1763 Repositories
Python generative-adversarial-networks Libraries
Autoregressive Models in PyTorch.
Autoregressive This repository contains all the necessary PyTorch code, tailored to my presentation, to train and generate data from WaveNet-like auto
Plenoxels: Radiance Fields without Neural Networks
Plenoxels: Radiance Fields without Neural Networks Alex Yu*, Sara Fridovich-Keil*, Matthew Tancik, Qinhong Chen, Benjamin Recht, Angjoo Kanazawa UC Be
A modular PyTorch library for optical flow estimation using neural networks
A modular PyTorch library for optical flow estimation using neural networks
Official implementation of "A Shared Representation for Photorealistic Driving Simulators" in PyTorch.
A Shared Representation for Photorealistic Driving Simulators The official code for the paper: "A Shared Representation for Photorealistic Driving Sim
Visual Adversarial Imitation Learning using Variational Models (VMAIL)
Visual Adversarial Imitation Learning using Variational Models (VMAIL) This is the official implementation of the NeurIPS 2021 paper. Project website
Codes for TIM2021 paper "Anchor-Based Spatio-Temporal Attention 3-D Convolutional Networks for Dynamic 3-D Point Cloud Sequences"
Codes for TIM2021 paper "Anchor-Based Spatio-Temporal Attention 3-D Convolutional Networks for Dynamic 3-D Point Cloud Sequences"
Supplemental learning materials for "Fourier Feature Networks and Neural Volume Rendering"
Fourier Feature Networks and Neural Volume Rendering This repository is a companion to a lecture given at the University of Cambridge Engineering Depa
Plenoxels: Radiance Fields without Neural Networks, Code release WIP
Plenoxels: Radiance Fields without Neural Networks Alex Yu*, Sara Fridovich-Keil*, Matthew Tancik, Qinhong Chen, Benjamin Recht, Angjoo Kanazawa UC Be
[KDD 2021, Research Track] DiffMG: Differentiable Meta Graph Search for Heterogeneous Graph Neural Networks
DiffMG This repository contains the code for our KDD 2021 Research Track paper: DiffMG: Differentiable Meta Graph Search for Heterogeneous Graph Neura
Public repository of the 3DV 2021 paper "Generative Zero-Shot Learning for Semantic Segmentation of 3D Point Clouds"
Generative Zero-Shot Learning for Semantic Segmentation of 3D Point Clouds Björn Michele1), Alexandre Boulch1), Gilles Puy1), Maxime Bucher1) and Rena
A modular application for performing anomaly detection in networks
Deep-Learning-Models-for-Network-Annomaly-Detection The modular app consists for mainly three annomaly detection algorithms. The system supports model
Official Implementation of "LUNAR: Unifying Local Outlier Detection Methods via Graph Neural Networks"
LUNAR Official Implementation of "LUNAR: Unifying Local Outlier Detection Methods via Graph Neural Networks" Adam Goodge, Bryan Hooi, Ng See Kiong and
This repository is an implementation of paper : Improving the Training of Graph Neural Networks with Consistency Regularization
CRGNN Paper : Improving the Training of Graph Neural Networks with Consistency Regularization Environments Implementing environment: GeForce RTX™ 3090
Meandering In Networks of Entities to Reach Verisimilar Answers
MINERVA Meandering In Networks of Entities to Reach Verisimilar Answers Code and models for the paper Go for a Walk and Arrive at the Answer - Reasoni
Federated Deep Reinforcement Learning for the Distributed Control of NextG Wireless Networks.
FDRL-PC-Dyspan Federated Deep Reinforcement Learning for the Distributed Control of NextG Wireless Networks. This repository contains the entire code
The best solution of the Weather Prediction track in the Yandex Shifts challenge
yandex-shifts-weather The repository contains information about my solution for the Weather Prediction track in the Yandex Shifts challenge https://re
Implementation of paper "Decision-based Black-box Attack Against Vision Transformers via Patch-wise Adversarial Removal"
Patch-wise Adversarial Removal Implementation of paper "Decision-based Black-box Attack Against Vision Transformers via Patch-wise Adversarial Removal
RID-Noise: Towards Robust Inverse Design under Noisy Environments
This is code of RID-Noise. Reproduce RID-Noise Results Toy tasks Please refer to the notebook ridnoise.ipynb to view experiments on three toy tasks. B
A new framework, collaborative cascade prediction based on graph neural networks (CCasGNN) to jointly utilize the structural characteristics, sequence features, and user profiles.
