1763 Repositories
Python generative-adversarial-networks Libraries
A curated list of Generative Deep Art projects, tools, artworks, and models
Generative Deep Art A curated list of Generative Deep Art projects, tools, artworks, and models Inbox Get started with making AI art in 2022 – deeplea
Semantic Segmentation Architectures Implemented in PyTorch
pytorch-semseg Semantic Segmentation Algorithms Implemented in PyTorch This repository aims at mirroring popular semantic segmentation architectures i
Evaluation framework for testing segmentation networks in PyTorch
Evaluation framework for testing segmentation networks in PyTorch. What segmentation network to choose for next Kaggle competition? This benchmark knows the answer!
Example of semantic segmentation in Keras
keras-semantic-segmentation-example Example of semantic segmentation in Keras Single class example: Generated data: random ellipse with random color o
Generative Flow Networks for Discrete Probabilistic Modeling
Energy-based GFlowNets Code for Generative Flow Networks for Discrete Probabilistic Modeling by Dinghuai Zhang, Nikolay Malkin, Zhen Liu, Alexandra Vo
Drslmarkov - Distributionally Robust Structure Learning for Discrete Pairwise Markov Networks
Distributionally Robust Structure Learning for Discrete Pairwise Markov Networks
SAAVN - Sound Adversarial Audio-Visual Navigation,ICLR2022 (In PyTorch)
SAAVN SAAVN Code release for paper "Sound Adversarial Audio-Visual Navigation,IC
Python Assignments for the Deep Learning lectures by Andrew NG on coursera with complete submission for grading capability.
Python Assignments for the Deep Learning lectures by Andrew NG on coursera with complete submission for grading capability.
This repository contains the official code of the paper Equivariant Subgraph Aggregation Networks (ICLR 2022)
Equivariant Subgraph Aggregation Networks (ESAN) This repository contains the official code of the paper Equivariant Subgraph Aggregation Networks (IC
traiNNer is an open source image and video restoration (super-resolution, denoising, deblurring and others) and image to image translation toolbox based on PyTorch.
traiNNer traiNNer is an open source image and video restoration (super-resolution, denoising, deblurring and others) and image to image translation to
CAMPARI: Camera-Aware Decomposed Generative Neural Radiance Fields
CAMPARI: Camera-Aware Decomposed Generative Neural Radiance Fields Paper | Supplementary | Video | Poster If you find our code or paper useful, please
DIR-GNN - Discovering Invariant Rationales for Graph Neural Networks
DIR-GNN "Discovering Invariant Rationales for Graph Neural Networks" (ICLR 2022)
Automatic Number Plate Recognition using Contours and Convolution Neural Networks (CNN)
Cite our paper if you find this project useful https://www.ijariit.com/manuscripts/v7i4/V7I4-1139.pdf Abstract Image processing technology is used in
LSTM model - IMDB review sentiment analysis
NLP - Movie review sentiment analysis The colab notebook contains the code for building a LSTM Recurrent Neural Network that gives 87-88% accuracy on
This is the source code of the 1st place solution for segmentation task (with Dice 90.32%) in 2021 CCF BDCI challenge.
1st place solution in CCF BDCI 2021 ULSEG challenge This is the source code of the 1st place solution for ultrasound image angioma segmentation task (
My solutions for Stanford University course CS224W: Machine Learning with Graphs Fall 2021 colabs (GNN, GAT, GraphSAGE, GCN)
machine-learning-with-graphs My solutions for Stanford University course CS224W: Machine Learning with Graphs Fall 2021 colabs Course materials can be
Explaining Deep Neural Networks - A comparison of different CAM methods based on an insect data set
Explaining Deep Neural Networks - A comparison of different CAM methods based on an insect data set This is the repository for the Deep Learning proje
Computer Vision Paper Reviews with Key Summary of paper, End to End Code Practice and Jupyter Notebook converted papers
Computer-Vision-Paper-Reviews Computer Vision Paper Reviews with Key Summary along Papers & Codes. Jonathan Choi 2021 The repository provides 100+ Pap
Beyond imagenet attack (accepted by ICLR 2022) towards crafting adversarial examples for black-box domains.
