Sarus implementation of classical ML models. The models are implemented using the Keras API of tensorflow 2. Vizualization are implemented and can be seen in tensorboard.

Last update: Aug 19, 2022

Overview

Sarus published models

Sarus implementation of classical ML models. The models are implemented using the Keras API of tensorflow 2. Vizualization are implemented and can be seen in tensorboard.

The required packages are managed with pipenv and can be installed using pipenv install. Please see the pipenv documentation for more information.

Philosophy

These models' implementations are intended to be easy to read and to adapt by making use of the latest Tensorflow 2 library and Keras API.

Basic usage

To install and train a model.

pipenv install
pipenv shell
python train.py

To visualize losses and reconstructions.

tensorboard --logdir ./logs/

Available models

Owner

Sarus Technologies

GitHub Repository https://sarus.tech/

Pytorch implementation of Implicit Behavior Cloning.

Implicit Behavior Cloning - PyTorch (wip) Pytorch implementation of Implicit Behavior Cloning. Install conda create -n ibc python=3.8 pip install -r r

49 Dec 25, 2022

A pytorch implementation of Pytorch-Sketch-RNN

Pytorch-Sketch-RNN A pytorch implementation of https://arxiv.org/abs/1704.03477 In order to draw other things than cats, you will find more drawing da

172 Dec 12, 2022

Human pose estimation from video plays a critical role in various applications such as quantifying physical exercises, sign language recognition, and full-body gesture control.

Pose Detection Project Description: Human pose estimation from video plays a critical role in various applications such as quantifying physical exerci

2 Jan 17, 2022

The implementation of the paper "A Deep Feature Aggregation Network for Accurate Indoor Camera Localization".

A Deep Feature Aggregation Network for Accurate Indoor Camera Localization This is the PyTorch implementation of our paper "A Deep Feature Aggregation

9 Dec 09, 2022

Code for the paper titled "Generalized Depthwise-Separable Convolutions for Adversarially Robust and Efficient Neural Networks" (NeurIPS 2021 Spotlight).

Generalized Depthwise-Separable Convolutions for Adversarially Robust and Efficient Neural Networks This repository contains the code and pre-trained

7 Dec 05, 2022

Sequence-tagging using deep learning

Classification using Deep Learning Requirements PyTorch version = 1.9.1+cu111 Python version = 3.8.10 PyTorch-Lightning version = 1.4.9 Huggingface

2 Dec 20, 2022

Implementation of gaze tracking and demo

Predicting Customer Demand by Using Gaze Detecting and Object Tracking This project is the integration of gaze detecting and object tracking. Predict

2 Oct 20, 2022

SmoothGrad implementation in PyTorch

SmoothGrad implementation in PyTorch PyTorch implementation of SmoothGrad: removing noise by adding noise. Vanilla Gradients SmoothGrad Guided backpro

143 Jan 05, 2023

Bounding Wasserstein distance with couplings

BoundWasserstein These scripts reproduce the results of the article Bounding Wasserstein distance with couplings by Niloy Biswas and Lester Mackey. ar

1 Jan 11, 2022

Official re-implementation of the Calibrated Adversarial Refinement model described in the paper Calibrated Adversarial Refinement for Stochastic Semantic Segmentation

31 Nov 22, 2022

Automatically align face images 🙃→🙂. Can also do windowing and warping.

Automatic Face Alignment (AFA) Carl M. Gaspar & Oliver G.B. Garrod You have lots of photos of faces like this: But you want to line up all of the face

15 Dec 12, 2022

A Pytorch Implementation of ClariNet

ClariNet A Pytorch Implementation of ClariNet (Mel Spectrogram -- Waveform) Requirements PyTorch 0.4.1 & python 3.6 & Librosa Examples Step 1. Downlo

286 Sep 15, 2022

Official repo of the paper "Surface Form Competition: Why the Highest Probability Answer Isn't Always Right"

Surface Form Competition This is the official repo of the paper "Surface Form Competition: Why the Highest Probability Answer Isn't Always Right" We p

46 Dec 23, 2022

Official repository for Few-shot Image Generation via Cross-domain Correspondence (CVPR '21)

Few-shot Image Generation via Cross-domain Correspondence Utkarsh Ojha, Yijun Li, Jingwan Lu, Alexei A. Efros, Yong Jae Lee, Eli Shechtman, Richard Zh

251 Dec 11, 2022

A package to predict protein inter-residue geometries from sequence data

trRosetta This package is a part of trRosetta protein structure prediction protocol developed in: Improved protein structure prediction using predicte

185 Jan 07, 2023

TensorFlow implementation of "Learning from Simulated and Unsupervised Images through Adversarial Training"

Simulated+Unsupervised (S+U) Learning in TensorFlow TensorFlow implementation of Learning from Simulated and Unsupervised Images through Adversarial T

569 Dec 29, 2022

Exploring Machine Learning Models for detecting anomalous behavior in credit-card transactions. It's crucial that credit-card companies are able to recognize fraudulent activity so that customers are not charged for items they didn't purchase.

Credit Card Fraud Detection Came across this mocked-up dataset of customer transactions at [Capital One Recruitment Challenge](https://github.com/Capi

1 Nov 17, 2022

Sarus implementation of classical ML models. The models are implemented using the Keras API of tensorflow 2. Vizualization are implemented and can be seen in tensorboard.

Related tags

Overview

Sarus published models

Philosophy

Basic usage

Available models

Owner

Sarus Technologies

Pytorch implementation of Implicit Behavior Cloning.

A pytorch implementation of Pytorch-Sketch-RNN

Human pose estimation from video plays a critical role in various applications such as quantifying physical exercises, sign language recognition, and full-body gesture control.

The implementation of the paper "A Deep Feature Aggregation Network for Accurate Indoor Camera Localization".

Code for the paper titled "Generalized Depthwise-Separable Convolutions for Adversarially Robust and Efficient Neural Networks" (NeurIPS 2021 Spotlight).

Sequence-tagging using deep learning

Implementation of gaze tracking and demo

SmoothGrad implementation in PyTorch

Bounding Wasserstein distance with couplings

Official re-implementation of the Calibrated Adversarial Refinement model described in the paper Calibrated Adversarial Refinement for Stochastic Semantic Segmentation

Automatically align face images 🙃→🙂. Can also do windowing and warping.

A Pytorch Implementation of ClariNet

Official repo of the paper "Surface Form Competition: Why the Highest Probability Answer Isn't Always Right"

Official repository for Few-shot Image Generation via Cross-domain Correspondence (CVPR '21)

A package to predict protein inter-residue geometries from sequence data

TensorFlow implementation of "Learning from Simulated and Unsupervised Images through Adversarial Training"

Exploring Machine Learning Models for detecting anomalous behavior in credit-card transactions. It's crucial that credit-card companies are able to recognize fraudulent activity so that customers are not charged for items they didn't purchase.

For encoding a text longer than 512 tokens, for example 800. Set max_pos to 800 during both preprocessing and training.

darija <-> english dictionary

Detail-Preserving Transformer for Light Field Image Super-Resolution