CCasGNN A new framework, collaborative cascade prediction based on graph neural networks (CCasGNN) to jointly utilize the structural characteristics,
Flexible Networks for Learning Physical Dynamics of Deformable Objects (2021)
Flexible Networks for Learning Physical Dynamics of Deformable Objects (2021) By Jinhyung Park, Dohae Lee, In-Kwon Lee from Yonsei University (Seoul,
SalFBNet: Learning Pseudo-Saliency Distribution via Feedback Convolutional Networks
SalFBNet This repository includes Pytorch implementation for the following paper: SalFBNet: Learning Pseudo-Saliency Distribution via Feedback Convolu
S-attack library. Official implementation of two papers "Are socially-aware trajectory prediction models really socially-aware?" and "Vehicle trajectory prediction works, but not everywhere".
S-attack library: A library for evaluating trajectory prediction models This library contains two research projects to assess the trajectory predictio
This repository is an implementation of paper : Improving the Training of Graph Neural Networks with Consistency Regularization
CRGNN Paper : Improving the Training of Graph Neural Networks with Consistency Regularization Environments Implementing environment: GeForce RTX™ 3090
Official PyTorch implementation of the ICRA 2021 paper: Adversarial Differentiable Data Augmentation for Autonomous Systems.
Adversarial Differentiable Data Augmentation This repository provides the official PyTorch implementation of the ICRA 2021 paper: Adversarial Differen
Self-Supervised Learning of Event-based Optical Flow with Spiking Neural Networks
Self-Supervised Learning of Event-based Optical Flow with Spiking Neural Networks Work accepted at NeurIPS'21 [paper, video]. If you use this code in
An Implementation of Transformer in Transformer in TensorFlow for image classification, attention inside local patches
Transformer-in-Transformer An Implementation of the Transformer in Transformer paper by Han et al. for image classification, attention inside local pa
Federated learning on graph, especially on graph neural networks (GNNs), knowledge graph, and private GNN.
Federated learning on graph, especially on graph neural networks (GNNs), knowledge graph, and private GNN.
Papers about explainability of GNNs
Papers about explainability of GNNs
Pytorch code for "Text-Independent Speaker Verification Using 3D Convolutional Neural Networks".
:speaker: Deep Learning & 3D Convolutional Neural Networks for Speaker Verification
Generative Handwriting using LSTM Mixture Density Network with TensorFlow
Generative Handwriting Demo using TensorFlow An attempt to implement the random handwriting generation portion of Alex Graves' paper. See my blog post
The Simplest DCGAN Implementation
DCGAN in TensorLayer This is the TensorLayer implementation of Deep Convolutional Generative Adversarial Networks. Looking for Text to Image Synthesis
Generative Adversarial Text to Image Synthesis
Text To Image Synthesis This is a tensorflow implementation of synthesizing images. The images are synthesized using the GAN-CLS Algorithm from the pa
Unsupervised Image to Image Translation with Generative Adversarial Networks
Unsupervised Image to Image Translation with Generative Adversarial Networks Paper: Unsupervised Image to Image Translation with Generative Adversaria
The implementation code for "DAGAN: Deep De-Aliasing Generative Adversarial Networks for Fast Compressed Sensing MRI Reconstruction"
DAGAN This is the official implementation code for DAGAN: Deep De-Aliasing Generative Adversarial Networks for Fast Compressed Sensing MRI Reconstruct
Dynamic Capacity Networks using Tensorflow
Dynamic Capacity Networks using Tensorflow Dynamic Capacity Networks (DCN; http://arxiv.org/abs/1511.07838) implementation using Tensorflow. DCN reduc
TensorFlow implementation of the paper "Hierarchical Attention Networks for Document Classification"
Hierarchical Attention Networks for Document Classification This is an implementation of the paper Hierarchical Attention Networks for Document Classi
End-To-End Memory Network using Tensorflow
MemN2N Implementation of End-To-End Memory Networks with sklearn-like interface using Tensorflow. Tasks are from the bAbl dataset. Get Started git clo
Translate darknet to tensorflow. Load trained weights, retrain/fine-tune using tensorflow, export constant graph def to mobile devices
Intro Real-time object detection and classification. Paper: version 1, version 2. Read more about YOLO (in darknet) and download weight files here. In
CNN visualization tool in TensorFlow
tf_cnnvis A blog post describing the library: https://medium.com/@falaktheoptimist/want-to-look-inside-your-cnn-we-have-just-the-right-tool-for-you-ad
Deep Learning & 3D Convolutional Neural Networks for Speaker Verification
TensorFlow implementation of 3D Convolutional Neural Networks for Speaker Verification - Official Project Page - Pytorch Implementation This repositor
Lip Reading - Cross Audio-Visual Recognition using 3D Convolutional Neural Networks
Lip Reading - Cross Audio-Visual Recognition using 3D Convolutional Neural Networks - Official Project Page This repository contains the code develope
A Tensorfflow implementation of Attend, Infer, Repeat
Attend, Infer, Repeat: Fast Scene Understanding with Generative Models This is an unofficial Tensorflow implementation of Attend, Infear, Repeat (AIR)
Semi-Supervised Learning with Ladder Networks in Keras. Get 98% test accuracy on MNIST with just 100 labeled examples !