Beyond ImageNet Attack: Towards Crafting Adversarial Examples for Black-box Domains (ICLR'2022) This is the Pytorch code for our paper Beyond ImageNet
Tensorflow Implementation of A Generative Flow for Text-to-Speech via Monotonic Alignment Search
Tensorflow Implementation of A Generative Flow for Text-to-Speech via Monotonic Alignment Search
Self-supervised learning algorithms provide a way to train Deep Neural Networks in an unsupervised way using contrastive losses
Self-supervised learning Self-supervised learning algorithms provide a way to train Deep Neural Networks in an unsupervised way using contrastive loss
PyTorch framework, for reproducing experiments from the paper Implicit Regularization in Hierarchical Tensor Factorization and Deep Convolutional Neural Networks
Implicit Regularization in Hierarchical Tensor Factorization and Deep Convolutional Neural Networks. Code, based on the PyTorch framework, for reprodu
This repository serves as a place to document a toy attempt on how to create a generative text model in Catalan, based on GPT-2
GPT-2 Catalan playground and scripts to train a GPT-2 model either from scrath or from another pretrained model.
CoINN: Correlated-informed neural networks: a new machine learning framework to predict pressure drop in micro-channels
CoINN: Correlated-informed neural networks: a new machine learning framework to predict pressure drop in micro-channels Accurate pressure drop estimat
Global-Local Path Networks for Monocular Depth Estimation with Vertical CutDepth [Paper]
Global-Local Path Networks for Monocular Depth Estimation with Vertical CutDepth [Paper] Downloads [Downloads] Trained ckpt files for NYU Depth V2 and
This repository contains the implementation of the HealthGen model, a generative model to synthesize realistic EHR time series data with missingness
HealthGen: Conditional EHR Time Series Generation This repository contains the implementation of the HealthGen model, a generative model to synthesize
Very large and sparse networks appear often in the wild and present unique algorithmic opportunities and challenges for the practitioner
Sparse network learning with snlpy Very large and sparse networks appear often in the wild and present unique algorithmic opportunities and challenges
GAN-based Matrix Factorization for Recommender Systems
GAN-based Matrix Factorization for Recommender Systems This repository contains the datasets' splits, the source code of the experiments and their res
HEAM: High-Efficiency Approximate Multiplier Optimization for Deep Neural Networks
Approximate Multiplier by HEAM What's HEAM? HEAM is a general optimization method to generate high-efficiency approximate multipliers for specific app
Unity Propagation in Bayesian Networks Handling Inconsistency via Unity Smoothing
This repository contains the scripts needed to generate the results from the paper Unity Propagation in Bayesian Networks Handling Inconsistency via U
A PyTorch implementation for our paper "Dual Contrastive Learning: Text Classification via Label-Aware Data Augmentation".
Dual-Contrastive-Learning A PyTorch implementation for our paper "Dual Contrastive Learning: Text Classification via Label-Aware Data Augmentation". Y
On the adaptation of recurrent neural networks for system identification
On the adaptation of recurrent neural networks for system identification This repository contains the Python code to reproduce the results of the pape
Leaf: Multiple-Choice Question Generation
Leaf: Multiple-Choice Question Generation Easy to use and understand multiple-choice question generation algorithm using T5 Transformers. The applicat
Explore the Expression: Facial Expression Generation using Auxiliary Classifier Generative Adversarial Network
Explore the Expression: Facial Expression Generation using Auxiliary Classifier Generative Adversarial Network This is the official implementation of
Adaptive Dropblock Enhanced GenerativeAdversarial Networks for Hyperspectral Image Classification
This repo holds the codes of our paper: Adaptive Dropblock Enhanced GenerativeAdversarial Networks for Hyperspectral Image Classification, which is ac
Out of Distribution Detection on Natural Adversarial Examples
OOD-on-NAE Research project on out of distribution detection for the Computer Vision course by Prof. Rob Fergus (CSCI-GA 2271) Paper out on arXiv - ht
PyTorch implementation of an end-to-end Handwritten Text Recognition (HTR) system based on attention encoder-decoder networks
AttentionHTR PyTorch implementation of an end-to-end Handwritten Text Recognition (HTR) system based on attention encoder-decoder networks. Scene Text
Pytorch implementation code for [Neural Architecture Search for Spiking Neural Networks]
Neural Architecture Search for Spiking Neural Networks Pytorch implementation code for [Neural Architecture Search for Spiking Neural Networks] (https
Improved Fitness Optimization Landscapes for Sequence Design
ReLSO Improved Fitness Optimization Landscapes for Sequence Design Description Citation How to run Training models Original data source Description In
Official repository for the paper "On Evaluation Metrics for Graph Generative Models"
On Evaluation Metrics for Graph Generative Models Authors: Rylee Thompson, Boris Knyazev, Elahe Ghalebi, Jungtaek Kim, Graham Taylor This is the offic
GND-Nets (Graph Neural Diffusion Networks) in TensorFlow.
