no code implementations • 28 May 2024 • Wei Zhu, Aaron Xuxiang Tian, Congrui Yin, Yuan Ni, Xiaoling Wang, Guotong Xie
Thus, we propose to learn the idiosyncratic activation functions for prompt generators automatically with the help of rational functions.
1 code implementation • 2 Apr 2024 • Chen Yang, Aaron Xuxiang Tian, Dong Chen, Tianyu Shi, Arsalan Heydarian
To enhance the scene diversity and stochasticity, the historical trajectory data is first preprocessed and encoded into latent space using Denoising Diffusion Probabilistic Models (DDPM) enhanced with Diffusion with Transformer (DiT) blocks.