Ayan Das's repositories
mlx-examples
Examples in the MLX framework
mlx-data
Efficient framework-agnostic data loading
mlx
MLX: An array framework for Apple silicon
diffusers
🤗 Diffusers: State-of-the-art diffusion models for image and audio generation in PyTorch
mlx-benchmark
Benchmark of Apple's MLX operations on mlx gpu, cpu, torch mps and cuda.
dasayan05
My Github profile README repo
iclr24_blog_code
Code repo for ICLR 24 BlogPost titled "Building Diffusion Model's theory from ground up"
Awesome-Diffusion-Models
A collection of resources and papers on Diffusion Models and Score-based Models, a darkhorse in the field of Generative Models
typst-ai-conf-templates
AI conference templates in Typst
Awesome-Sketch-Based-Applications
:books: A collection of sketch based application papers.
pytorch-lightning
The lightweight PyTorch wrapper for high-performance AI research. Scale your models, not the boilerplate.
awesome-neural-ode
A collection of resources regarding the interplay between differential equations, deep learning, dynamical systems, control and numerical methods.
jsonargparse
Parsing of command line options, yaml/jsonnet config files and/or environment variables based on argparse
neuralsort-siggraph
Neural Sort implementation for "Pixelor: A Competitive Sketching AI Agent. So you think you can sketch?" accepted @ SIGGRAPH Asia 2020
bnlp
BNLP is a natural language processing toolkit for Bengali Language.
quickdraw_nn_dataset
PyTorch nn.Dataset for QuickDraw
patterns-of-randomness
Code to reproduce figures from my blog post https://dasayan05.github.io/blog-tut/2020/04/15/patterns-of-randomness.html
vanilla-GAN
Implementation of Vanilla GAN
neuralode-pytorch
A simple implementation of ODE Layer from Neural ODE
pytorch-normalizing-flows
Normalizing flows in PyTorch. Current intended use is education not production.
sketchanet-quickdraw
Implements Sketch-a-Net in PyTorch and trains it with QuickDraw raster images
Carrom_rl
A Pygame+Pymunk Carrom Simulation Testbed for reinforcement learning. [CS747][ Foundations of Intelligent and Learning Agents]