GNDC For submission to IEEE TKDE. Overview Here we provide the implementation of GND-Nets (Graph Neural Diffusion Networks) in TensorFlow. The reposit
Do Neural Networks for Segmentation Understand Insideness?
This is part of the code to reproduce the results of the paper Do Neural Networks for Segmentation Understand Insideness? [pdf] by K. Villalobos (*),
Explanatory Learning: Beyond Empiricism in Neural Networks
Explanatory Learning This is the official repository for "Explanatory Learning: Beyond Empiricism in Neural Networks". Datasets Download the datasets
PyTorch implementation of our paper How robust are discriminatively trained zero-shot learning models?
How robust are discriminatively trained zero-shot learning models? This repository contains the PyTorch implementation of our paper How robust are dis
Official implementation of the paper Momentum Capsule Networks (MoCapsNet)
Momentum Capsule Network Official implementation of the paper Momentum Capsule Networks (MoCapsNet). Abstract Capsule networks are a class of neural n
Post-training Quantization for Neural Networks with Provable Guarantees
Post-training Quantization for Neural Networks with Provable Guarantees Authors: Jinjie Zhang ([email protected]), Yixuan Zhou ([email protected]) and Ray
Check out the StyleGAN repo and place it in the same directory hierarchy as the present repo
Variational Model Inversion Attacks Kuan-Chieh Wang, Yan Fu, Ke Li, Ashish Khisti, Richard Zemel, Alireza Makhzani Most commands are in run_scripts. W
Pytorch code for our paper Beyond ImageNet Attack: Towards Crafting Adversarial Examples for Black-box Domains)
Beyond ImageNet Attack: Towards Crafting Adversarial Examples for Black-box Domains (ICLR'2022) This is the Pytorch code for our paper Beyond ImageNet
Melanoma Skin Cancer Detection using Convolutional Neural Networks and Transfer Learning🕵🏻♂️
This is a Kaggle competition in which we have to identify if the given lesion image is malignant or not for Melanoma which is a type of skin cancer.
What can linearized neural networks actually say about generalization?
What can linearized neural networks actually say about generalization? This is the source code to reproduce the experiments of the NeurIPS 2021 paper
This repo provides the source code & data of our paper "GreaseLM: Graph REASoning Enhanced Language Models"
GreaseLM: Graph REASoning Enhanced Language Models This repo provides the source code & data of our paper "GreaseLM: Graph REASoning Enhanced Language
EdiBERT is a generative model based on a bi-directional transformer, suited for image manipulation
EdiBERT, a generative model for image editing EdiBERT is a generative model based on a bi-directional transformer, suited for image manipulation. The
Noether Networks: meta-learning useful conserved quantities
Noether Networks: meta-learning useful conserved quantities This repository contains the code necessary to reproduce experiments from "Noether Network
On the Adversarial Robustness of Visual Transformer
On the Adversarial Robustness of Visual Transformer Code for our paper "On the Adversarial Robustness of Visual Transformers"
Adversarial vulnerability of powerful near out-of-distribution detection
Adversarial vulnerability of powerful near out-of-distribution detection by Stanislav Fort In this repository we're collecting replications for the ke
Spectral normalization (SN) is a widely-used technique for improving the stability and sample quality of Generative Adversarial Networks (GANs)
Why Spectral Normalization Stabilizes GANs: Analysis and Improvements [paper (NeurIPS 2021)] [paper (arXiv)] [code] Authors: Zinan Lin, Vyas Sekar, Gi
Evidential Softmax for Sparse Multimodal Distributions in Deep Generative Models
Evidential Softmax for Sparse Multimodal Distributions in Deep Generative Models Abstract Many applications of generative models rely on the marginali
Awesome Transformers in Medical Imaging
This repo supplements our Survey on Transformers in Medical Imaging Fahad Shamshad, Salman Khan, Syed Waqas Zamir, Muhammad Haris Khan, Munawar Hayat,
This code is for our paper "VTGAN: Semi-supervised Retinal Image Synthesis and Disease Prediction using Vision Transformers"
ICCV Workshop 2021 VTGAN This code is for our paper "VTGAN: Semi-supervised Retinal Image Synthesis and Disease Prediction using Vision Transformers"
Unsupervised MRI Reconstruction via Zero-Shot Learned Adversarial Transformers
Official TensorFlow implementation of the unsupervised reconstruction model using zero-Shot Learned Adversarial TransformERs (SLATER). (https://arxiv.
