2496 Repositories
Python artificial-neural-networks Libraries
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
Few-shot Neural Architecture Search
One-shot Neural Architecture Search uses a single supernet to approximate the performance each architecture. However, this performance estimation is super inaccurate because of co-adaption among operations in supernet.
Official code for UnICORNN (ICML 2021)
UnICORNN (Undamped Independent Controlled Oscillatory RNN) [ICML 2021] This repository contains the implementation to reproduce the numerical experime
TilinGNN: Learning to Tile with Self-Supervised Graph Neural Network (SIGGRAPH 2020)
TilinGNN: Learning to Tile with Self-Supervised Graph Neural Network (SIGGRAPH 2020) About The goal of our research problem is illustrated below: give
PyTorch Implementation of VAENAR-TTS: Variational Auto-Encoder based Non-AutoRegressive Text-to-Speech Synthesis.
VAENAR-TTS - PyTorch Implementation PyTorch Implementation of VAENAR-TTS: Variational Auto-Encoder based Non-AutoRegressive Text-to-Speech Synthesis.
Implementation of the Triangle Multiplicative module, used in Alphafold2 as an efficient way to mix rows or columns of a 2d feature map, as a standalone package for Pytorch
Triangle Multiplicative Module - Pytorch Implementation of the Triangle Multiplicative module, used in Alphafold2 as an efficient way to mix rows or c
A BurpSuite extension to parse 5GC NF OpenAPI 3.0 files to assess 5G core networks
5GC_API_parse Description 5GC API parse is a BurpSuite extension allowing to assess 5G core network functions, by parsing the OpenAPI 3.0 not supporte
NeuralCompression is a Python repository dedicated to research of neural networks that compress data
NeuralCompression is a Python repository dedicated to research of neural networks that compress data. The repository includes tools such as JAX-based entropy coders, image compression models, video compression models, and metrics for image and video evaluation.
Rubrix is a free and open-source tool for exploring and iterating on data for artificial intelligence projects.
Open-source tool for exploring, labeling, and monitoring data for AI projects
A PyTorch Implementation of "Neural Arithmetic Logic Units"
Neural Arithmetic Logic Units [WIP] This is a PyTorch implementation of Neural Arithmetic Logic Units by Andrew Trask, Felix Hill, Scott Reed, Jack Ra
Generative Query Network (GQN) in PyTorch as described in "Neural Scene Representation and Rendering"
Update 2019/06/24: A model trained on 10% of the Shepard-Metzler dataset has been added, the following notebook explains the main features of this mod
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
PyTorch implementation of Wide Residual Networks with 1-bit weights by McDonnell (ICLR 2018)
1-bit Wide ResNet PyTorch implementation of training 1-bit Wide ResNets from this paper: Training wide residual networks for deployment using a single
PyTorch implementation of "Transparency by Design: Closing the Gap Between Performance and Interpretability in Visual Reasoning"
Transparency-by-Design networks (TbD-nets) This repository contains code for replicating the experiments and visualizations from the paper Transparenc
Pervasive Attention: 2D Convolutional Networks for Sequence-to-Sequence Prediction
This is a fork of Fairseq(-py) with implementations of the following models: Pervasive Attention - 2D Convolutional Neural Networks for Sequence-to-Se
Pytorch implementation of the DeepDream computer vision algorithm
deep-dream-in-pytorch Pytorch (https://github.com/pytorch/pytorch) implementation of the deep dream (https://en.wikipedia.org/wiki/DeepDream) computer
PyTorch implementations of algorithms for density estimation
pytorch-flows A PyTorch implementations of Masked Autoregressive Flow and some other invertible transformations from Glow: Generative Flow with Invert
An implementation of DeepMind's Relational Recurrent Neural Networks in PyTorch.
relational-rnn-pytorch An implementation of DeepMind's Relational Recurrent Neural Networks (Santoro et al. 2018) in PyTorch. Relational Memory Core (
PyTorch implementation for Convolutional Networks with Adaptive Inference Graphs
Convolutional Networks with Adaptive Inference Graphs (ConvNet-AIG) This repository contains a PyTorch implementation of the paper Convolutional Netwo
This is the pytorch implementation of the paper - Axiomatic Attribution for Deep Networks.
