4188 Repositories
Python pytorch-generative-adversarial-networks Libraries
The codebase for our paper "Generative Occupancy Fields for 3D Surface-Aware Image Synthesis" (NeurIPS 2021)
Generative Occupancy Fields for 3D Surface-Aware Image Synthesis (NeurIPS 2021) Project Page | Paper Xudong Xu, Xingang Pan, Dahua Lin and Bo Dai GOF
Official code for "Maximum Likelihood Training of Score-Based Diffusion Models", NeurIPS 2021 (spotlight)
Maximum Likelihood Training of Score-Based Diffusion Models This repo contains the official implementation for the paper Maximum Likelihood Training o
FLSim a flexible, standalone library written in PyTorch that simulates FL settings with a minimal, easy-to-use API
Federated Learning Simulator (FLSim) is a flexible, standalone core library that simulates FL settings with a minimal, easy-to-use API. FLSim is domain-agnostic and accommodates many use cases such as vision and text.
Codes for CyGen, the novel generative modeling framework proposed in "On the Generative Utility of Cyclic Conditionals" (NeurIPS-21)
On the Generative Utility of Cyclic Conditionals This repository is the official implementation of "On the Generative Utility of Cyclic Conditionals"
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
Re-implememtation of MAE (Masked Autoencoders Are Scalable Vision Learners) using PyTorch.
mae-repo PyTorch re-implememtation of "masked autoencoders are scalable vision learners". In this repo, it heavily borrows codes from codebase https:/
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
2D Human Pose estimation using transformers. Implementation in Pytorch
PE-former: Pose Estimation Transformer Vision transformer architectures perform very well for image classification tasks. Efforts to solve more challe
Riemann Noise Injection With PyTorch
Riemann Noise Injection - PyTorch A module for modeling GAN noise injection based on Riemann geometry, as described in Ruili Feng, Deli Zhao, and Zhen
Continuously update some NLP practice based on different tasks.
NLP_practice We will continuously update some NLP practice based on different tasks. prerequisites Software pytorch = 1.10 torchtext = 0.11.0 sklear
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"
SOLO and SOLOv2 for instance segmentation, ECCV 2020 & NeurIPS 2020.
SOLO: Segmenting Objects by Locations This project hosts the code for implementing the SOLO algorithms for instance segmentation. SOLO: Segmenting Obj
R3Det based on mmdet 2.19.0
R3Det: Refined Single-Stage Detector with Feature Refinement for Rotating Object Installation # install mmdetection first if you haven't installed it
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
Unofficial PyTorch implementation of TokenLearner by Google AI
tokenlearner-pytorch Unofficial PyTorch implementation of TokenLearner by Ryoo et al. from Google AI (abs, pdf) Installation You can install TokenLear
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
Implementation of "Large Steps in Inverse Rendering of Geometry"
Large Steps in Inverse Rendering of Geometry ACM Transactions on Graphics (Proceedings of SIGGRAPH Asia), December 2021. Baptiste Nicolet · Alec Jacob
[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
K-PLUG: Knowledge-injected Pre-trained Language Model for Natural Language Understanding and Generation in E-Commerce (EMNLP Founding 2021)
Introduction K-PLUG: Knowledge-injected Pre-trained Language Model for Natural Language Understanding and Generation in E-Commerce. Installation PyTor
PyTorch implementation of our paper: "Artistic Style Transfer with Internal-external Learning and Contrastive Learning"
Artistic Style Transfer with Internal-external Learning and Contrastive Learning This is the official PyTorch implementation of our paper: "Artistic S
NeurIPS'19: Meta-Weight-Net: Learning an Explicit Mapping For Sample Weighting (Pytorch implementation for noisy labels).
Meta-Weight-Net NeurIPS'19: Meta-Weight-Net: Learning an Explicit Mapping For Sample Weighting (Official Pytorch implementation for noisy labels). The
[NeurIPS 2020] This project provides a strong single-stage baseline for Long-Tailed Classification, Detection, and Instance Segmentation (LVIS).
A Strong Single-Stage Baseline for Long-Tailed Problems This project provides a strong single-stage baseline for Long-Tailed Classification (under Ima
[ICLR 2021 Spotlight] Pytorch implementation for "Long-tailed Recognition by Routing Diverse Distribution-Aware Experts."
