Saved in:
| Main Author: | Zhang, Xuanming |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2507.02912 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Quantitative Energy Prediction based on Carbon Emission Analysis by DPR Framework
by: Zhang, Xuanming
Published: (2023)
by: Zhang, Xuanming
Published: (2023)
Co-Activation Graph Analysis of Safety-Verified and Explainable Deep Reinforcement Learning Policies
by: Gross, Dennis, et al.
Published: (2025)
by: Gross, Dennis, et al.
Published: (2025)
The Impact of On-Policy Parallelized Data Collection on Deep Reinforcement Learning Networks
by: Mayor, Walter, et al.
Published: (2025)
by: Mayor, Walter, et al.
Published: (2025)
Automated Knowledge Graph Learning in Industrial Processes
by: Ammann, Lolitta, et al.
Published: (2024)
by: Ammann, Lolitta, et al.
Published: (2024)
Unsupervised Generative Feature Transformation via Graph Contrastive Pre-training and Multi-objective Fine-tuning
by: Ying, Wangyang, et al.
Published: (2024)
by: Ying, Wangyang, et al.
Published: (2024)
GraphLand: Evaluating Graph Machine Learning Models on Diverse Industrial Data
by: Bazhenov, Gleb, et al.
Published: (2024)
by: Bazhenov, Gleb, et al.
Published: (2024)
DeepStock: Reinforcement Learning with Policy Regularizations for Inventory Management
by: Xie, Yaqi, et al.
Published: (2026)
by: Xie, Yaqi, et al.
Published: (2026)
Knowledge Graph Modulated Deep Learning for Limited-Sample Clinical Data Analysis
by: Xue, Yuwei, et al.
Published: (2026)
by: Xue, Yuwei, et al.
Published: (2026)
Event Classification of Accelerometer Data for Industrial Package Monitoring with Embedded Deep Learning
by: Renault, Manon, et al.
Published: (2025)
by: Renault, Manon, et al.
Published: (2025)
Deep Causal Behavioral Policy Learning: Applications to Healthcare
by: Knecht, Jonas, et al.
Published: (2025)
by: Knecht, Jonas, et al.
Published: (2025)
A Study of Plasticity Loss in On-Policy Deep Reinforcement Learning
by: Juliani, Arthur, et al.
Published: (2024)
by: Juliani, Arthur, et al.
Published: (2024)
Graph Deep Learning for Time Series Forecasting
by: Cini, Andrea, et al.
Published: (2023)
by: Cini, Andrea, et al.
Published: (2023)
Revolutionizing Biomarker Discovery: Leveraging Generative AI for Bio-Knowledge-Embedded Continuous Space Exploration
by: Ying, Wangyang, et al.
Published: (2024)
by: Ying, Wangyang, et al.
Published: (2024)
The Tsetlin Machine Goes Deep: Logical Learning and Reasoning With Graphs
by: Granmo, Ole-Christoffer, et al.
Published: (2025)
by: Granmo, Ole-Christoffer, et al.
Published: (2025)
Learning Dynamics of Deep Learning -- Force Analysis of Deep Neural Networks
by: Ren, Yi
Published: (2025)
by: Ren, Yi
Published: (2025)
Enabling Off-Policy Imitation Learning with Deep Actor Critic Stabilization
by: Sen, Sayambhu, et al.
Published: (2025)
by: Sen, Sayambhu, et al.
Published: (2025)
SafeAdapt: Provably Safe Policy Updates in Deep Reinforcement Learning
by: Anisimov, Maksim, et al.
Published: (2026)
by: Anisimov, Maksim, et al.
Published: (2026)
Efficient Deep Reinforcement Learning with Predictive Processing Proximal Policy Optimization
by: Küçükoğlu, Burcu, et al.
Published: (2022)
by: Küçükoğlu, Burcu, et al.
Published: (2022)
Optimal Policy Sparsification and Low Rank Decomposition for Deep Reinforcement Learning
by: Goddla, Vikram
Published: (2024)
by: Goddla, Vikram
Published: (2024)
Deep Reinforcement Learning for Inventory Networks: Toward Reliable Policy Optimization
by: Alvo, Matias, et al.
Published: (2023)
by: Alvo, Matias, et al.
Published: (2023)
The Impact of Quantization and Pruning on Deep Reinforcement Learning Models
by: Lu, Heng, et al.
Published: (2024)
by: Lu, Heng, et al.
Published: (2024)
Deep k-grouping: An Unsupervised Learning Framework for Combinatorial Optimization on Graphs and Hypergraphs
by: Bai, Sen, et al.
