Guangyi Chen

Orcid: 0000-0001-7542-5378

Affiliations:
  • Mohamed bin Zayed University of Artificial Intelligence, Masdar City, Abu Dhabi, AE
  • Carnegie Mellon University, Pittsburgh, PA, USA
  • Tsinghua University, Department of Automation, Beijing, China (PhD 2021)
  • Tsinghua University, State Key Lab of Intelligent Technologies and Systems, Beijing, China (former)
  • Tsinghua National Laboratory for Information Science and Technology, TNList, Beijing, China (former)
  • Beijing National Research Center for Information Science and Technology, China (former)


According to our database1, Guangyi Chen authored at least 57 papers between 2017 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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Bibliography

2024
Causal Temporal Representation Learning with Nonstationary Sparse Transition.
CoRR, 2024

CT4D: Consistent Text-to-4D Generation with Animatable Meshes.
CoRR, 2024

Continual Learning of Nonlinear Independent Representations.
CoRR, 2024

Efficient Inference of Vision Instruction-Following Models with Elastic Cache.
CoRR, 2024

Learning Discrete Concepts in Latent Hierarchical Models.
CoRR, 2024

From Orthogonality to Dependency: Learning Disentangled Representation for Multi-Modal Time-Series Sensing Signals.
CoRR, 2024

On the Identification of Temporally Causal Representation with Instantaneous Dependence.
CoRR, 2024

Federated Causal Discovery from Heterogeneous Data.
CoRR, 2024

When and How: Learning Identifiable Latent States for Nonstationary Time Series Forecasting.
CoRR, 2024

Learning Domain-Invariant Temporal Dynamics for Few-Shot Action Recognition.
CoRR, 2024

Confidence Matters: Revisiting Intrinsic Self-Correction Capabilities of Large Language Models.
CoRR, 2024

MuGSI: Distilling GNNs with Multi-Granularity Structural Information for Graph Classification.
Proceedings of the ACM on Web Conference 2024, 2024

Learning Causal Domain-Invariant Temporal Dynamics for Few-Shot Action Recognition.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

CaRiNG: Learning Temporal Causal Representation under Non-Invertible Generation Process.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

Federated Causal Discovery from Heterogeneous Data.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

Structural Estimation of Partially Observed Linear Non-Gaussian Acyclic Model: A Practical Approach with Identifiability.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

LLCP: Learning Latent Causal Processes for Reasoning-based Video Question Answer.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

Language-Free Compositional Action Generation via Decoupling Refinement.
Proceedings of the IEEE International Conference on Acoustics, 2024

Encourage or Inhibit Monosemanticity? Revisit Monosemanticity from a Feature Decorrelation Perspective.
Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing, 2024

Narrative Action Evaluation with Prompt-Guided Multimodal Interaction.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024

S3A: Towards Realistic Zero-Shot Classification via Self Structural Semantic Alignment.
Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023
Learning Socio-Temporal Graphs for Multi-Agent Trajectory Prediction.
CoRR, 2023

Identifying Semantic Component for Robust Molecular Property Prediction.
CoRR, 2023

Towards Realistic Zero-Shot Classification via Self Structural Semantic Alignment.
CoRR, 2023

Language-free Compositional Action Generation via Decoupling Refinement.
CoRR, 2023

Partial Identifiability for Domain Adaptation.
CoRR, 2023

Temporally Disentangled Representation Learning under Unknown Nonstationarity.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Subspace Identification for Multi-Source Domain Adaptation.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Feature Expansion for Graph Neural Networks.
Proceedings of the International Conference on Machine Learning, 2023

GAIN: On the Generalization of Instructional Action Understanding.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

PLOT: Prompt Learning with Optimal Transport for Vision-Language Models.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

Tem-adapter: Adapting Image-Text Pretraining for Video Question Answer.
Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

PromptCAL: Contrastive Affinity Learning via Auxiliary Prompts for Generalized Novel Category Discovery.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

Understanding Masked Autoencoders via Hierarchical Latent Variable Models.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

Unsupervised Sampling Promoting for Stochastic Human Trajectory Prediction.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

Adversarial Alignment for Source Free Object Detection.
Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022
Probabilistic Temporal Modeling for Unintentional Action Localization.
IEEE Trans. Image Process., 2022

Unintentional Action Localization via Counterfactual Examples.
IEEE Trans. Image Process., 2022

Prompt Learning with Optimal Transport for Vision-Language Models.
CoRR, 2022

Learning Latent Causal Dynamics.
CoRR, 2022

Temporally Disentangled Representation Learning.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Partial disentanglement for domain adaptation.
Proceedings of the International Conference on Machine Learning, 2022

FineDiving: A Fine-grained Dataset for Procedure-aware Action Quality Assessment.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

DenseCLIP: Language-Guided Dense Prediction with Context-Aware Prompting.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

Stochastic Trajectory Prediction via Motion Indeterminacy Diffusion.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

2021
Person Re-Identification via Attention Pyramid.
IEEE Trans. Image Process., 2021

Temporal Label Aggregation for Unintentional Action Localization.
Proceedings of the 2021 IEEE International Conference on Multimedia and Expo, 2021

Counterfactual Attention Learning for Fine-Grained Visual Categorization and Re-identification.
Proceedings of the 2021 IEEE/CVF International Conference on Computer Vision, 2021

Personalized Trajectory Prediction via Distribution Discrimination.
Proceedings of the 2021 IEEE/CVF International Conference on Computer Vision, 2021

Human Trajectory Prediction via Counterfactual Analysis.
Proceedings of the 2021 IEEE/CVF International Conference on Computer Vision, 2021

2020
Learning Recurrent 3D Attention for Video-Based Person Re-Identification.
IEEE Trans. Image Process., 2020

Temporal Coherence or Temporal Motion: Which Is More Critical for Video-Based Person Re-identification?
Proceedings of the Computer Vision - ECCV 2020, 2020

Deep Credible Metric Learning for Unsupervised Domain Adaptation Person Re-identification.
Proceedings of the Computer Vision - ECCV 2020, 2020

2019
Spatial-Temporal Attention-Aware Learning for Video-Based Person Re-Identification.
IEEE Trans. Image Process., 2019

Deep Meta Metric Learning.
Proceedings of the 2019 IEEE/CVF International Conference on Computer Vision, 2019

Self-Critical Attention Learning for Person Re-Identification.
Proceedings of the 2019 IEEE/CVF International Conference on Computer Vision, 2019

2017
Localized multi-kernel discriminative canonical correlation analysis for video-based person re-identification.
Proceedings of the 2017 IEEE International Conference on Image Processing, 2017


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