1816 Repositories
Python neural-magic-eye Libraries
Neural Message Passing for Computer Vision
Neural Message Passing for Quantum Chemistry Implementation of different models of Neural Networks on graphs as explained in the article proposed by G
Pytorch implementation of "A simple neural network module for relational reasoning" (Relational Networks)
Pytorch implementation of Relational Networks - A simple neural network module for relational reasoning Implemented & tested on Sort-of-CLEVR task. So
Principled Detection of Out-of-Distribution Examples in Neural Networks
ODIN: Out-of-Distribution Detector for Neural Networks This is a PyTorch implementation for detecting out-of-distribution examples in neural networks.
Accelerate Neural Net Training by Progressively Freezing Layers
FreezeOut A simple technique to accelerate neural net training by progressively freezing layers. This repository contains code for the extended abstra
Pytorch implementation of "Forward Thinking: Building and Training Neural Networks One Layer at a Time"
forward-thinking-pytorch Pytorch implementation of Forward Thinking: Building and Training Neural Networks One Layer at a Time Requirements Python 2.7
PyTorch implementation of Neural Combinatorial Optimization with Reinforcement Learning.
neural-combinatorial-rl-pytorch PyTorch implementation of Neural Combinatorial Optimization with Reinforcement Learning. I have implemented the basic
Sequence-to-Sequence learning using PyTorch
Seq2Seq in PyTorch This is a complete suite for training sequence-to-sequence models in PyTorch. It consists of several models and code to both train
PyTorch Implementation of [1611.06440] Pruning Convolutional Neural Networks for Resource Efficient Inference
PyTorch implementation of [1611.06440 Pruning Convolutional Neural Networks for Resource Efficient Inference] This demonstrates pruning a VGG16 based
PyTorch implementation of SampleRNN: An Unconditional End-to-End Neural Audio Generation Model
samplernn-pytorch A PyTorch implementation of SampleRNN: An Unconditional End-to-End Neural Audio Generation Model. It's based on the reference implem
An experimental technique for efficiently exploring neural architectures.
SMASH: One-Shot Model Architecture Search through HyperNetworks An experimental technique for efficiently exploring neural architectures. This reposit
Find target hash collisions for Apple's NeuralHash perceptual hash function.💣
neural-hash-collider Find target hash collisions for Apple's NeuralHash perceptual hash function. For example, starting from a picture of this cat, we
This is the offical website for paper ''Category-consistent deep network learning for accurate vehicle logo recognition''
The Pytorch Implementation of Category-consistent deep network learning for accurate vehicle logo recognition This is the offical website for paper ''
[Preprint] "Bag of Tricks for Training Deeper Graph Neural Networks A Comprehensive Benchmark Study" by Tianlong Chen*, Kaixiong Zhou*, Keyu Duan, Wenqing Zheng, Peihao Wang, Xia Hu, Zhangyang Wang
Bag of Tricks for Training Deeper Graph Neural Networks: A Comprehensive Benchmark Study Codes for [Preprint] Bag of Tricks for Training Deeper Graph
Deep learning for spiking neural networks
A deep learning library for spiking neural networks. Norse aims to exploit the advantages of bio-inspired neural components, which are sparse and even
BARF: Bundle-Adjusting Neural Radiance Fields 🤮 (ICCV 2021 oral)
BARF 🤮 : Bundle-Adjusting Neural Radiance Fields Chen-Hsuan Lin, Wei-Chiu Ma, Antonio Torralba, and Simon Lucey IEEE International Conference on Comp
A PyTorch implementation of "Multi-Scale Contrastive Siamese Networks for Self-Supervised Graph Representation Learning", IJCAI-21
MERIT A PyTorch implementation of our IJCAI-21 paper Multi-Scale Contrastive Siamese Networks for Self-Supervised Graph Representation Learning. Depen
[ICCV'21] NEAT: Neural Attention Fields for End-to-End Autonomous Driving
NEAT: Neural Attention Fields for End-to-End Autonomous Driving Paper | Supplementary | Video | Poster | Blog This repository is for the ICCV 2021 pap
The official repo for CVPR2021——ViPNAS: Efficient Video Pose Estimation via Neural Architecture Search.
