iaspisw

iaspisw's Stars

• prwilkin/CSE379

  Language:Assembly1

• doyom123/cse379

  initial

  Language:Assembly2

• YixinChen-AI/CVAE-GAN-zoos-PyTorch-Beginner

  For beginner, this will be the best start for VAEs, GANs, and CVAE-GAN. This contains AE, DAE, VAE, GAN, CGAN, DCGAN, WGAN, WGAN-GP, VAE-GAN, CVAE-GAN. All use PyTorch.

  Language:Python796114

• makgyver/rectorch

  rectorch is a pytorch-based framework for state-of-the-art top-N recommendation

  Language:Python15119

• jiwidi/Behavior-Sequence-Transformer-Pytorch

  This is a pytorch implementation for the BST model from Alibaba https://arxiv.org/pdf/1905.06874.pdf

  Language:Jupyter Notebook16936

• shenweichen/DeepCTR

  Easy-to-use,Modular and Extendible package of deep-learning based CTR models .

  Language:Python7.9k2.2k

• geek-ai/irgan

  IRGAN SIGIR paper experimental code

  Language:Python621242

• VITA-Group/TransGAN

  [NeurIPS‘2021] "TransGAN: Two Pure Transformers Can Make One Strong GAN, and That Can Scale Up", Yifan Jiang, Shiyu Chang, Zhangyang Wang

  Language:Python1.7k205

• NVIDIA-Merlin/publications

  Language:Jupyter Notebook639

• EmilHvitfeldt/smltar

  Manuscript of the book "Supervised Machine Learning for Text Analysis in R" by Emil Hvitfeldt and Julia Silge

  Language:TeX261105

• deepgenerativemodels/notes

  Course notes

  Language:CSS716142

• NVIDIA-Merlin/Transformers4Rec

  Transformers4Rec is a flexible and efficient library for sequential and session-based recommendation and works with PyTorch.

  Language:Python1.2k151

• sarthak15169/Deep-Music

  In this project, I use LSTM RNN architecture to generate music. The entire Bach corpus from MuseData website (http://musedata.org/) has been used which has 417 raw midi files of the works of the prolific composer Johann Sebastian Bach. When converted to 50 length sequences for training the RNN, I was able to get 2441 sequences which is a good number for training the RNN.

  Language:TeX111

• jihoo-kim/Awesome-Generative-RecSys

  A curated list of Generative Recommender Systems (Paper & Code)

  43941

• ilya-shenbin/RecVAE

  The official PyTorch implementation of the paper "RecVAE: A New Variational Autoencoder for Top-N Recommendations with Implicit Feedback"

  Language:Python11832

• adityashrm21/book-recommender-system-rbm

  A book recommender system created using simple Restricted Boltzmann Machines in TensorFlow

  Language:Jupyter Notebook547

• srp98/Movie-Recommender-using-RBM

  A Movie Recommender System using Restricted Boltzmann Machine (RBM), approach used is collaborative filtering.

  Language:Python3427

• brunnergino/MIDI-VAE

  Language:Python6718

• jbornschein/bihm

  Bidirectional Helmholtz Machines

  Language:Python406

• wiseodd/generative-models

  Collection of generative models, e.g. GAN, VAE in Pytorch and Tensorflow.

  Language:Python7.5k2k

• salu133445/musegan

  An AI for Music Generation

  Language:Python2k395

• je-suis-tm/machine-learning

  Python machine learning applications in image processing, recommender system, matrix completion, netflix problem and algorithm implementations including Co-clustering, Funk SVD, SVD++, Non-negative Matrix Factorization, Koren Neighborhood Model, Koren Integrated Model, Dawid-Skene, Platt-Burges, Expectation Maximization, Factor Analysis, ISTA, FISTA, ADMM, Gaussian Mixture Model, OPTICS, DBSCAN, Random Forest, Decision Tree, Support Vector Machine, Independent Component Analysis, Latent Semantic Indexing, Principal Component Analysis, Singular Value Decomposition, K Nearest Neighbors, K Means, Naïve Bayes Mixture Model, Gaussian Discriminant Analysis, Newton Method, Coordinate Descent, Gradient Descent, Elastic Net Regression, Ridge Regression, Lasso Regression, Least Squares, Logistic Regression, Linear Regression

  Language:Jupyter Notebook25557

• aws/aws-step-functions-data-science-sdk-python

  Step Functions Data Science SDK for building machine learning (ML) workflows and pipelines on AWS

  Language:Python29288

• EllaKaye/BradleyTerryScalable

  R package for fitting the Bradley-Terry model to large datasets

  Language:R253

• lucasmaystre/choix

  Inference algorithms for models based on Luce's choice axiom

  Language:Jupyter Notebook17830

• forieux/qmm

  Python Quadratic Majorization-Minimization (MM) optimization algorithms of half-quadratic criteria. Inverses problems, image restoration, denoising, ...

  Language:Python173

• satyamgovila/MNIST-dataset-Analysis-Python

  Analysing MNIST Dataset and using Principal Component Analysis(PCA) for dimensionality reduction and visualisation.

  Language:Jupyter Notebook22

• alsora/CNN_Visualization

  Implementation of visualization techniques for CNN in Caffe (t-sne, DeconvNet, Image occlusions)

  Language:Python1710

• animebing/mnist_tsne

  t-sne visualization of mnist images when feature is represented by raw pixels and cnn learned feature

  Language:Jupyter Notebook6515

• thu-ml/tianshou

  An elegant PyTorch deep reinforcement learning library.

  Language:Python8.8k1.2k