ashok-arjun

Awesome-Sketch-Based-Applications

:books: A collection of sketch based application papers.

Awesome-Talking-Face

📖 A curated list of resources dedicated to talking face.

CSCCT

Official Implementation of the ECCV 2022 Paper "Class-Incremental Learning with Cross-Space Clustering and Controlled Transfer"

Gaussian-Poisson-GANs-For-Image-Blending

Blending composite images using a generative model and a Gaussian-Poisson equation with a Laplacian Pyramid

MLRC-2021-Few-Shot-Learning-And-Self-Supervision

Does Self-supervision Always Improve Few-shot Learning? - MLRC 2021 and ReScience-C

Monocular-Depth-Estimation

Depth estimation from single-view RGB images

pytorch-transformer-ts

Repository of Transformer based PyTorch Time Series Models

Zero-Shot-Sketch-Based-Image-Retrieval

Zero-shot sketch-based image retrieval using a domain adversarial neural network

TACTiS

TACTiS-2: Better, Faster, Simpler Attentional Copulas for Multivariate Time Series, from ServiceNow Research

lag-llama

Lag-Llama: Towards Foundation Models for Probabilistic Time Series Forecasting

ashok-arjun/BigGAN-PyTorch

The author's officially unofficial PyTorch BigGAN implementation.

ashok-arjun/few-shot

A lightweight library that implements state-of-the-art few-shot learning algorithms.

ashok-arjun/fsl_ssl

Code for "When Does Self-supervision Improve Few-shot Learning?" ECCV 2020

ashok-arjun/HyperNetworks

PyTorch implementation of HyperNetworks (Ha et al., ICLR 2017) for ResNet (Residual Networks)

ashok-arjun/AIM-Fewshot-Continual

ashok-arjun/annotated_deep_learning_paper_implementations

🧠 Implementations/tutorials of deep learning papers with side-by-side notes; including transformers (original, xl, switch, feedback), optimizers(adam, radam, adabelief), gans(dcgan, cyclegan, stylegan2), reinforcement learning (ppo, dqn), capsnet, sketch-rnn, etc.

ashok-arjun/awesome-ai-residency

List of AI Residency Programs

ashok-arjun/brain-inspired-replay

A brain-inspired version of generative replay for continual learning with deep neural networks (e.g., class-incremental learning on CIFAR-100; PyTorch code).

ashok-arjun/CloserLookFewShot

source code to ICLR'19, 'A Closer Look at Few-shot Classification'

ashok-arjun/colabcode

Run VSCode (codeserver) on Google Colab or Kaggle Notebooks

ashok-arjun/distributed_tutorial

ashok-arjun/dropbox-sdk-python

The Official Dropbox API V2 SDK for Python

ashok-arjun/fairtorch

PyTorch implementation of parity loss as constraints function to realize the fairness of machine learning.

ashok-arjun/files

ashok-arjun/img_classification_pk_pytorch

Quickly comparing your image classification models with the state-of-the-art models (such as DenseNet, ResNet, ...)

ashok-arjun/LCFCN-AI

ashok-arjun/metanas

Meta-Learning of Neural Architectures for Few-Shot Learning

ashok-arjun/ML-paper-notes

:book: Notes and summaries of some Machine Learning, Computer Vision & NLP papers.

ashok-arjun/NAS-with-Proxy-data

Official code of "NAS acceleration via proxy data", IJCAI21

ashok-arjun/Orthogonal-Convolutional-Neural-Networks

Code for paper "Orthogonal Convolutional Neural Networks".

ashok-arjun/pytorch-cifar-models

Pretrained models on CIFAR10/100 in PyTorch

ashok-arjun/pytorch-cifar100

Practice on cifar100(ResNet, DenseNet, VGG, GoogleNet, InceptionV3, InceptionV4, Inception-ResNetv2, Xception, Resnet In Resnet, ResNext,ShuffleNet, ShuffleNetv2, MobileNet, MobileNetv2, SqueezeNet, NasNet, Residual Attention Network, SENet, WideResNet)

ashok-arjun/pytorch3d

PyTorch3D is FAIR's library of reusable components for deep learning with 3D data

ashok-arjun/pytorchviz

A small package to create visualizations of PyTorch execution graphs

ashok-arjun/reloading

Change Python code while it's running without losing state

ashok-arjun/rfs

ashok-arjun/SelfTime

Fork of SelfTime

ashok-arjun/ShakeItOff--HackCambridge

Set your Fitbit calories goal by just scanning your food receipt!

ashok-arjun/SSL-FEW-SHOT

SSL-FEW-SHOT

ashok-arjun/Wav2Lip

This repository contains the codes of "A Lip Sync Expert Is All You Need for Speech to Lip Generation In the Wild", published at ACM Multimedia 2020.