Dongjin Song
Assistant Professor/Computing
Storrs Mansfield
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Scholarly Contributions
49 Scholarly Contributions
Dynamic Gaussian Mixture based Deep Generative Model For Robust Forecasting on Sparse Multivariate Time Series
2024
Research Type: Conference Proceedings
Interpretable Skill Learning for Dynamic Treatment Regimes through Imitation
2024
Research Type: Conference Proceedings
Deep Multi-Instance Contrative Learning with Dual Attention for Anomaly Precursor Detection
2024
Research Type: Conference Proceedings
CGBL: Benchmark Tasks for Continual Graph Representation Learning
2024
Research Type: Conference Proceedings
Interpreting Convolutional Sequence Model by Learning Local and Resolution Controllable Prototypes
2024
Research Type: Conference Proceedings
Deep Federated Anomaly Detection for Multivariate Time Series Data
2024
Research Type: Conference Proceedings
Sparsified Subgraph Memory for Continual Graph
Representation Learning
2024
Research Type: Conference Proceedings
HiT-MDP: Learning the SMDP option framework on MDPs with Hidden Temporal Variables
2024
Research Type: Conference Proceedings
FACESEC: A Fine-grained Robustness Evaluation Framework for Face Recognition Systems
2024
Research Type: Conference Proceedings
Privacy-Preserving and Uncertainty-Aware Federated Trajectory Prediction for Connected Autonomous Vehicles
2024
Research Type: Conference Proceedings
Distributed Distributionally Robust Optimization with Non-Convex Objectives
2024
Research Type: Conference Proceedings
Using Mobile Daily Mood and Anxiety Self-ratings to Predict Depression Symptom Improvement
2024
Research Type: Conference Proceedings
Channel-Temporal Gated Networks for Long Sequence Time-series Forecasting
Research Type: Conference Proceedings
Topology-aware Embedding Memory for Continual Learning on Expanding Networks
Research Type: Conference Proceedings
A Novel Hybrid SIAM International Conference on Data Mining (SDM),Graph Learning Method for Inbound Parcel Volume Forecasting in Logistics System
Research Type: Conference Proceedings
Structrual Knowledge Informed Continual Learning for Multivariate Time Series Forecasting
Research Type: Conference Proceedings
S2IP-LLM: Semantic Space Informed Prompt Learning with LLM for Time Series Forecasting
Research Type: Conference Proceedings