Integrated Gradients This is the pytorch implementation of "Axiomatic Attribution for Deep Networks". The original tensorflow version could be found h
[ICLR'19] Trellis Networks for Sequence Modeling
TrellisNet for Sequence Modeling This repository contains the experiments done in paper Trellis Networks for Sequence Modeling by Shaojie Bai, J. Zico
Learning to Communicate with Deep Multi-Agent Reinforcement Learning in PyTorch
Learning to Communicate with Deep Multi-Agent Reinforcement Learning This is a PyTorch implementation of the original Lua code release. Overview This
PyTorch implementation of CVPR'18 - Perturbative Neural Networks
This is an attempt to reproduce results in Perturbative Neural Networks paper. See original repo for details.
A PyTorch implementation of the WaveGlow: A Flow-based Generative Network for Speech Synthesis
WaveGlow A PyTorch implementation of the WaveGlow: A Flow-based Generative Network for Speech Synthesis Quick Start: Install requirements: pip install
Code for visualizing the loss landscape of neural nets
Visualizing the Loss Landscape of Neural Nets This repository contains the PyTorch code for the paper Hao Li, Zheng Xu, Gavin Taylor, Christoph Studer
A PyTorch implementation of "Graph Wavelet Neural Network" (ICLR 2019)
Graph Wavelet Neural Network ⠀⠀ A PyTorch implementation of Graph Wavelet Neural Network (ICLR 2019). Abstract We present graph wavelet neural network
A PyTorch Implementation of "Watch Your Step: Learning Node Embeddings via Graph Attention" (NeurIPS 2018).
Attention Walk ⠀⠀ A PyTorch Implementation of Watch Your Step: Learning Node Embeddings via Graph Attention (NIPS 2018). Abstract Graph embedding meth
A PyTorch implementation of "Signed Graph Convolutional Network" (ICDM 2018).
SGCN ⠀ A PyTorch implementation of Signed Graph Convolutional Network (ICDM 2018). Abstract Due to the fact much of today's data can be represented as
A PyTorch implementation of "Graph Classification Using Structural Attention" (KDD 2018).
GAM ⠀⠀ A PyTorch implementation of Graph Classification Using Structural Attention (KDD 2018). Abstract Graph classification is a problem with practic
A Closer Look at Structured Pruning for Neural Network Compression
A Closer Look at Structured Pruning for Neural Network Compression Code used to reproduce experiments in https://arxiv.org/abs/1810.04622. To prune, w
A PyTorch implementation of "SimGNN: A Neural Network Approach to Fast Graph Similarity Computation" (WSDM 2019).
SimGNN ⠀⠀⠀ A PyTorch implementation of SimGNN: A Neural Network Approach to Fast Graph Similarity Computation (WSDM 2019). Abstract Graph similarity s
Implementation of character based convolutional neural network
Character Based CNN This repo contains a PyTorch implementation of a character-level convolutional neural network for text classification. The model a
A certifiable defense against adversarial examples by training neural networks to be provably robust
DiffAI v3 DiffAI is a system for training neural networks to be provably robust and for proving that they are robust. The system was developed for the
A PyTorch implementation of "Predict then Propagate: Graph Neural Networks meet Personalized PageRank" (ICLR 2019).
APPNP ⠀ A PyTorch implementation of Predict then Propagate: Graph Neural Networks meet Personalized PageRank (ICLR 2019). Abstract Neural message pass
An implementation of "MixHop: Higher-Order Graph Convolutional Architectures via Sparsified Neighborhood Mixing" (ICML 2019).
