In a past life, I used to do a lot of software engineering, contribute to some popular open-source projects and build robot hardware (i was a part of my country’s World Robot Olympiad team). I have listed a few open-source projects I started. I have presented a few talks at software conferences which are also listed here.
selected software
torch diffsim
Parallelizable, differentiable, deformable simulation entirely in PyTorch
Fast Transformer
Use additive attention to make Transformers go brrr... (GitHub Trending)
Gradient Centralization
Attach onto your Adam-style optimizers to instantly improve your training performance. (GitHub Trending)
Simplicits Nerfstudio
Qualitative/ speed improvements to Simplicits to run reduced-order simulation on mesh, Gaussian Splat or a NeRF.
3D Transforms
A library to easily work with 3D data and make 3D transformations.
MIRNet TFJS
Run low-light💡 image enhancement, also runs entirely in your browser. (GitHub Trending)
Perceiver
Use Perceiver and Latent-Query-style models. (GitHub Trending)
Greenathon
Train models specifically to deploy them entirely on browsers. A hackathon submission. (GitHub Trending)
ISAB
Train and use permutation invariant neural networks.
Neural Nets on Android
Run model inference in Android apps. (GitHub Trending)
Neural Nets on Flutter
Run model inference in Android apps within Flutter's runtime.
TF Watcher
A tool to monitor your ML jobs remotely. (GitHub Trending)
Nystromformer
Use approximation of the self-attention operation to go brrr...
Transformer in Transformer
Perform attention inside local patches for image classification.
Conformer
Combine convolution and self-attention blocks for speech recognition.
GLOM
Hinton's GLOM part-whole hierarchies using grouped 1x1 convolutions to run level-wise MLPs in parallel.
GLU
Gated Linear Units and many of their variants: Bilinear, ReGLU, GeGLU, SwiGLU, and SeGLU.
Compositional Attention
Compositional Attention and its variants around disentangling search and retrieval.
Invariant Point Attention
Use Invariant Point Attention from AlphaFold 2 for other problems.
Wasm FAAS
Run neural nets as serverless functions inside Wasm.
conference talks