Defu Cao

Orcid: 0000-0003-0240-3818

According to our database1, Defu Cao authored at least 29 papers between 2020 and 2024.

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

Timeline

2020
2021
2022
2023
2024
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6
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Bibliography

2024
Creating a Cooperative AI Policymaking Platform through Open Source Collaboration.
CoRR, 2024

Active Sequential Posterior Estimation for Sample-Efficient Simulation-Based Inference.
CoRR, 2024

Beyond Forecasting: Compositional Time Series Reasoning for End-to-End Task Execution.
CoRR, 2024

TimeDiT: General-purpose Diffusion Transformers for Time Series Foundation Model.
CoRR, 2024

Exploring Neuron Interactions and Emergence in LLMs: From the Multifractal Analysis Perspective.
CoRR, 2024

Prompting Large Language Models with Divide-and-Conquer Program for Discerning Problem Solving.
CoRR, 2024

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

Collaborative Multi-Task Representation for Natural Language Understanding.
Proceedings of the International Joint Conference on Neural Networks, 2024

An Empirical Examination of Balancing Strategy for Counterfactual Estimation on Time Series.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

Neuro-Inspired Information-Theoretic Hierarchical Perception for Multimodal Learning.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

TEMPO: Prompt-based Generative Pre-trained Transformer for Time Series Forecasting.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

GPT4MTS: Prompt-based Large Language Model for Multimodal Time-series Forecasting.
Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023
Detecting Out-of-Context Multimodal Misinformation with interpretable neural-symbolic model.
CoRR, 2023

Coupled Multiwavelet Neural Operator Learning for Coupled Partial Differential Equations.
CoRR, 2023

Estimating Treatment Effects in Continuous Time with Hidden Confounders.
CoRR, 2023

Time-delayed Multivariate Time Series Predictions.
Proceedings of the 2023 SIAM International Conference on Data Mining, 2023

Coupled Multiwavelet Operator Learning for Coupled Differential Equations.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

Large Scale Financial Time Series Forecasting with Multi-faceted Model.
Proceedings of the 4th ACM International Conference on AI in Finance, 2023

SVGformer: Representation Learning for Continuous Vector Graphics using Transformers.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

Estimating Treatment Effects from Irregular Time Series Observations with Hidden Confounders.
Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022
DSLOB: A Synthetic Limit Order Book Dataset for Benchmarking Forecasting Algorithms under Distributional Shift.
CoRR, 2022

When Physics Meets Machine Learning: A Survey of Physics-Informed Machine Learning.
CoRR, 2022

Mu2ReST: Multi-resolution Recursive Spatio-Temporal Transformer for Long-Term Prediction.
Proceedings of the Advances in Knowledge Discovery and Data Mining, 2022

Counterfactual Neural Temporal Point Process for Estimating Causal Influence of Misinformation on Social Media.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Enhancing Self-Attention with Knowledge-Assisted Attention Maps.
Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2022

2021
Spectral Temporal Graph Neural Network for Trajectory Prediction.
Proceedings of the IEEE International Conference on Robotics and Automation, 2021

2020
FTCLNet: Convolutional LSTM with Fourier Transform for Vulnerability Detection.
Proceedings of the 19th IEEE International Conference on Trust, 2020

Spectral Temporal Graph Neural Network for Multivariate Time-series Forecasting.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Multivariate Time-series Anomaly Detection via Graph Attention Network.
Proceedings of the 20th IEEE International Conference on Data Mining, 2020


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