MixHop and N-GCN ⠀ A PyTorch implementation of "MixHop: Higher-Order Graph Convolutional Architectures via Sparsified Neighborhood Mixing" (ICML 2019)
A Pytorch implementation of "Splitter: Learning Node Representations that Capture Multiple Social Contexts" (WWW 2019).
Splitter ⠀⠀ A PyTorch implementation of Splitter: Learning Node Representations that Capture Multiple Social Contexts (WWW 2019). Abstract Recent inte
A PyTorch implementation of "Capsule Graph Neural Network" (ICLR 2019).
CapsGNN ⠀⠀ A PyTorch implementation of Capsule Graph Neural Network (ICLR 2019). Abstract The high-quality node embeddings learned from the Graph Neur
The author's officially unofficial PyTorch BigGAN implementation.
BigGAN-PyTorch The author's officially unofficial PyTorch BigGAN implementation. This repo contains code for 4-8 GPU training of BigGANs from Large Sc
The Hailo Model Zoo includes pre-trained models and a full building and evaluation environment
Hailo Model Zoo The Hailo Model Zoo provides pre-trained models for high-performance deep learning applications. Using the Hailo Model Zoo you can mea
Implementation of: "Exploring Randomly Wired Neural Networks for Image Recognition"
RandWireNN Unofficial PyTorch Implementation of: Exploring Randomly Wired Neural Networks for Image Recognition. Results Validation result on Imagenet
GPU-accelerated PyTorch implementation of Zero-shot User Intent Detection via Capsule Neural Networks
GPU-accelerated PyTorch implementation of Zero-shot User Intent Detection via Capsule Neural Networks This repository implements a capsule model Inten
A PyTorch implementation of "Semi-Supervised Graph Classification: A Hierarchical Graph Perspective" (WWW 2019)
SEAL ⠀⠀⠀ A PyTorch implementation of Semi-Supervised Graph Classification: A Hierarchical Graph Perspective (WWW 2019) Abstract Node classification an
A PyTorch implementation of "Cluster-GCN: An Efficient Algorithm for Training Deep and Large Graph Convolutional Networks" (KDD 2019).
ClusterGCN ⠀⠀ A PyTorch implementation of "Cluster-GCN: An Efficient Algorithm for Training Deep and Large Graph Convolutional Networks" (KDD 2019). A
Implementation of QuickDraw - an online game developed by Google, combined with AirGesture - a simple gesture recognition application
QuickDraw - AirGesture Introduction Here is my python source code for QuickDraw - an online game developed by google, combined with AirGesture - a sim
PyTorch Implementation of VAENAR-TTS: Variational Auto-Encoder based Non-AutoRegressive Text-to-Speech Synthesis.
VAENAR-TTS - PyTorch Implementation PyTorch Implementation of VAENAR-TTS: Variational Auto-Encoder based Non-AutoRegressive Text-to-Speech Synthesis.
Implementation of Invariant Point Attention, used for coordinate refinement in the structure module of Alphafold2, as a standalone Pytorch module
Invariant Point Attention - Pytorch Implementation of Invariant Point Attention as a standalone module, which was used in the structure module of Alph
Moving Object Segmentation in 3D LiDAR Data: A Learning-based Approach Exploiting Sequential Data
LiDAR-MOS: Moving Object Segmentation in 3D LiDAR Data This repo contains the code for our paper: Moving Object Segmentation in 3D LiDAR Data: A Learn
Code for the paper: "On the Bottleneck of Graph Neural Networks and Its Practical Implications"
On the Bottleneck of Graph Neural Networks and its Practical Implications This is the official implementation of the paper: On the Bottleneck of Graph
Code for ViTAS_Vision Transformer Architecture Search
Vision Transformer Architecture Search This repository open source the code for ViTAS: Vision Transformer Architecture Search. ViTAS aims to search fo
SMD-Nets: Stereo Mixture Density Networks
SMD-Nets: Stereo Mixture Density Networks This repository contains a Pytorch implementation of "SMD-Nets: Stereo Mixture Density Networks" (CVPR 2021)
PyTorch implementation of our Adam-NSCL algorithm from our CVPR2021 (oral) paper "Training Networks in Null Space for Continual Learning"
Adam-NSCL This is a PyTorch implementation of Adam-NSCL algorithm for continual learning from our CVPR2021 (oral) paper: Title: Training Networks in N
MicRank is a Learning to Rank neural channel selection framework where a DNN is trained to rank microphone channels.