List of awesome things around semantic segmentation 🎉
Awesome Semantic Segmentation List of awesome things around semantic segmentation 🎉 Semantic segmentation is a computer vision task in which we label
Automated Melanoma Recognition in Dermoscopy Images via Very Deep Residual Networks
Introduction This repository contains the modified caffe library and network architectures for our paper "Automated Melanoma Recognition in Dermoscopy
Repository features UNet inspired architecture used for segmenting lungs on chest X-Ray images
Lung Segmentation (2D) Repository features UNet inspired architecture used for segmenting lungs on chest X-Ray images. Demo See the application of the
Pre-trained models for a Cascaded-FCN in caffe and tensorflow that segments
Cascaded-FCN This repository contains the pre-trained models for a Cascaded-FCN in caffe and tensorflow that segments the liver and its lesions out of
Using Convolutional Neural Networks (CNN) for Semantic Segmentation of Breast Cancer Lesions (BRCA)
Using Convolutional Neural Networks (CNN) for Semantic Segmentation of Breast Cancer Lesions (BRCA). Master's thesis documents. Bibliography, experiments and reports.
Multiple Object Extraction from Aerial Imagery with Convolutional Neural Networks
This is an implementation of Volodymyr Mnih's dissertation methods on his Massachusetts road & building dataset and my original methods that are publi
Source code of all the projects of Udacity Self-Driving Car Engineer Nanodegree.
self-driving-car In this repository I will share the source code of all the projects of Udacity Self-Driving Car Engineer Nanodegree. Hope this might
CN24 is a complete semantic segmentation framework using fully convolutional networks
Build status: master (production branch): develop (development branch): Welcome to the CN24 GitHub repository! CN24 is a complete semantic segmentatio
Segment axon and myelin from microscopy data using deep learning
Segment axon and myelin from microscopy data using deep learning. Written in Python. Using the TensorFlow framework. Based on a convolutional neural network architecture. Pixels are classified as either axon, myelin or background.
Taking A Closer Look at Domain Shift: Category-level Adversaries for Semantics Consistent Domain Adaptation
Taking A Closer Look at Domain Shift: Category-level Adversaries for Semantics Consistent Domain Adaptation (CVPR2019) This is a pytorch implementatio
DeepCO3: Deep Instance Co-segmentation by Co-peak Search and Co-saliency
[CVPR19] DeepCO3: Deep Instance Co-segmentation by Co-peak Search and Co-saliency (Oral paper) Authors: Kuang-Jui Hsu, Yen-Yu Lin, Yung-Yu Chuang PDF:
Built a deep neural network (DNN) that functions as an end-to-end machine translation pipeline
Built a deep neural network (DNN) that functions as an end-to-end machine translation pipeline. The pipeline accepts english text as input and returns the French translation.
Code for the paper "Generative design of breakwaters usign deep convolutional neural network as a surrogate model"
Generative design of breakwaters usign deep convolutional neural network as a surrogate model This repository contains the code for the paper "Generat
A deep neural networks for images using CNN algorithm.
Example-CNN-Project This is a simple project showing how to implement deep neural networks using CNN algorithm. The dataset is taken from this link: h
On Evaluation Metrics for Graph Generative Models
On Evaluation Metrics for Graph Generative Models Authors: Rylee Thompson, Boris Knyazev, Elahe Ghalebi, Jungtaek Kim, Graham Taylor This is the offic
To prepare an image processing model to classify the type of disaster based on the image dataset
Disaster Classificiation using CNNs bunnysaini/Disaster-Classificiation Goal To prepare an image processing model to classify the type of disaster bas
This project generates news headlines using a Long Short-Term Memory (LSTM) neural network.
News Headlines Generator bunnysaini/Generate-Headlines Goal This project aims to generate news headlines using a Long Short-Term Memory (LSTM) neural
An curated collection of awesome resources about networking in cybersecurity
An ongoing curated collection of awesome software, libraries, frameworks, talks & videos, best practices, learning tutorials and important practical resources about networking in cybersecurity
A notebook explaining the principle of adversarial attacks and their defences
TL;DR: A notebook explaining the principle of adversarial attacks and their defences Abstract: Deep neural networks models have been wildly successful
Multi-modal Text Recognition Networks: Interactive Enhancements between Visual and Semantic Features
Multi-modal Text Recognition Networks: Interactive Enhancements between Visual and Semantic Features | paper | Official PyTorch implementation for Mul
Perform sentiment analysis on textual data that people generally post on websites like social networks and movie review sites.
