity Price Forecasting

arXiv preprint

2025

Sundial: A Family of Highly Capable Time Series Foundation Models

arXiv (Cornell University)

DOI

2025

TimesBERT: A BERT-Style Foundation Model for Time Series Understanding

arXiv preprint

2025

Dynamical Diffusion: Learning Temporal Dynamics with Diffusion Models

arXiv preprint

2025

Exploring Accuracy Law for Deep Time Series Forecasters: An Empirical Study

arXiv preprint

2025

ProPINN: Demystifying Propagation Failures in Physics-Informed Neural Networks

arXiv preprint

2025

Trajectory World Models for Heterogeneous Environments

arXiv preprint

2025

Mitigating the Noise Shift for Denoising Generative Models via Noise Awareness Guidance

arXiv preprint

2025

Foresight Diffusion: Improving Sampling Consistency in Predictive Diffusion Models

arXiv preprint

2025

CoRA: Covariate-Aware Adaptation of Time Series Foundation Models

arXiv preprint

2025

Vid2World: Crafting Video Diffusion Models to Interactive World Models

arXiv preprint

2025

Domain Guidance: A Simple Transfer Approach for a Pre-trained Diffusion Model

arXiv preprint

2025

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

arXiv preprint

2024

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

arXiv preprint

2024

Metadata Matters for Time Series: Informative Forecasting with Transformers

arXiv preprint

2024

Unisolver: PDE-Conditional Transformers Towards Universal Neural PDE Solvers

arXiv preprint

2024

Timer-XL: Long-Context Transformers for Unified Time Series Forecasting

arXiv preprint

2024

TimeXer: Empowering Transformers for Time Series Forecasting with Exogenous Variables

arXiv preprint

2024

Transolver: A Fast Transformer Solver for PDEs on General Geometries

arXiv preprint

2024

RoPINN: Region Optimized Physics-Informed Neural Networks

arXiv preprint

2024

iVideoGPT: Interactive VideoGPTs are Scalable World Models

arXiv preprint

2024

CompilerDream: Learning a Compiler World Model for General Code Optimization

arXiv preprint

2024

AutoTimes: Autoregressive Time Series Forecasters via Large Language Models

arXiv preprint

2024

Diffusion Tuning: Transferring Diffusion Models via Chain of Forgetting

arXiv preprint

2024

depyf: Open the Opaque Box of PyTorch Compiler for Machine Learning Researchers

arXiv preprint

2024

Long-Sequence Recommendation Models Need Decoupled Embeddings

arXiv preprint

2024

DeepLag: Discovering Deep Lagrangian Dynamics for Intuitive Fluid Prediction

arXiv preprint

2024

CogDPM: Diffusion Probabilistic Models via Cognitive Predictive Coding

arXiv preprint

2024

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

arXiv preprint

2023

iTransformer: Inverted Transformers Are Effective for Time Series Forecasting

arXiv preprint

2023

Efficient ConvBN Blocks for Transfer Learning and Beyond

arXiv preprint

2023

On the Embedding Collapse when Scaling up Recommendation Models

arXiv preprint

2023

CLIPood: Generalizing CLIP to Out-of-Distributions

arXiv preprint

2023

HelmFluid: Learning Helmholtz Dynamics for Interpretable Fluid Prediction

arXiv preprint

2023

HarmonyDream: Task Harmonization Inside World Models

arXiv preprint

2023

ForkMerge: Mitigating Negative Transfer in Auxiliary-Task Learning

arXiv preprint

2023

Pre-training Contextualized World Models with In-the-wild Videos for Reinforcement Learning

arXiv preprint

2022

From Big to Small: Adaptive Learning to Partial-Set Domains

arXiv (Cornell University)

DOI

2022

Recommender Transformers with Behavior Pathways

arXiv preprint

2022

Flowformer: Linearizing Transformers with Conservation Flows

arXiv preprint

2022

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

arXiv preprint

2022

Transferability in Deep Learning: A Survey

arXiv preprint

2022

A Roadmap for Big Model

arXiv preprint

2022

MetaSets: Meta-Learning on Point Sets for Generalizable Representations

arXiv preprint

2022

TimesNet: Temporal 2D-Variation Modeling for General Time Series Analysis

arXiv preprint

2022

Out-of-Dynamics Imitation Learning from Multimodal Demonstrations

arXiv preprint

2022

Continual Predictive Learning from Videos

arXiv preprint

2022

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

arXiv preprint

2022

Supported Policy Optimization for Offline Reinforcement Learning

arXiv preprint

2022

Debiased Self-Training for Semi-Supervised Learning

arXiv preprint

2021

Anomaly Transformer: Time Series Anomaly Detection with Association Discrepancy

arXiv (Cornell University)

DOI

2021

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

arXiv (Cornell University)

DOI

2021

Zoo-Tuning: Adaptive Transfer from a Zoo of Models

arXiv (Cornell University)

DOI

2021

Open Domain Generalization with Domain-Augmented Meta-Learning

arXiv (Cornell University)

DOI

2021

ModeRNN: Harnessing Spatiotemporal Mode Collapse in Unsupervised Predictive Learning

arXiv preprint

2021

X-model: Improving Data Efficiency in Deep Learning with A Minimax Model

arXiv preprint

2021

Omni-Training: Bridging Pre-Training and Meta-Training for Few-Shot Learning

arXiv preprint

2021

Ranking and Tuning Pre-trained Models: A New Paradigm for Exploiting Model Hubs

arXiv preprint

2021

Decoupled Adaptation for Cross-Domain Object Detection

arXiv preprint

2019

VideoDG: Generalizing Temporal Relations in Videos to Novel Domains

arXiv preprint