Semi-Supervised Learning with Ladder Networks in Keras This is an implementation of Ladder Network in Keras. Ladder network is a model for semi-superv
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.
Sarus published models Sarus implementation of classical ML models. The models are implemented using the Keras API of tensorflow 2. Vizualization are
Run Keras models in the browser, with GPU support using WebGL
**This project is no longer active. Please check out TensorFlow.js.** The Keras.js demos still work but is no longer updated. Run Keras models in the
SLAMP: Stochastic Latent Appearance and Motion Prediction
SLAMP: Stochastic Latent Appearance and Motion Prediction Official implementation of the paper SLAMP: Stochastic Latent Appearance and Motion Predicti
Training Structured Neural Networks Through Manifold Identification and Variance Reduction
Training Structured Neural Networks Through Manifold Identification and Variance Reduction This repository is a pytorch implementation of the Regulari
Learning Tracking Representations via Dual-Branch Fully Transformer Networks
Learning Tracking Representations via Dual-Branch Fully Transformer Networks DualTFR ⭐ We achieves the runner-ups for both VOT2021ST (short-term) and
A new play-and-plug method of controlling an existing generative model with conditioning attributes and their compositions.
Controllable and Compositional Generation with Latent-Space Energy-Based Models Official PyTorch implementation of the NeurIPS 2021 paper: Controllabl
Graph Posterior Network: Bayesian Predictive Uncertainty for Node Classification (NeurIPS 2021)
Graph Posterior Network This is the official code repository to the paper Graph Posterior Network: Bayesian Predictive Uncertainty for Node Classifica
Train and use generative text models in a few lines of code.
blather Train and use generative text models in a few lines of code. To see blather in action check out the colab notebook! Installation Use the packa
Alternatives to Deep Neural Networks for Function Approximations in Finance
Alternatives to Deep Neural Networks for Function Approximations in Finance Code companion repo Overview This is a repository of Python code to go wit
Convert ONNX model graph to Keras model format.
Convert ONNX model graph to Keras model format.
Object Detection with YOLOv3
Object Detection with YOLOv3 Bu projede YOLOv3-608 modeli kullanılmıştır. Requirements Python 3.8 OpenCV Numpy Documentation Yolo ile ilgili detaylı b
Is RobustBench/AutoAttack a suitable Benchmark for Adversarial Robustness?
Adversrial Machine Learning Benchmarks This code belongs to the papers: Is RobustBench/AutoAttack a suitable Benchmark for Adversarial Robustness? Det
Source code and dataset of the paper "Contrastive Adaptive Propagation Graph Neural Networks forEfficient Graph Learning"
CAPGNN Source code and dataset of the paper "Contrastive Adaptive Propagation Graph Neural Networks forEfficient Graph Learning" Paper URL: https://ar
TC-GNN with Pytorch integration
TC-GNN (Running Sparse GNN on Dense Tensor Core on Ampere GPU) Cite this project and paper. @inproceedings{TC-GNN, title={TC-GNN: Accelerating Spars
Efficient Two-Step Networks for Temporal Action Segmentation (Neurocomputing 2021)
Efficient Two-Step Networks for Temporal Action Segmentation This repository provides a PyTorch implementation of the paper Efficient Two-Step Network
Self-Supervised Generative Style Transfer for One-Shot Medical Image Segmentation
Self-Supervised Generative Style Transfer for One-Shot Medical Image Segmentation This repository contains the Pytorch implementation of the proposed
An assignment from my grad-level data mining course demonstrating some experience with NLP/neural networks/Pytorch
NLP-Pytorch-Assignment An assignment from my grad-level data mining course (before I started personal projects) demonstrating some experience with NLP
With Py-Autocrack you can crack WPA2 networks in no time.
With Py-Autocrack you can crack WPA2 networks in no time. All based on Aircrack-ng and Crunch.