ViPNAS: Efficient Video Pose Estimation via Neural Architecture Search [paper] Introduction This is the official implementation of ViPNAS: Efficient V
"Reinforcement Learning for Bandit Neural Machine Translation with Simulated Human Feedback"
This is code repo for our EMNLP 2017 paper "Reinforcement Learning for Bandit Neural Machine Translation with Simulated Human Feedback", which implements the A2C algorithm on top of a neural encoder-decoder model and benchmarks the combination under simulated noisy rewards.
Neural Turing Machines (NTM) - PyTorch Implementation
PyTorch Neural Turing Machine (NTM) PyTorch implementation of Neural Turing Machines (NTM). An NTM is a memory augumented neural network (attached to
yolox_backbone is a deep-learning library and is a collection of YOLOX Backbone models.
YOLOX-Backbone yolox-backbone is a deep-learning library and is a collection of YOLOX backbone models. Install pip install yolox-backbone Load a Pret
An implementation of paper `Real-time Convolutional Neural Networks for Emotion and Gender Classification` with PaddlePaddle.
简介 通过PaddlePaddle框架复现了论文 Real-time Convolutional Neural Networks for Emotion and Gender Classification 中提出的两个模型,分别是SimpleCNN和MiniXception。利用 imdb_crop
The official implementation of the IEEE S&P`22 paper "SoK: How Robust is Deep Neural Network Image Classification Watermarking".
Watermark-Robustness-Toolbox - Official PyTorch Implementation This repository contains the official PyTorch implementation of the following paper to
QTool: A Low-bit Quantization Toolbox for Deep Neural Networks in Computer Vision
This project provides abundant choices of quantization strategies (such as the quantization algorithms, training schedules and empirical tricks) for quantizing the deep neural networks into low-bit counterparts.
Guesslang detects the programming language of a given source code
Detect the programming language of a source code
A PyTorch implementation of the Relational Graph Convolutional Network (RGCN).
Torch-RGCN Torch-RGCN is a PyTorch implementation of the RGCN, originally proposed by Schlichtkrull et al. in Modeling Relational Data with Graph Conv
CM-NAS: Cross-Modality Neural Architecture Search for Visible-Infrared Person Re-Identification (ICCV2021)
CM-NAS Official Pytorch code of paper CM-NAS: Cross-Modality Neural Architecture Search for Visible-Infrared Person Re-Identification in ICCV2021. Vis
Official PyTorch implementation of the paper: Improving Graph Neural Network Expressivity via Subgraph Isomorphism Counting.
Improving Graph Neural Network Expressivity via Subgraph Isomorphism Counting Official PyTorch implementation of the paper: Improving Graph Neural Net
Reference code for the paper CAMS: Color-Aware Multi-Style Transfer.
CAMS: Color-Aware Multi-Style Transfer Mahmoud Afifi1, Abdullah Abuolaim*1, Mostafa Hussien*2, Marcus A. Brubaker1, Michael S. Brown1 1York University
PyTorch implementations for our SIGGRAPH 2021 paper: Editable Free-viewpoint Video Using a Layered Neural Representation.
st-nerf We provide PyTorch implementations for our paper: Editable Free-viewpoint Video Using a Layered Neural Representation SIGGRAPH 2021 Jiakai Zha
Official implementation of Meta-StyleSpeech and StyleSpeech
Meta-StyleSpeech : Multi-Speaker Adaptive Text-to-Speech Generation Dongchan Min, Dong Bok Lee, Eunho Yang, and Sung Ju Hwang This is an official code
A "gym" style toolkit for building lightweight Neural Architecture Search systems
A "gym" style toolkit for building lightweight Neural Architecture Search systems
Ἀνατομή is a PyTorch library to analyze representation of neural networks
Ἀνατομή is a PyTorch library to analyze representation of neural networks
Open source implementation of AceNAS: Learning to Rank Ace Neural Architectures with Weak Supervision of Weight Sharing
AceNAS This repo is the experiment code of AceNAS, and is not considered as an official release. We are working on integrating AceNAS as a built-in st
10th place solution for Google Smartphone Decimeter Challenge at kaggle.
