We propose the development of a high-efficiency foundation model tailored for the MedMNIST v2 benchmark, utilizing a novel architecture based on Multi-Resolution [...]

Although generative adversarial networks (GANs) and diffusion models achieve impressive realism through neural networks and backpropagation, the learned representations [...]

Our work starts with a simple idea: the way different brain regions communicate can reveal a lot about what [...]

We propose Variable-Length Word Embeddings, a POS-aware and compute-efficient Word2Vec training framework. Traditional embeddings assign the same dimensionality to [...]