Saurabh Dash's repositories
GCN_Partitioning
Graph Partitoning Using Graph Convolutional Networks
deeplearning-essentials
This repository contains an explanation of the basic structure of code required to build, train and test deep learning models in pytorch.
browserpilot
Natural language browser automation
cpp-cheat-sheet
C++ Syntax, Data Structures, and Algorithms Cheat Sheet
DeepGenerativeModels-GANandWGAN
GAN and WGAN experiments on MNIST and CelebA (Written for ECE6254 Final Project)
dropbox-backup-tool
tar and upload to dropbox for backup
ECMLDeepAudio
Documented code with instructions to reproduce results of paper submitted to ECML
how-do-vits-work
(ICLR 2022 Spotlight) Official PyTorch implementation of "How Do Vision Transformers Work?"
learnable_fourier_positional_encoding
Learnable Fourier Features for Multi-Dimensional Spatial Positional Encoding
marlin
FP16xINT4 LLM inference kernel that can achieve near-ideal ~4x speedups up to medium batchsizes of 16-32 tokens.
matchbox
Write PyTorch code at the level of individual examples, then run it efficiently on minibatches.
old.saurabhdash.github.io
A beautiful Jekyll theme for academics
PyTorch-GAN
PyTorch implementations of Generative Adversarial Networks.
pytorch-MNIST-CelebA-GAN-DCGAN
Pytorch implementation of Generative Adversarial Networks (GAN) and Deep Convolutional Generative Adversarial Networks (DCGAN) for MNIST and CelebA datasets
pytorch-playground
Base pretrained models and datasets in pytorch (MNIST, SVHN, CIFAR10, CIFAR100, STL10, AlexNet, VGG16, VGG19, ResNet, Inception, SqueezeNet)
pytorch_resnet_cifar10
Proper implementation of ResNet-s for CIFAR10/100 in pytorch that matches description of the original paper.
tgn
TGN: Temporal Graph Networks
the-algorithm-ml
Source code for Twitter's Recommendation Algorithm
Transformer-Hawkes-Process
Code for Transformer Hawkes Process, ICML 2020.