Under refactoring 10th place solution for Google Smartphone Decimeter Challenge at kaggle. Google Smartphone Decimeter Challenge Global Navigation Sat
PyTorch implementation of the Quasi-Recurrent Neural Network - up to 16 times faster than NVIDIA's cuDNN LSTM
Quasi-Recurrent Neural Network (QRNN) for PyTorch Updated to support multi-GPU environments via DataParallel - see the the multigpu_dataparallel.py ex
Learning and Building Convolutional Neural Networks using PyTorch
Image Classification Using Deep Learning Learning and Building Convolutional Neural Networks using PyTorch. Models, selected are based on number of ci
The pytorch implementation of the paper "text-guided neural image inpainting" at MM'2020
TDANet: Text-Guided Neural Image Inpainting, MM'2020 (Oral) MM | ArXiv This repository implements the paper "Text-Guided Neural Image Inpainting" by L
We evaluate our method on different datasets (including ShapeNet, CUB-200-2011, and Pascal3D+) and achieve state-of-the-art results, outperforming all the other supervised and unsupervised methods and 3D representations, all in terms of performance, accuracy, and training time.
An Effective Loss Function for Generating 3D Models from Single 2D Image without Rendering Papers with code | Paper Nikola Zubić Pietro Lio University
PyTorch implementation for paper Neural Marching Cubes.
NMC PyTorch implementation for paper Neural Marching Cubes, Zhiqin Chen, Hao Zhang. Paper | Supplementary Material (to be updated) Citation If you fin
Revisiting, benchmarking, and refining Heterogeneous Graph Neural Networks.
Heterogeneous Graph Benchmark Revisiting, benchmarking, and refining Heterogeneous Graph Neural Networks. Roadmap We organize our repo by task, and on
Neural Scene Graphs for Dynamic Scene (CVPR 2021)
Implementation of Neural Scene Graphs, that optimizes multiple radiance fields to represent different objects and a static scene background. Learned representations can be rendered with novel object compositions and views.
Code accompanying our paper Feature Learning in Infinite-Width Neural Networks
Empirical Experiments in "Feature Learning in Infinite-width Neural Networks" This repo contains code to replicate our experiments (Word2Vec, MAML) in
A DNN inference latency prediction toolkit for accurately modeling and predicting the latency on diverse edge devices.
Note: This is an alpha (preview) version which is still under refining. nn-Meter is a novel and efficient system to accurately predict the inference l
PyTorch Implementation of Daft-Exprt: Robust Prosody Transfer Across Speakers for Expressive Speech Synthesis
Daft-Exprt - PyTorch Implementation PyTorch Implementation of Daft-Exprt: Robust Prosody Transfer Across Speakers for Expressive Speech Synthesis The
PyTorch implementation of Neural Dual Contouring.
NDC PyTorch implementation of Neural Dual Contouring. Citation We are still writing the paper while adding more improvements and applications. If you
Neural network visualization toolkit for tf.keras
Neural network visualization toolkit for tf.keras
Homepage of paper: Paint Transformer: Feed Forward Neural Painting with Stroke Prediction, ICCV 2021.
Paint Transformer: Feed Forward Neural Painting with Stroke Prediction [Paper] [PaddlePaddle Implementation] Homepage of paper: Paint Transformer: Fee
Sign Language Translation with Transformers (COLING'2020, ECCV'20 SLRTP Workshop)
transformer-slt This repository gathers data and code supporting the experiments in the paper Better Sign Language Translation with STMC-Transformer.
