gaussian mixture model
A Gaussian mixture model (GMM) is a probabilistic model that represents a mixture of multiple Gaussian distributions. In AI, it is commonly used for clustering and density estimation, allowing flexibility in modeling complex data distributions.
- $\epsilon$-Seg: Sparsely Supervised Semantic Segmentation of Microscopy Data
- A Reinforcement Learning-based Bidding Strategy for Data Consumers in Auction-based Federated Learning
- Attention-based clustering
- Autoregressive Motion Generation with Gaussian Mixture-Guided Latent Sampling
- GMM-based VAE model with Normalising Flow for effective stochastic segmentation
- Go With the Flow: Fast Diffusion for Gaussian Mixture Models
- Self-Boost via Optimal Retraining: An Analysis via Approximate Message Passing