Published: (2025)
by: Bai, Sen, et al.
Published: (2025)
Deep Contrastive Graph Learning with Clustering-Oriented Guidance
by: Chen, Mulin, et al.
Published: (2024)
by: Chen, Mulin, et al.
Published: (2024)
Predicting the Lifespan of Industrial Printheads with Survival Analysis
by: Parii, Dan, et al.
Published: (2025)
by: Parii, Dan, et al.
Published: (2025)
GraphGen+: Advancing Distributed Subgraph Generation and Graph Learning On Industrial Graphs
by: Jin, Yue, et al.
Published: (2025)
by: Jin, Yue, et al.
Published: (2025)
Learning to Explore: Policy-Guided Outlier Synthesis for Graph Out-of-Distribution Detection
by: Sun, Li, et al.
Published: (2026)
by: Sun, Li, et al.
Published: (2026)
SAFE-RL: Saliency-Aware Counterfactual Explainer for Deep Reinforcement Learning Policies
by: Samadi, Amir, et al.
Published: (2024)
by: Samadi, Amir, et al.
Published: (2024)
Relative Importance Sampling for off-Policy Actor-Critic in Deep Reinforcement Learning
by: Humayoo, Mahammad, et al.
Published: (2018)
by: Humayoo, Mahammad, et al.
Published: (2018)
Scheduled Curiosity-Deep Dyna-Q: Efficient Exploration for Dialog Policy Learning
by: Niu, Xuecheng, et al.
Published: (2024)
by: Niu, Xuecheng, et al.
Published: (2024)
Improving Deep Reinforcement Learning by Reducing the Chain Effect of Value and Policy Churn
by: Tang, Hongyao, et al.
Published: (2024)
by: Tang, Hongyao, et al.
Published: (2024)
Solving Deep Reinforcement Learning Tasks with Evolution Strategies and Linear Policy Networks
by: Wong, Annie, et al.
Published: (2024)
by: Wong, Annie, et al.
Published: (2024)
The Definitive Guide to Policy Gradients in Deep Reinforcement Learning: Theory, Algorithms and Implementations
by: Lehmann, Matthias
Published: (2024)
by: Lehmann, Matthias
Published: (2024)
RiemannGL: Riemannian Geometry Changes Graph Deep Learning
by: Sun, Li, et al.
Published: (2026)
by: Sun, Li, et al.
Published: (2026)
Crime Forecasting: A Spatio-temporal Analysis with Deep Learning Models
by: Mao, Li, et al.
Published: (2025)
by: Mao, Li, et al.
Published: (2025)
Deep Generative Models for Offline Policy Learning: Tutorial, Survey, and Perspectives on Future Directions
by: Chen, Jiayu, et al.
Published: (2024)
by: Chen, Jiayu, et al.
Published: (2024)
Rank-1 Approximation of Inverse Fisher for Natural Policy Gradients in Deep Reinforcement Learning
by: Huo, Yingxiao, et al.
Published: (2026)
by: Huo, Yingxiao, et al.
Published: (2026)
Integrating Temporal and Structural Context in Graph Transformers for Relational Deep Learning
by: Lachi, Divyansha, et al.
Published: (2025)
by: Lachi, Divyansha, et al.
Published: (2025)
Deep Graph Neural Point Process For Learning Temporal Interactive Networks
by: Chen, Su, et al.
Published: (2025)
by: Chen, Su, et al.
Published: (2025)
Scalable Property Valuation Models via Graph-based Deep Learning
by: Riveros, Enrique, et al.
Published: (2024)
by: Riveros, Enrique, et al.
Published: (2024)
Causal Concept Graph Models: Beyond Causal Opacity in Deep Learning
by: Dominici, Gabriele, et al.
Published: (2024)
by: Dominici, Gabriele, et al.
Published: (2024)
Similar Items
-
Quantitative Energy Prediction based on Carbon Emission Analysis by DPR Framework
by: Zhang, Xuanming
Published: (2023) -
Co-Activation Graph Analysis of Safety-Verified and Explainable Deep Reinforcement Learning Policies
by: Gross, Dennis, et al.
Published: (2025) -
The Impact of On-Policy Parallelized Data Collection on Deep Reinforcement Learning Networks
by: Mayor, Walter, et al.
Published: (2025) -
Automated Knowledge Graph Learning in Industrial Processes
by: Ammann, Lolitta, et al.
Published: (2024) -
Unsupervised Generative Feature Transformation via Graph Contrastive Pre-training and Multi-objective Fine-tuning
by: Ying, Wangyang, et al.
Published: (2024)