aengusng8/i2i-anything

I2SB: Image-to-Image Schrödinger Bridge, Dual Diffusion Implicit Bridges for Image-to-Image Translation (ICLR 2023)

My research interest lies in developing robust generative models and applying them to diverse applications, including conditional sampling, disentangled representation learning, and reasoning. Currently, my goal is to build a generative model capable of producing high-fidelity, diverse, and high-dimensional samples in a single forward pass.

My recent works focus on image generation and manipulation using ODE/SDE-based generative models, specifically diffusion probabilistic models.

• My huggingface/diffusers pull requests [1*] [2*] [3]
• My math derivation of DDPM [PDF]
• My literature review on diffusion probabilistic models [Google Sheets]

There's too many problems. So how can you work on all problems simultaneously? You solve the meta-problem, which is to me just intelligence and how do you automate it? - Andrej Karpathy

Personal logs:

• This is my fourth time resolving a bug in the long run 🏃‍♂️🏃, as well as medium-difficulty problems such as "How to work effectively with a large codebase?" and "Preparing an agenda and good questions for my presentation." I am still figuring out how to reproduce the phenomenon. My main strategies include: (1) Loading my mental RAM (my working memory) fully with the problem, be obsessed with it when I'm taking a shower, and falling asleep, until it's fully ingrained in my memory. I might be ready to wake up and work on it right there. This process can take a whole day or more. (2) Asking logical, systematic, and non-random questions, frequently.
• I don't enjoy encountering old bugs. New bugs provide me with a natural source of dopamine. assert and raise are our friends.
• Lots of minor engineering problems must be rapidly solved in an algorithmic way, thus contributing to good research.
• Backpropagation and transformer are general ❤️. I like general things. (inductive prior will set a starting point until your model gets informed by your data, while the inductive bias inevitability limits the space of possible model-solutions)
• Why? or Why is it important? So what?