RIDE: Long-tailed Recognition by Routing Diverse Distribution-Aware Experts. by Xudong Wang, Long Lian, Zhongqi Miao, Ziwei Liu and Stella X. Yu at UC
Official PyTorch implementation of RIO
Image-Level or Object-Level? A Tale of Two Resampling Strategies for Long-Tailed Detection Figure 1: Our proposed Resampling at image-level and obect-
A high-performance Python-based I/O system for large (and small) deep learning problems, with strong support for PyTorch.
WebDataset WebDataset is a PyTorch Dataset (IterableDataset) implementation providing efficient access to datasets stored in POSIX tar archives and us
Torchrecipes provides a set of reproduci-able, re-usable, ready-to-run RECIPES for training different types of models, across multiple domains, on PyTorch Lightning.
Recipes are a standard, well supported set of blueprints for machine learning engineers to rapidly train models using the latest research techniques without significant engineering overhead.Specifically, recipes aims to provide- Consistent access to pre-trained SOTA models ready for production- Reference implementations for SOTA research reproducibility, and infrastructure to guarantee correctness, efficiency, and interoperability.
State-of-the-art NLP through transformer models in a modular design and consistent APIs.
Trapper (Transformers wRAPPER) Trapper is an NLP library that aims to make it easier to train transformer based models on downstream tasks. It wraps h
Pytorch Implementations of large number classical backbone CNNs, data enhancement, torch loss, attention, visualization and some common algorithms.
Torch-template-for-deep-learning Pytorch implementations of some **classical backbone CNNs, data enhancement, torch loss, attention, visualization and
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 PyTorch Implementation of GAN-Supervised Dense Visual Alignment
GAN-Supervised Dense Visual Alignment — Official PyTorch Implementation Paper | Project Page | Video This repo contains training, evaluation and visua
A simple rest api that classifies pneumonia infection weather it is Normal, Pneumonia Virus or Pneumonia Bacteria from a chest-x-ray image.
This is a simple rest api that classifies pneumonia infection weather it is Normal, Pneumonia Virus or Pneumonia Bacteria from a chest-x-ray image.
Independent and minimal implementations of some reinforcement learning algorithms using PyTorch (including PPO, A3C, A2C, ...).
PyTorch RL Minimal Implementations There are implementations of some reinforcement learning algorithms, whose characteristics are as follow: Less pack
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
CALVIN - A benchmark for Language-Conditioned Policy Learning for Long-Horizon Robot Manipulation Tasks
CALVIN CALVIN - A benchmark for Language-Conditioned Policy Learning for Long-Horizon Robot Manipulation Tasks Oier Mees, Lukas Hermann, Erick Rosete,
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,
Pytorch code for paper "Image Compressed Sensing Using Non-local Neural Network" TMM 2021.
NL-CSNet-Pytorch Pytorch code for paper "Image Compressed Sensing Using Non-local Neural Network" TMM 2021. Note: this repo only shows the strategy of
This is an official PyTorch implementation of "Contrastive Learning from Extremely Augmented Skeleton Sequences for Self-supervised Action Recognition" in AAAI2022.
AimCLR This is an official PyTorch implementation of "Contrastive Learning from Extremely Augmented Skeleton Sequences for Self-supervised Action Reco
Dilated Convolution with Learnable Spacings PyTorch
Dilated-Convolution-with-Learnable-Spacings-PyTorch Ismail Khalfaoui Hassani Dilated Convolution with Learnable Spacings (abbreviated to DCLS) is a no
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
This is a re-implementation of TransGAN: Two Pure Transformers Can Make One Strong GAN (CVPR 2021) in PyTorch.
