Abstract: This paper presents an in-depth exploration of the Stable Diffusion pipeline for text-to-image synthesis, emphasizing a comparative analysis between the Latent Diffusion Model (LDM) and the ...

PyTorch reimplementation of "Deep Hierarchical Planning" RL framework. Features a multi-model architecture with manager-worker policies, world model, and goal autoencoder. Built with Python/PyTorch ...

The new 7nm-class chip, reportedly in testing, signals a shift to domestic fabrication and aims to rival Nvidia’s China-compliant GPUs while maintaining CUDA compatibility. Alibaba is reportedly ...

Deep residual autoencoder for reconstructing and analyzing spectral data using PyTorch. Includes composite loss, UMAP visualization, and spectral diagnostics. Built for unsupervised learning on ...

Meta has introduced KernelLLM, an 8-billion-parameter language model fine-tuned from Llama 3.1 Instruct, aimed at automating the translation of PyTorch modules into efficient Triton GPU kernels. This ...

Abstract: A complex-valued autoencoder neural network ca-pable of compressing & denoising radio frequency signals with arbitrary model scaling is proposed. Complex-valued time sam-ples received with ...