Official implementation for the paper: Permutation Invariant Graph Generation via Score-Based Generative Modeling
Permutation Invariant Graph Generation via Score-Based Generative Modeling This repo contains the official implementation for the paper Permutation In
Implementation of "Adversarial purification with Score-based generative models", ICML 2021
Adversarial Purification with Score-based Generative Models by Jongmin Yoon, Sung Ju Hwang, Juho Lee This repository includes the official PyTorch imp
Noise Conditional Score Networks (NeurIPS 2019, Oral)
Generative Modeling by Estimating Gradients of the Data Distribution This repo contains the official implementation for the NeurIPS 2019 paper Generat
The official PyTorch implementation for NCSNv2 (NeurIPS 2020)
Improved Techniques for Training Score-Based Generative Models This repo contains the official implementation for the paper Improved Techniques for Tr
Code for paper "Adversarial score matching and improved sampling for image generation"
Adversarial score matching and improved sampling for image generation This repo contains the official implementation for the ICLR 2021 paper Adversari
Diffusion Probabilistic Models for 3D Point Cloud Generation (CVPR 2021)
Diffusion Probabilistic Models for 3D Point Cloud Generation [Paper] [Code] The official code repository for our CVPR 2021 paper "Diffusion Probabilis
PyTorch Implementation of DSB for Score Based Generative Modeling. Experiments managed using Hydra.
Diffusion Schrödinger Bridge with Applications to Score-Based Generative Modeling This repository contains the implementation for the paper Diffusion
A collection of resources and papers on Diffusion Models, a darkhorse in the field of Generative Models
This repository contains a collection of resources and papers on Diffusion Models and Score-based Models. If there are any missing valuable resources
A Loss Function for Generative Neural Networks Based on Watson’s Perceptual Model
This repository contains the similarity metrics designed and evaluated in the paper, and instructions and code to re-run the experiments. Implementation in the deep-learning framework PyTorch
MoViNets PyTorch implementation: Mobile Video Networks for Efficient Video Recognition;
MoViNet-pytorch Pytorch unofficial implementation of MoViNets: Mobile Video Networks for Efficient Video Recognition. Authors: Dan Kondratyuk, Liangzh
The Official PyTorch Implementation of "LSGM: Score-based Generative Modeling in Latent Space" (NeurIPS 2021)
The Official PyTorch Implementation of "LSGM: Score-based Generative Modeling in Latent Space" (NeurIPS 2021) Arash Vahdat* · Karsten Kreis* ·
The project page of paper: Architecture disentanglement for deep neural networks [ICCV 2021, oral]
This is the project page for the paper: Architecture Disentanglement for Deep Neural Networks, Jie Hu, Liujuan Cao, Tong Tong, Ye Qixiang, ShengChuan
Spatial Temporal Graph Convolutional Networks (ST-GCN) for Skeleton-Based Action Recognition in PyTorch
Reminder ST-GCN has transferred to MMSkeleton, and keep on developing as an flexible open source toolbox for skeleton-based human understanding. You a
End-2-end speech synthesis with recurrent neural networks
Introduction New: Interactive demo using Google Colaboratory can be found here TTS-Cube is an end-2-end speech synthesis system that provides a full p
PyTorch implementation of the Pose Residual Network (PRN)
Pose Residual Network This repository contains a PyTorch implementation of the Pose Residual Network (PRN) presented in our ECCV 2018 paper: Muhammed
A generative art library for NFT avatar and collectible projects.
Generative NFT Art Introduction The generative-art-nft repository is a library for creating generative art. It was developed for the purpose of creati
Research Code for NeurIPS 2020 Spotlight paper "Large-Scale Adversarial Training for Vision-and-Language Representation Learning": UNITER adversarial training part
VILLA: Vision-and-Language Adversarial Training This is the official repository of VILLA (NeurIPS 2020 Spotlight). This repository currently supports
PyTorch implementation for "HyperSPNs: Compact and Expressive Probabilistic Circuits", NeurIPS 2021
HyperSPN This repository contains code for the paper: HyperSPNs: Compact and Expressive Probabilistic Circuits "HyperSPNs: Compact and Expressive Prob
Codebase for Inducing Causal Structure for Interpretable Neural Networks
Interchange Intervention Training (IIT) Codebase for Inducing Causal Structure for Interpretable Neural Networks Release Notes 12/01/2021: Code and Pa
PyTorch(Geometric) implementation of G^2GNN in "Imbalanced Graph Classification via Graph-of-Graph Neural Networks"
This repository is an official PyTorch(Geometric) implementation of G^2GNN in "Imbalanced Graph Classification via Graph-of-Graph Neural Networks". Th
An implementation of the AdaOPS (Adaptive Online Packing-based Search), which is an online POMDP Solver used to solve problems defined with the POMDPs.jl generative interface.