TorchDrug is a PyTorch-based machine learning toolbox designed for drug discovery
A powerful and flexible machine learning platform for drug discovery
nn-Meter is a novel and efficient system to accurately predict the inference latency of DNN models on diverse edge devices
A DNN inference latency prediction toolkit for accurately modeling and predicting the latency on diverse edge devices.
neural network based speaker embedder
Content What is deepaudio-speaker? Installation Get Started Model Architecture How to contribute to deepaudio-speaker? Acknowledge What is deepaudio-s
Collective Multi-type Entity Alignment Between Knowledge Graphs (WWW'20)
CG-MuAlign A reference implementation for "Collective Multi-type Entity Alignment Between Knowledge Graphs", published in WWW 2020. If you find our pa
Defending graph neural networks against adversarial attacks (NeurIPS 2020)
GNNGuard: Defending Graph Neural Networks against Adversarial Attacks Authors: Xiang Zhang ([email protected]), Marinka Zitnik (marinka@hms.
NeRD: Neural Reflectance Decomposition from Image Collections
NeRD: Neural Reflectance Decomposition from Image Collections Project Page | Video | Paper | Dataset Implementation for NeRD. A novel method which dec
Official implementation of the paper ``Unifying Nonlocal Blocks for Neural Networks'' (ICCV'21)
Spectral Nonlocal Block Overview Official implementation of the paper: Unifying Nonlocal Blocks for Neural Networks (ICCV'21) Spectral View of Nonloca
Contrastive Learning for Many-to-many Multilingual Neural Machine Translation(mCOLT/mRASP2), ACL2021
Contrastive Learning for Many-to-many Multilingual Neural Machine Translation(mCOLT/mRASP2), ACL2021 The code for training mCOLT/mRASP2, a multilingua
PyTorch implementation of paper: AdaAttN: Revisit Attention Mechanism in Arbitrary Neural Style Transfer, ICCV 2021.
AdaAttN: Revisit Attention Mechanism in Arbitrary Neural Style Transfer [Paper] [PyTorch Implementation] [Paddle Implementation] Overview This reposit
This repository contains the source code for the paper "DONeRF: Towards Real-Time Rendering of Compact Neural Radiance Fields using Depth Oracle Networks",
DONeRF: Towards Real-Time Rendering of Compact Neural Radiance Fields using Depth Oracle Networks Project Page | Video | Presentation | Paper | Data L
Code for the paper "JANUS: Parallel Tempered Genetic Algorithm Guided by Deep Neural Networks for Inverse Molecular Design"
JANUS: Parallel Tempered Genetic Algorithm Guided by Deep Neural Networks for Inverse Molecular Design This repository contains code for the paper: JA
An implementation for Neural Architecture Search with Random Labels (CVPR 2021 poster) on Pytorch.
Neural Architecture Search with Random Labels(RLNAS) Introduction This project provides an implementation for Neural Architecture Search with Random L
FPGA: Fast Patch-Free Global Learning Framework for Fully End-to-End Hyperspectral Image Classification
FPGA & FreeNet Fast Patch-Free Global Learning Framework for Fully End-to-End Hyperspectral Image Classification by Zhuo Zheng, Yanfei Zhong, Ailong M
Official implementation of NPMs: Neural Parametric Models for 3D Deformable Shapes - ICCV 2021
NPMs: Neural Parametric Models Project Page | Paper | ArXiv | Video NPMs: Neural Parametric Models for 3D Deformable Shapes Pablo Palafox, Aljaz Bozic
This is project is the implementation of the DeepShift: Towards Multiplication-Less Neural Networks paper
DeepShift This is project is the implementation of the DeepShift: Towards Multiplication-Less Neural Networks paper, that aims to replace multiplicati
Source code and Dataset creation for the paper "Neural Symbolic Regression That Scales"
NeuralSymbolicRegressionThatScales Pytorch implementation and pretrained models for the paper "Neural Symbolic Regression That Scales", presented at I
A library for uncertainty representation and training in neural networks.