MicRank: Learning to Rank Microphones for Distant Speech Recognition Application Scenario Many applications nowadays envision the presence of multiple
Pytorch code for ICRA'21 paper: "Hierarchical Cross-Modal Agent for Robotics Vision-and-Language Navigation"
Hierarchical Cross-Modal Agent for Robotics Vision-and-Language Navigation This repository is the pytorch implementation of our paper: Hierarchical Cr
Official implementation of the ICML2021 paper "Elastic Graph Neural Networks"
ElasticGNN This repository includes the official implementation of ElasticGNN in the paper "Elastic Graph Neural Networks" [ICML 2021]. Xiaorui Liu, W
STMTrack: Template-free Visual Tracking with Space-time Memory Networks
STMTrack This is the official implementation of the paper: STMTrack: Template-free Visual Tracking with Space-time Memory Networks. Setup Prepare Anac
efficient neural audio synthesis in the waveform domain
neural waveshaping synthesis real-time neural audio synthesis in the waveform domain paper • website • colab • audio by Ben Hayes, Charalampos Saitis,
Parameterized Explainer for Graph Neural Network
PGExplainer This is a Tensorflow implementation of the paper: Parameterized Explainer for Graph Neural Network https://arxiv.org/abs/2011.04573 NeurIP
ESTDepth: Multi-view Depth Estimation using Epipolar Spatio-Temporal Networks (CVPR 2021)
ESTDepth: Multi-view Depth Estimation using Epipolar Spatio-Temporal Networks (CVPR 2021) Project Page | Video | Paper | Data We present a novel metho
Implementation of "Glancing Transformer for Non-Autoregressive Neural Machine Translation"
GLAT Implementation for the ACL2021 paper "Glancing Transformer for Non-Autoregressive Neural Machine Translation" Requirements Python = 3.7 Pytorch
Implementation of Rotary Embeddings, from the Roformer paper, in Pytorch
Rotary Embeddings - Pytorch A standalone library for adding rotary embeddings to transformers in Pytorch, following its success as relative positional
Official PyTorch Implementation of Convolutional Hough Matching Networks, CVPR 2021 (oral)
Convolutional Hough Matching Networks This is the implementation of the paper "Convolutional Hough Matching Network" by J. Min and M. Cho. Implemented
The MLOps platform for innovators 🚀
DS2.ai is an integrated AI operation solution that supports all stages from custom AI development to deployment. It is an AI-specialized platform service that collects data, builds a training dataset through data labeling, and enables automatic development of artificial intelligence and easy deployment and operation.
Artificial Intelligence search algorithm base on Pacman
Pacman Search Artificial Intelligence search algorithm base on Pacman Source The Pacman Projects by the University of California, Berkeley. Layouts Di
code for "AttentiveNAS Improving Neural Architecture Search via Attentive Sampling"
code for "AttentiveNAS Improving Neural Architecture Search via Attentive Sampling"
A collection of 100 Deep Learning images and visualizations
A collection of Deep Learning images and visualizations. The project has been developed by the AI Summer team and currently contains almost 100 images.