TransGAN: Two Transformers Can Make One Strong GAN [YouTube Video] Paper Authors: Yifan Jiang, Shiyu Chang, Zhangyang Wang CVPR 2021 This is re-implem
Faster RCNN pytorch windows
Faster-RCNN-pytorch-windows Faster RCNN implementation with pytorch for windows Open cmd, compile this comands: cd lib python setup.py build develop T
PyTorch implementation for OCT-GAN Neural ODE-based Conditional Tabular GANs (WWW 2021)
OCT-GAN: Neural ODE-based Conditional Tabular GANs (OCT-GAN) Code for reproducing the experiments in the paper: Jayoung Kim*, Jinsung Jeon*, Jaehoon L
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
Data pipelines for both TensorFlow and PyTorch!
rapidnlp-datasets Data pipelines for both TensorFlow and PyTorch ! If you want to load public datasets, try: tensorflow/datasets huggingface/datasets
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
Pytorch implementation for A-NeRF: Articulated Neural Radiance Fields for Learning Human Shape, Appearance, and Pose
A-NeRF: Articulated Neural Radiance Fields for Learning Human Shape, Appearance, and Pose Paper | Website | Data A-NeRF: Articulated Neural Radiance F
Official Pytorch Implementation of Relational Self-Attention: What's Missing in Attention for Video Understanding
Relational Self-Attention: What's Missing in Attention for Video Understanding This repository is the official implementation of "Relational Self-Atte
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
Pytorch code for paper "Image Compressed Sensing Using Non-local Neural Network" TMM 2021.
NL-CSNet-Pytorch Pytorch code for paper "Image Compressed Sensing Using Non-local Neural Network" TMM 2021. Note: this repo only shows the strategy of
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
PyTorch implementation of the paper Dynamic Token Normalization Improves Vision Transfromers.
Dynamic Token Normalization Improves Vision Transformers This is the PyTorch implementation of the paper Dynamic Token Normalization Improves Vision T
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
PyTorch implementation of probabilistic deep forecast applied to air quality.
Probabilistic Deep Forecast PyTorch implementation of a paper, titled: Probabilistic Deep Learning to Quantify Uncertainty in Air Quality Forecasting
PyTorch implementation of hand mesh reconstruction described in CMR and MobRecon.
Hand Mesh Reconstruction Introduction This repo is the PyTorch implementation of hand mesh reconstruction described in CMR and MobRecon. Update 2021-1
Implementation of N-Grammer, augmenting Transformers with latent n-grams, in Pytorch
N-Grammer - Pytorch Implementation of N-Grammer, augmenting Transformers with latent n-grams, in Pytorch Install $ pip install n-grammer-pytorch Usage
A simple library that implements CLIP guided loss in PyTorch.
pytorch_clip_guided_loss: Pytorch implementation of the CLIP guided loss for Text-To-Image, Image-To-Image, or Image-To-Text generation. A simple libr
The code for 'Deep Residual Fourier Transformation for Single Image Deblurring'
Deep Residual Fourier Transformation for Single Image Deblurring Xintian Mao, Yiming Liu, Wei Shen, Qingli Li and Yan Wang News 2021.12.5 Release Deep
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
PyTorch implementation of Grokking: Generalization Beyond Overfitting on Small Algorithmic Datasets
Simple PyTorch Implementation of "Grokking" Implementation of Grokking: Generalization Beyond Overfitting on Small Algorithmic Datasets Usage Running
Official pytorch code for SSAT: A Symmetric Semantic-Aware Transformer Network for Makeup Transfer and Removal
SSAT: A Symmetric Semantic-Aware Transformer Network for Makeup Transfer and Removal This is the official pytorch code for SSAT: A Symmetric Semantic-
Rewrite ultralytics/yolov5 v6.0 opencv inference code based on numpy, no need to rely on pytorch
Rewrite ultralytics/yolov5 v6.0 opencv inference code based on numpy, no need to rely on pytorch; pre-processing and post-processing using numpy instead of pytroch.
Convert ONNX model graph to Keras model format.
Convert ONNX model graph to Keras model format.
PyTorch Implementation of Daft-Exprt: Robust Prosody Transfer Across Speakers for Expressive Speech Synthesis
PyTorch Implementation of Daft-Exprt: Robust Prosody Transfer Across Speakers for Expressive Speech Synthesis
FedTorch is an open-source Python package for distributed and federated training of machine learning models using PyTorch distributed API
FedTorch is a generic repository for benchmarking different federated and distributed learning algorithms using PyTorch Distributed API.