AdaOPS An implementation of the AdaOPS (Adaptive Online Packing-guided Search), which is an online POMDP Solver used to solve problems defined with th
Palo Alto Networks PAN-OS SDK for Python
Palo Alto Networks PAN-OS SDK for Python The PAN-OS SDK for Python (pan-os-python) is a package to help interact with Palo Alto Networks devices (incl
Local Similarity Pattern and Cost Self-Reassembling for Deep Stereo Matching Networks
Local Similarity Pattern and Cost Self-Reassembling for Deep Stereo Matching Networks Contributions A novel pairwise feature LSP to extract structural
Another pytorch implementation of FCN (Fully Convolutional Networks)
FCN-pytorch-easiest Trying to be the easiest FCN pytorch implementation and just in a get and use fashion Here I use a handbag semantic segmentation f
Milano is a tool for automating hyper-parameters search for your models on a backend of your choice.
Milano (This is a research project, not an official NVIDIA product.) Documentation https://nvidia.github.io/Milano Milano (Machine learning autotuner
A light weight data augmentation tool for training CNNs and Viola Jones detectors
hey-daug A light weight data augmentation tool for training CNNs and Viola Jones detectors (Haar Cascades). This tool inflates your data by up to six
Code & Models for Temporal Segment Networks (TSN) in ECCV 2016
Temporal Segment Networks (TSN) We have released MMAction, a full-fledged action understanding toolbox based on PyTorch. It includes implementation fo
Convolutional Neural Networks
Darknet Darknet is an open source neural network framework written in C and CUDA. It is fast, easy to install, and supports CPU and GPU computation. D
Reproduce ResNet-v2(Identity Mappings in Deep Residual Networks) with MXNet
Reproduce ResNet-v2 using MXNet Requirements Install MXNet on a machine with CUDA GPU, and it's better also installed with cuDNN v5 Please fix the ran
Codebase for testing whether hidden states of neural networks encode discrete structures.
structural-probes Codebase for testing whether hidden states of neural networks encode discrete structures. Based on the paper A Structural Probe for
Code for EMNLP2020 long paper: BERT-Attack: Adversarial Attack Against BERT Using BERT
BERT-ATTACK Code for our EMNLP2020 long paper: BERT-ATTACK: Adversarial Attack Against BERT Using BERT Dependencies Python 3.7 PyTorch 1.4.0 transform
A Model for Natural Language Attack on Text Classification and Inference
TextFooler A Model for Natural Language Attack on Text Classification and Inference This is the source code for the paper: Jin, Di, et al. "Is BERT Re
Code for this paper The Lottery Ticket Hypothesis for Pre-trained BERT Networks.
The Lottery Ticket Hypothesis for Pre-trained BERT Networks Code for this paper The Lottery Ticket Hypothesis for Pre-trained BERT Networks. [NeurIPS
Implementation of Continuous Sparsification, a method for pruning and ticket search in deep networks
Continuous Sparsification Implementation of Continuous Sparsification (CS), a method based on l_0 regularization to find sparse neural networks, propo
Multi-Task Deep Neural Networks for Natural Language Understanding
New Release We released Adversarial training for both LM pre-training/finetuning and f-divergence. Large-scale Adversarial training for LMs: ALUM code
[KBS] Aspect-based sentiment analysis via affective knowledge enhanced graph convolutional networks
#Sentic GCN Introduction This repository was used in our paper: Aspect-Based Sentiment Analysis via Affective Knowledge Enhanced Graph Convolutional N
Code release for "Conditional Adversarial Domain Adaptation" (NIPS 2018)
CDAN Code release for "Conditional Adversarial Domain Adaptation" (NIPS 2018) New version: https://github.com/thuml/Transfer-Learning-Library Dataset
DeepFill v1/v2 with Contextual Attention and Gated Convolution, CVPR 2018, and ICCV 2019 Oral
Generative Image Inpainting An open source framework for generative image inpainting task, with the support of Contextual Attention (CVPR 2018) and Ga
Multi-path load balancing is a method used by most of the real-time network to split the packets into different paths rather than transferring it through a single path
Multipath-Load-Balancing Method of managing incoming traffic by distributing and sharing load fairly among multiple routes from source to destination