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Found 6 papers, 2 papers with code
Bt-GAN: Generating Fair Synthetic Healthdata via Bias-transforming Generative Adversarial Networks
In conclusion, our research introduces a novel and professional approach to addressing the limitations of synthetic data generation in the healthcare domain.
Autonomous 3D Exploration in Large-Scale Environments with Dynamic Obstacles
DAEP outperform state-of-the-art planners in dynamic and large-scale environments.
TransFusion: Generating Long, High Fidelity Time Series using Diffusion Models with Transformers
The generation of high-quality, long-sequenced time-series data is essential due to its wide range of applications.
Towards Utilitarian Combinatorial Assignment with Deep Neural Networks and Heuristic Algorithms
This paper presents preliminary work on using deep neural networks to guide general-purpose heuristic algorithms for performing utilitarian combinatorial assignment.
A Practical Guide to Multi-Objective Reinforcement Learning and Planning
Real-world decision-making tasks are generally complex, requiring trade-offs between multiple, often conflicting, objectives.
Enhancing Lattice-based Motion Planning with Introspective Learning and Reasoning
Reasoning takes place to both verify that the learned models stays safe and to improve collision checking effectiveness in the motion planner by the use of more accurate execution predictions with a smaller safety margin.
