Geri Skenderi's starred repositories
pytorch-image-models
The largest collection of PyTorch image encoders / backbones. Including train, eval, inference, export scripts, and pretrained weights -- ResNet, ResNeXT, EfficientNet, NFNet, Vision Transformer (ViT), MobileNetV4, MobileNet-V3 & V2, RegNet, DPN, CSPNet, Swin Transformer, MaxViT, CoAtNet, ConvNeXt, and more
Awesome-Diffusion-Models
A collection of resources and papers on Diffusion Models
PyTorch-VAE
A Collection of Variational Autoencoders (VAE) in PyTorch.
gans-awesome-applications
Curated list of awesome GAN applications and demo
pattern_classification
A collection of tutorials and examples for solving and understanding machine learning and pattern classification tasks
ML-foundations
Machine Learning Foundations: Linear Algebra, Calculus, Statistics & Computer Science
benchmark_VAE
Unifying Variational Autoencoder (VAE) implementations in Pytorch (NeurIPS 2022)
score_sde_pytorch
PyTorch implementation for Score-Based Generative Modeling through Stochastic Differential Equations (ICLR 2021, Oral)
PINNpapers
Must-read Papers on Physics-Informed Neural Networks.
how-do-vits-work
(ICLR 2022 Spotlight) Official PyTorch implementation of "How Do Vision Transformers Work?"
hugo-profile
A highly customizable and mobile first Hugo template for personal portfolio and blog.
Trajectron-plus-plus
Code accompanying the ECCV 2020 paper "Trajectron++: Dynamically-Feasible Trajectory Forecasting With Heterogeneous Data" by Tim Salzmann*, Boris Ivanovic*, Punarjay Chakravarty, and Marco Pavone (* denotes equal contribution).
optimaltransport.github.io
Web site of the Computational Optimal Transport book
disentanglement-pytorch
Disentanglement library for PyTorch
nngeometry
{KFAC,EKFAC,Diagonal,Implicit} Fisher Matrices and finite width NTKs in PyTorch
ETSformer-pytorch
Implementation of ETSformer, state of the art time-series Transformer, in Pytorch
RecSys_PyTorch
PyTorch implementations of Top-N recommendation, collaborative filtering recommenders.
vae-cf-pytorch
Variational Autoencoders for Collaborative Filtering - Implementation in PyTorch
disentangling-correlated-factors
A benchmarking suite for disentanglement algorithms, suited for evaluating robustness to correlated factors. Codebase for the paper "Disentanglement of Correlated Factors via Hausdorff Factorized Support" by Karsten Roth, Mark Ibrahim, Zeynep Akata, Pascal Vincent, Diane Bouchacourt.
GTM-Transformer
Official Implementation of paper: Well Googled is Half Done: Multimodal Forecasting of New FashionProduct Sales with Image-based Google Trends
pytorch-distributions
Basic VAE flow using pytorch distributions
Disentanglement_NEURIPS_2019
On disentangling the menagerie of disentanglement papers
hyperbolic_alignment
This repo contains a base implementation for aligning hyperbolic representations using an Optimal Transport-based approach.