S2-BNN: Bridging the Gap Between Self-Supervised Real and 1-bit Neural Networks via Guided Distribution Calibration (CVPR 2021)
S2-BNN (Self-supervised Binary Neural Networks Using Distillation Loss) This is the official pytorch implementation of our paper: "S2-BNN: Bridging th
[CVPR 2021] A Peek Into the Reasoning of Neural Networks: Interpreting with Structural Visual Concepts
Visual-Reasoning-eXplanation [CVPR 2021 A Peek Into the Reasoning of Neural Networks: Interpreting with Structural Visual Concepts] Project Page | Vid
A collection of 100 Deep Learning images and visualizations
A collection of Deep Learning images and visualizations. The project has been developed by the AI Summer team and currently contains almost 100 images.
Cancer metastasis detection with neural conditional random field (NCRF)
NCRF Prerequisites Data Whole slide images Annotations Patch images Model Training Testing Tissue mask Probability map Tumor localization FROC evaluat
A PyTorch implementation of " EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks."
EfficientNet A PyTorch implementation of EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks. [arxiv] [Official TF Repo] Implemen
Deep Neural Networks Improve Radiologists' Performance in Breast Cancer Screening
Deep Neural Networks Improve Radiologists' Performance in Breast Cancer Screening Introduction This is an implementation of the model used for breast
The Incredible PyTorch: a curated list of tutorials, papers, projects, communities and more relating to PyTorch.
This is a curated list of tutorials, projects, libraries, videos, papers, books and anything related to the incredible PyTorch. Feel free to make a pu
Draw like Bob Ross using the power of Neural Networks (With PyTorch)!
Draw like Bob Ross using the power of Neural Networks! (+ Pytorch) Learning Process Visualization Getting started Install dependecies Requires python3
Amazon Forest Computer Vision: Satellite Image tagging code using PyTorch / Keras with lots of PyTorch tricks
Amazon Forest Computer Vision Satellite Image tagging code using PyTorch / Keras Here is a sample of images we had to work with Source: https://www.ka
Torchreid: Deep learning person re-identification in PyTorch.
Torchreid Torchreid is a library for deep-learning person re-identification, written in PyTorch. It features: multi-GPU training support both image- a
Tensors and neural networks in Haskell
Hasktorch Hasktorch is a library for tensors and neural networks in Haskell. It is an independent open source community project which leverages the co
PyTorch - Python + Nim
Master Release Pytorch - Py + Nim A Nim frontend for pytorch, aiming to be mostly auto-generated and internally using ATen. Because Nim compiles to C+
Kaggle | 9th place single model solution for TGS Salt Identification Challenge
UNet for segmenting salt deposits from seismic images with PyTorch. General We, tugstugi and xuyuan, have participated in the Kaggle competition TGS S
The Medical Detection Toolkit contains 2D + 3D implementations of prevalent object detectors such as Mask R-CNN, Retina Net, Retina U-Net, as well as a training and inference framework focused on dealing with medical images.
The Medical Detection Toolkit contains 2D + 3D implementations of prevalent object detectors such as Mask R-CNN, Retina Net, Retina U-Net, as well as a training and inference framework focused on dealing with medical images.
ocaml-torch provides some ocaml bindings for the PyTorch tensor library.
ocaml-torch provides some ocaml bindings for the PyTorch tensor library. This brings to OCaml NumPy-like tensor computations with GPU acceleration and tape-based automatic differentiation.
Rust bindings for the C++ api of PyTorch.
tch-rs Rust bindings for the C++ api of PyTorch. The goal of the tch crate is to provide some thin wrappers around the C++ PyTorch api (a.k.a. libtorc
🛠 All-in-one web-based IDE specialized for machine learning and data science.
All-in-one web-based development environment for machine learning Getting Started • Features & Screenshots • Support • Report a Bug • FAQ • Known Issu
Geometry-Consistent Neural Shape Representation with Implicit Displacement Fields
Geometry-Consistent Neural Shape Representation with Implicit Displacement Fields [project page][paper][cite] Geometry-Consistent Neural Shape Represe
HyperPose is a library for building high-performance custom pose estimation applications.
HyperPose is a library for building high-performance custom pose estimation applications.
