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Hi there! I'm David (He/Him) Github Stars Github Followers

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I'm passionate about making quality tools that empower AI practitioners and generative artists.

I'm currently working as an ML engineer at CoreWeave, and am also affiliated with eleuther.ai. Previously, I helped launch Stability AI in the role of Distinguished Engineer, and worked in more conventional Data Scientist roles at Microsoft, Amazon, Fannie Mae, USDOL-OIG, Elder Research, and SoundExchange. A common theme in my work for the last few years has been building tools which making bleeding edge AI research accessible to non-technical creatives.

Creator/maintainer/curator of https://github.com/pytti-tools -> Open In Colab

Some projects I'm currently or recently involved with:

  • Developing tools to facilitate parameterizing complex, multi-scene animation sequences
  • Invented a technique for generating a multi-scene music video from audio Open In Colab
  • inventing and building cutting edge, state of the art, AI animation tools and techniques
  • working with electronic musicians and VJs to advance audio-reactive animation research
  • maintaining and extending pytti-tools
  • building a library to facilitate working with pre-trained CLIP-like models
  • building a library to facilitate working with and management of messy research code
  • working with researchers to build data collection tools that will be used to turn hackathon activities into training data for code generative language modeling
  • Implementing notebooks to facilitate AI artist use of pre-trained research models, including FiLM and blended defusion
  • model design for a forthcoming AI art model
  • Shepherding the launch of the Stable Diffusion API and accompanying infra and tooling (public SDK, CI/CD, etc.) as engineering lead through the launch of the DreamStudio product

Microsoft WWL Amazon TRMS Elder Research


github stats for dmarx

Broad Research Interests

  • Text guided image synthesis
  • AI-assisted animation
  • Representation learning
    • contrastive
    • semi-supervised
    • adversarial
    • composable
    • multi-modal
  • Application of topolgical and geometric methods to machine learning
  • Generative models
  • Inductive priors
  • Learning theory

Current Areas of Research Focus

  • Modeling with implicit representations and operators
  • Composable representations
  • Latent-space manipulation
  • Scale-agnostic learning
  • Artistic applications of multi-modal generative models

Old Blog


# Greatest hits

https://github.com/dmarx/bench-warmers/
https://github.com/dmarx/sd-lazy-wildcards
https://github.com/dmarx/notebooks
https://github.com/dmarx/workbench
https://github.com/dmarx/anthology-of-modern-ml
https://github.com/dmarx/video-killed-the-radio-star
https://github.com/dmarx/keyframed
https://github.com/dmarx/fast-and-simple-dense-retrieval
https://github.com/dmarx/fasdr-action
https://github.com/dmarx/zero-shot-intent-classifier
https://github.com/dmarx/keyframed_chatgpt
https://github.com/dmarx/not-a-package-manager
https://github.com/dmarx/Multi-Modal-Comparators
https://github.com/dmarx/anthology-of-ml-for-ai-art
https://github.com/dmarx/pytti-core
https://github.com/dmarx/cka_pytorch
https://github.com/dmarx/checkin
https://github.com/dmarx/Topological-Anomaly-Detection
https://github.com/dmarx/Reddit_response_to_Trump

https://github.com/dmarx/make_for_datascience
https://github.com/dmarx/dispatchr
https://github.com/dmarx/twitterMonitor
https://github.com/dmarx/TextSummarization
https://github.com/dmarx/reddit-map
https://github.com/dmarx/dmarx.github.io
https://github.com/dmarx/Target-Shuffling
https://github.com/dmarx/statisticalArgumentForSettling
https://github.com/dmarx/SubredditMentionsGraph
https://github.com/dmarx/BoostTheVote

https://github.com/dmarx/Topological-Anomaly-Detection-r
https://github.com/dmarx/TravelingSalesmanMCMC
https://github.com/dmarx/GameOfLife
https://github.com/dmarx/Dreidel
https://github.com/dmarx/Random-Contingency-Table-Generator
https://github.com/dmarx/d3-mines
https://github.com/dmarx/mines

https://github.com/dmarx/VideoLinkBot

https://github.com/dmarx/awesome-llm-utilities
https://github.com/dmarx/auto-tagger
https://github.com/dmarx/the-rest-of-the-fucking-owl
https://github.com/dmarx/owl-keyframed
https://github.com/dmarx/psaw
https://github.com/dmarx/debugger
https://github.com/dmarx/nfpa
https://github.com/dmarx/enl-supply
https://github.com/dmarx/supply-chain
https://github.com/dmarx/data_generation_demo
https://github.com/dmarx/tpot
https://github.com/dmarx/DataKind-SmokeAlarms
https://github.com/dmarx/congressional-rollcalls

David Marx's Projects

1click-hpc icon 1click-hpc

Deploy your HPC Cluster on AWS in 20min. with just 1-Click.

1d-statespace icon 1d-statespace

This repository contains the implementation of an efficient joint beat, downbeat, tempo, and meter tracking system using a compact 1D probabilistic state space and a jump-back reward technique. ICASSP 2022.

auto-sd-paint-ext icon auto-sd-paint-ext

Extension for AUTOMATIC1111 to add custom backend API for Krita Plugin & more

auto-tagger icon auto-tagger

use an LLM (chatgpt) to automatically categorize documents

autopr icon autopr

Fix issues with AI-generated pull requests, powered by ChatGPT

azure-sdk-for-python icon azure-sdk-for-python

This repository is for active development of the Azure SDK for Python. For consumers of the SDK we recommend visiting our public developer docs at https://docs.microsoft.com/en-us/python/azure/ or our versioned developer docs at https://azure.github.io/azure-sdk-for-python.

big-sleep icon big-sleep

A simple command line tool for text to image generation, using OpenAI's CLIP and a BigGAN. Technique was originally created by https://twitter.com/advadnoun

boostthevote icon boostthevote

A thought experiment demonstrating how machine learning could be applied to the electoral process to improve electoral outcomes.

chronicle-etl icon chronicle-etl

📜 A CLI toolkit for extracting and working with your digital history

cka_pytorch icon cka_pytorch

Reproducing Raghu et al 2021 - Do Vision Transformers See Like Convolutional Neural Networks?

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