Epistemic Neural Networks A library for uncertainty representation and training in neural networks. Introduction Many applications in deep learning re
Differentiable Neural Computers, Sparse Access Memory and Sparse Differentiable Neural Computers, for Pytorch
Differentiable Neural Computers and family, for Pytorch Includes: Differentiable Neural Computers (DNC) Sparse Access Memory (SAM) Sparse Differentiab
PyTorch implementations of neural network models for keyword spotting
Honk: CNNs for Keyword Spotting Honk is a PyTorch reimplementation of Google's TensorFlow convolutional neural networks for keyword spotting, which ac
Code for ICCV 2021 paper "Distilling Holistic Knowledge with Graph Neural Networks"
HKD Code for ICCV 2021 paper "Distilling Holistic Knowledge with Graph Neural Networks" cifia-100 result The implementation of compared methods are ba
Callable PyTrees and filtered JIT/grad transformations = neural networks in JAX.
Equinox Callable PyTrees and filtered JIT/grad transformations = neural networks in JAX Equinox brings more power to your model building in JAX. Repr
Unofficial PyTorch Implementation of UnivNet: A Neural Vocoder with Multi-Resolution Spectrogram Discriminators for High-Fidelity Waveform Generation
UnivNet UnivNet: A Neural Vocoder with Multi-Resolution Spectrogram Discriminators for High-Fidelity Waveform Generation This is an unofficial PyTorch
This project is a sample demo of Arxiv search related to AI/ML Papers built using Streamlit, sentence-transformers and Faiss.
This project is a sample demo of Arxiv search related to AI/ML Papers built using Streamlit, sentence-transformers and Faiss.
Image Deblurring using Generative Adversarial Networks
DeblurGAN arXiv Paper Version Pytorch implementation of the paper DeblurGAN: Blind Motion Deblurring Using Conditional Adversarial Networks. Our netwo
Image restoration with neural networks but without learning.
Warning! The optimization may not converge on some GPUs. We've personally experienced issues on Tesla V100 and P40 GPUs. When running the code, make s
Deep Learning Head Pose Estimation using PyTorch.
Hopenet is an accurate and easy to use head pose estimation network. Models have been trained on the 300W-LP dataset and have been tested on real data with good qualitative performance.
Synthesizing and manipulating 2048x1024 images with conditional GANs
pix2pixHD Project | Youtube | Paper Pytorch implementation of our method for high-resolution (e.g. 2048x1024) photorealistic image-to-image translatio
Neural Module Network for VQA in Pytorch
Neural Module Network (NMN) for VQA in Pytorch Note: This is NOT an official repository for Neural Module Networks. NMN is a network that is assembled
PyTorch implementation of the YOLO (You Only Look Once) v2
PyTorch implementation of the YOLO (You Only Look Once) v2 The YOLOv2 is one of the most popular one-stage object detector. This project adopts PyTorc
Image reconstruction done with untrained neural networks.
