- ✨ Interested in Optimization Theory & Deep Learning
- 🧰 Coding in MATLAB & Python
- 🧊 Currently studying cutting-edge one-step generative modeling, focusing on diffusion and flow-based methods that transform noise distributions into data distributions with a single neural network evaluation
-
Central South University.
- Changsha, China
Highlights
- Pro
Pinned Loading
-
2025_CUMCM_Problem_A
2025_CUMCM_Problem_A PublicMathematical modeling solution for CUMCM 2025 Problem A using PSO/PSO-DE optimization in MATLAB.
MATLAB 2
-
2026_MCM_Problem_C
2026_MCM_Problem_C PublicMCM 2026 Problem C solution for Dancing with the Stars voting: hidden fan-vote estimation, rule comparison, SHAP analysis, and LBG-Runoff design.
Python 2
-
Flow_Driven_Posterior_Sampling_for_Inverse_Problems
Flow_Driven_Posterior_Sampling_for_Inverse_Problems PublicFlowDPS reproduction and benchmark package for flow-based posterior sampling in inverse imaging.
-
Flower_A_Flow_Matching_Solver
Flower_A_Flow_Matching_Solver PublicFlower paper reproduction with metric tables, visual comparisons, and flow-matching solver analysis.
-
diffusion_toy_experiments
diffusion_toy_experiments PublicUse 2D distributions to validate generative modeling methods
Python 3
-
If the problem persists, check the GitHub status page or contact support.