⚙️ minimal paralllelizable physics simulator supporting differentiation entirely in torch

VoMP: Predicting Volumetric Mechanical Property Fields

GigaTrain: An Efficient and Scalable Training Framework for AI Models

Squeeze3D: Your 3D Generation Model is Secretly an Extreme Neural Compressor

GPU-optimized version of the MuJoCo physics simulator, designed for NVIDIA hardware.

Ray tracing and hybrid rasterization of Gaussian particles

NVIDIA Cosmos is an open platform of world models, datasets, and tools that enables developers to build Physical AI for robots, autonomous vehicles, smart infrastructure, and more.

Simulate a mesh, Gaussian Splat, or a NeRF

Official code for NeRF-US: Removing Ultrasound Imaging Artifacts from Neural Radiance Fields in the Wild

Fast and memory-efficient exact attention

Official code for SEE-2-SOUND: Zero-Shot Spatial Environment-to-Spatial Sound

Schedule-Free Optimization in PyTorch

TORAX: Tokamak transport simulation in JAX

Grok open release

A pytorch CUDA extension implementation of instant-ngp (sdf and nerf), with a GUI.

Simple code for generating a color-coded latex table from raw data

This repository contains the official implementation of Astroformer, an ICLR Workshop 2023 paper.

[ICLR 2024 Oral] Generative Gaussian Splatting for Efficient 3D Content Creation

ImageBind One Embedding Space to Bind Them All

A collection of utility functions to prototype geometry processing research in python

3D Transforms is a library to easily work with 3D data and make 3D transformations. This library originally started as a few functions here and there for my own work which I then turned into a libr…

An implementation of Invariant Point Attention from Alphafold 2

An implementation of "Set Transformer: A Framework for Attention-based Permutation-Invariant Neural Networks"

Official Implementation of ICML 2023 paper: "A Generalization of ViT/MLP-Mixer to Graphs"

Easily train or fine-tune SOTA computer vision models with one open source training library. The home of Yolo-NAS.

My notes from UofT CS Theory Research Group seminars