PyTorch Deep Image Prior An implementation of image reconstruction methods from Deep Image Prior (Ulyanov et al., 2017) in PyTorch. The point of the p
A PyTorch Implementation of Gated Graph Sequence Neural Networks (GGNN)
A PyTorch Implementation of GGNN This is a PyTorch implementation of the Gated Graph Sequence Neural Networks (GGNN) as described in the paper Gated G
This's an implementation of deepmind Visual Interaction Networks paper using pytorch
Visual-Interaction-Networks An implementation of Deepmind visual interaction networks in Pytorch. Introduction For the purpose of understanding the ch
Photographic Image Synthesis with Cascaded Refinement Networks - Pytorch Implementation
Photographic Image Synthesis with Cascaded Refinement Networks-Pytorch (https://arxiv.org/abs/1707.09405) This is a Pytorch implementation of cascaded
PyTorch implementation of "Efficient Neural Architecture Search via Parameters Sharing"
Efficient Neural Architecture Search (ENAS) in PyTorch PyTorch implementation of Efficient Neural Architecture Search via Parameters Sharing. ENAS red
A PyTorch Implementation of Neural IMage Assessment
NIMA: Neural IMage Assessment This is a PyTorch implementation of the paper NIMA: Neural IMage Assessment (accepted at IEEE Transactions on Image Proc
Proximal Backpropagation - a neural network training algorithm that takes implicit instead of explicit gradient steps
Proximal Backpropagation Proximal Backpropagation (ProxProp) is a neural network training algorithm that takes implicit instead of explicit gradient s
NIMA: Neural IMage Assessment
PyTorch NIMA: Neural IMage Assessment PyTorch implementation of Neural IMage Assessment by Hossein Talebi and Peyman Milanfar. You can learn more from
PyTorch Implementation of "Non-Autoregressive Neural Machine Translation"
Non-Autoregressive Transformer Code release for Non-Autoregressive Neural Machine Translation by Jiatao Gu, James Bradbury, Caiming Xiong, Victor O.K.
Pytorch implementation of the Variational Recurrent Neural Network (VRNN).
VariationalRecurrentNeuralNetwork Pytorch implementation of the Variational RNN (VRNN), from A Recurrent Latent Variable Model for Sequential Data. Th
PyTorch implementation of convolutional neural networks-based text-to-speech synthesis models
Deepvoice3_pytorch PyTorch implementation of convolutional networks-based text-to-speech synthesis models: arXiv:1710.07654: Deep Voice 3: Scaling Tex
🐥A PyTorch implementation of OpenAI's finetuned transformer language model with a script to import the weights pre-trained by OpenAI
PyTorch implementation of OpenAI's Finetuned Transformer Language Model This is a PyTorch implementation of the TensorFlow code provided with OpenAI's
PyTorch implementation for MINE: Continuous-Depth MPI with Neural Radiance Fields
MINE: Continuous-Depth MPI with Neural Radiance Fields Project Page | Video PyTorch implementation for our ICCV 2021 paper. MINE: Towards Continuous D
GNN4Traffic - This is the repository for the collection of Graph Neural Network for Traffic Forecasting
GNN4Traffic - This is the repository for the collection of Graph Neural Network for Traffic Forecasting
Fast and scalable uncertainty quantification for neural molecular property prediction, accelerated optimization, and guided virtual screening.
Evidential Deep Learning for Guided Molecular Property Prediction and Discovery Ava Soleimany*, Alexander Amini*, Samuel Goldman*, Daniela Rus, Sangee
Portal is the fastest way to load and visualize your deep neural networks on images and videos 🔮
Portal is the fastest way to load and visualize your deep neural networks on images and videos 🔮
Stochastic Downsampling for Cost-Adjustable Inference and Improved Regularization in Convolutional Networks
Stochastic Downsampling for Cost-Adjustable Inference and Improved Regularization in Convolutional Networks (SDPoint) This repository contains the cod
PyTorch implementation of PNASNet-5 on ImageNet
PNASNet.pytorch PyTorch implementation of PNASNet-5. Specifically, PyTorch code from this repository is adapted to completely match both my implemetat
Neural implicit reconstruction experiments for the Vector Neuron paper
Neural Implicit Reconstruction with Vector Neurons This repository contains code for the neural implicit reconstruction experiments in the paper Vecto
IDRLnet, a Python toolbox for modeling and solving problems through Physics-Informed Neural Network (PINN) systematically.
IDRLnet IDRLnet is a machine learning library on top of PyTorch. Use IDRLnet if you need a machine learning library that solves both forward and inver
Neural Fixed-Point Acceleration for Convex Optimization
Licensing The majority of neural-scs is licensed under the CC BY-NC 4.0 License, however, portions of the project are available under separate license
Learned Token Pruning for Transformers
LTP: Learned Token Pruning for Transformers Check our paper for more details. Installation We follow the same installation procedure as the original H