PyTorch implementation of Densely Connected Time Delay Neural Network
Densely Connected Time Delay Neural Network PyTorch implementation of Densely Connected Time Delay Neural Network (D-TDNN) in our paper "Densely Conne
This is the unofficial code of Deep Dual-resolution Networks for Real-time and Accurate Semantic Segmentation of Road Scenes. which achieve state-of-the-art trade-off between accuracy and speed on cityscapes and camvid, without using inference acceleration and extra data
Deep Dual-resolution Networks for Real-time and Accurate Semantic Segmentation of Road Scenes Introduction This is the unofficial code of Deep Dual-re
NU-Wave: A Diffusion Probabilistic Model for Neural Audio Upsampling @ INTERSPEECH 2021 Accepted
NU-Wave — Official PyTorch Implementation NU-Wave: A Diffusion Probabilistic Model for Neural Audio Upsampling Junhyeok Lee, Seungu Han @ MINDsLab Inc
3D Multi-Person Pose Estimation by Integrating Top-Down and Bottom-Up Networks
3D Multi-Person Pose Estimation by Integrating Top-Down and Bottom-Up Networks Introduction This repository contains the code and models for the follo
Neural Logic Inductive Learning
Neural Logic Inductive Learning This is the implementation of the Neural Logic Inductive Learning model (NLIL) proposed in the ICLR 2020 paper: Learn
Code release for DS-NeRF (Depth-supervised Neural Radiance Fields)
Depth-supervised NeRF: Fewer Views and Faster Training for Free Project | Paper | YouTube Pytorch implementation of our method for learning neural rad
Official PyTorch implementation of "Rapid Neural Architecture Search by Learning to Generate Graphs from Datasets" (ICLR 2021)
Rapid Neural Architecture Search by Learning to Generate Graphs from Datasets This is the official PyTorch implementation for the paper Rapid Neural A
Code for paper "Vocabulary Learning via Optimal Transport for Neural Machine Translation"
**Codebase and data are uploaded in progress. ** VOLT(-py) is a vocabulary learning codebase that allows researchers and developers to automaticaly ge
Unofficial implementation of Alias-Free Generative Adversarial Networks. (https://arxiv.org/abs/2106.12423) in PyTorch
alias-free-gan-pytorch Unofficial implementation of Alias-Free Generative Adversarial Networks. (https://arxiv.org/abs/2106.12423) This implementation
Official repository for the paper "Can You Learn an Algorithm? Generalizing from Easy to Hard Problems with Recurrent Networks"
Easy-To-Hard The official repository for the paper "Can You Learn an Algorithm? Generalizing from Easy to Hard Problems with Recurrent Networks". Gett
Official PyTorch implementation of the preprint paper "Stylized Neural Painting", accepted to CVPR 2021.
Official PyTorch implementation of the preprint paper "Stylized Neural Painting", accepted to CVPR 2021.
Integrating Amazon API Gateway private endpoints with on-premises networks
Integrating Amazon API Gateway private endpoints with on-premises networks Read the blog about this application: Integrating Amazon API Gateway privat
Classify bird species based on their songs using SIamese Networks and 1D dilated convolutions.
The goal is to classify different birds species based on their songs/calls. Spectrograms have been extracted from the audio samples and used as features for classification.
PyTorch implementation of Graph Convolutional Networks in Feature Space for Image Deblurring and Super-resolution, IJCNN 2021.
GCResNet PyTorch implementation of Graph Convolutional Networks in Feature Space for Image Deblurring and Super-resolution, IJCNN 2021. The code will
This is my reading list for my PhD in AI, NLP, Deep Learning and more.
This is my reading list for my PhD in AI, NLP, Deep Learning and more.
This is the source code for our ICLR2021 paper: Adaptive Universal Generalized PageRank Graph Neural Network.
GPRGNN This is the source code for our ICLR2021 paper: Adaptive Universal Generalized PageRank Graph Neural Network. Hidden state feature extraction i