neural network
A computational model inspired by the way biological neural networks in the human brain operate. It consists of interconnected layers of neurons that process input data through learned weights to perform tasks like classification and regression.
- A machine learning approach that beats Rubik's cubes
- Covariate-moderated Empirical Bayes Matrix Factorization
- FSNet: Feasibility-Seeking Neural Network for Constrained Optimization with Guarantees
- How Does Label Noise Gradient Descent Improve Generalization in the Low SNR Regime?
- Learning to Condition: A Neural Heuristic for Scalable MPE Inference
- Locality in Image Diffusion Models Emerges from Data Statistics
- NPN: Non-Linear Projections of the Null-Space for Imaging Inverse Problems
- Neural Entropy
- Neural Evolution Strategy for Black-box Pareto Set Learning
- SymMaP: Improving Computational Efficiency in Linear Solvers through Symbolic Preconditioning
- Towards Generalizable Multi-Policy Optimization with Self-Evolution for Job Scheduling
- Unextractable Protocol Models: Collaborative Training and Inference without Weight Materialization