Sentiment Analyzer The goal of this project is to perform sentiment analysis on textual data that people generally post on websites like social networ
nn_builder lets you build neural networks with less boilerplate code
nn_builder lets you build neural networks with less boilerplate code. You specify the type of network you want and it builds it. Install pip install n
Neuron class provides LNU (Linear Neural Unit), QNU (Quadratic Neural Unit), RBF (Radial Basis Function), MLP (Multi Layer Perceptron), MLP-ELM (Multi Layer Perceptron - Extreme Learning Machine) neurons learned with Gradient descent or LeLevenberg–Marquardt algorithm
Neuron class provides LNU (Linear Neural Unit), QNU (Quadratic Neural Unit), RBF (Radial Basis Function), MLP (Multi Layer Perceptron), MLP-ELM (Multi Layer Perceptron - Extreme Learning Machine) neurons learned with Gradient descent or LeLevenberg–Marquardt algorithm
Peek-a-Boo: What (More) is Disguised in a Randomly Weighted Neural Network, and How to Find It Efficiently
Peek-a-Boo: What (More) is Disguised in a Randomly Weighted Neural Network, and How to Find It Efficiently This repository is the official implementat
Google AI Open Images - Object Detection Track: Open Solution
Google AI Open Images - Object Detection Track: Open Solution This is an open solution to the Google AI Open Images - Object Detection Track 😃 More c
Airbus Ship Detection Challenge
Airbus Ship Detection Challenge This is an open solution to the Airbus Ship Detection Challenge. Our goals We are building entirely open solution to t
This Deep Learning Model Predicts that from which disease you are suffering.
Deep-Learning-Project This Deep Learning Model Predicts that from which disease you are suffering. This Project Covers the Topics of Deep Learning Int
GalaXC: Graph Neural Networks with Labelwise Attention for Extreme Classification
GalaXC GalaXC: Graph Neural Networks with Labelwise Attention for Extreme Classification @InProceedings{Saini21, author = {Saini, D. and Jain,
Code for the paper BERT might be Overkill: A Tiny but Effective Biomedical Entity Linker based on Residual Convolutional Neural Networks
Biomedical Entity Linking This repo provides the code for the paper BERT might be Overkill: A Tiny but Effective Biomedical Entity Linker based on Res
Single Red Blood Cell Hydrodynamic Traps Via the Generative Design
Rbc-traps-generative-design - The generative design for single red clood cell hydrodynamic traps using GEFEST framework
Conditional Generative Adversarial Networks (CGAN) for Mobility Data Fusion
This code implements the paper, Kim et al. (2021). Imputing Qualitative Attributes for Trip Chains Extracted from Smart Card Data Using a Conditional Generative Adversarial Network. Transportation Research Part C. Under Review.
Can We Find Neurons that Cause Unrealistic Images in Deep Generative Networks?
Can We Find Neurons that Cause Unrealistic Images in Deep Generative Networks? Artifact Detection/Correction - Offcial PyTorch Implementation This rep
Employs neural networks to classify images into four categories: ship, automobile, dog or frog
Neural Net Image Classifier Employs neural networks to classify images into four categories: ship, automobile, dog or frog Viterbi_1.py uses a classic
Brain Tumor Detection with Tensorflow Neural Networks.
Brain-Tumor-Detection A convolutional neural network model built with Tensorflow & Keras to detect brain tumor and its different variants. Data of the
Animal Sound Classification (Cats Vrs Dogs Audio Sentiment Classification)
this is a simple artificial neural network model using deep learning and torch-audio to classify cats and dog sounds.
Unofficial PyTorch Implementation of "Augmenting Convolutional networks with attention-based aggregation"
Pytorch Implementation of Augmenting Convolutional networks with attention-based aggregation This is the unofficial PyTorch Implementation of "Augment
Cross-modal Retrieval using Transformer Encoder Reasoning Networks (TERN). With use of Metric Learning and FAISS for fast similarity search on GPU
Cross-modal Retrieval using Transformer Encoder Reasoning Networks This project reimplements the idea from "Transformer Reasoning Network for Image-Te
CIFS: Improving Adversarial Robustness of CNNs via Channel-wise Importance-based Feature Selection
CIFS This repository provides codes for CIFS (ICML 2021). CIFS: Improving Adversarial Robustness of CNNs via Channel-wise Importance-based Feature Sel
OneShot Learning-based hotword detection.
EfficientWord-Net Hotword detection based on one-shot learning Home assistants require special phrases called hotwords to get activated (eg:"ok google
Reimplementation of Learning Mesh-based Simulation With Graph Networks
Pytorch Implementation of Learning Mesh-based Simulation With Graph Networks This is the unofficial implementation of the approach described in the pa