4 papers
ItDPDM: Information-Theoretic Discrete Poisson Diffusion Model
Sagnik Bhattacharya, Abhiram Gorle, Ahsan Bilal +3
Generative modeling of non-negative, discrete data, such as symbolic music, remains challenging due to two persistent limitations in existing methods. Firstly, many approaches rely…
GaussianVision: Vision-Language Alignment from Compressed Image Representations using 2D Gaussian Splatting
Yasmine Omri, Connor Ding, Tsachy Weissman +1
Modern vision language pipelines are driven by RGB vision encoders trained on massive image text corpora. While these pipelines have enabled impressive zero-shot capabilities and s…
Information-computation trade-offs in non-linear transforms
Connor Ding, Abhiram Rao Gorle, Jiwon Jeong +2
In this work, we explore the interplay between information and computation in non-linear transform-based compression for broad classes of modern information-processing tasks. We fi…
LZMidi: Compression-Based Symbolic Music Generation
Connor Ding, Abhiram Gorle, Sagnik Bhattacharya +3
Recent advances in symbolic music generation primarily rely on deep learning models such as Transformers, GANs, and diffusion models. While these approaches achieve high-quality re…