2625 Repositories
Python deep-hist Libraries
code for generating data set ES-ImageNet with corresponding training code
es-imagenet-master code for generating data set ES-ImageNet with corresponding training code dataset generator some codes of ODG algorithm The variabl
EgoNN: Egocentric Neural Network for Point Cloud Based 6DoF Relocalization at the City Scale
EgonNN: Egocentric Neural Network for Point Cloud Based 6DoF Relocalization at the City Scale Paper: EgoNN: Egocentric Neural Network for Point Cloud
A Context-aware Visual Attention-based training pipeline for Object Detection from a Webpage screenshot!
CoVA: Context-aware Visual Attention for Webpage Information Extraction Abstract Webpage information extraction (WIE) is an important step to create k
The official repository for "Revealing unforeseen diagnostic image features with deep learning by detecting cardiovascular diseases from apical four-chamber ultrasounds"
Revealing unforeseen diagnostic image features with deep learning by detecting cardiovascular diseases from apical four-chamber ultrasounds The why Im
Implementation of PersonaGPT Dialog Model
PersonaGPT An open-domain conversational agent with many personalities PersonaGPT is an open-domain conversational agent cpable of decoding personaliz
Hierarchical probabilistic 3D U-Net, with attention mechanisms (βππ΅π΅π¦π―π΅πͺπ°π― π-ππ¦π΅, ππππ¦π΄ππ¦π΅) and a nested decoder structure with deep supervision (βπππ¦π΅++).
Hierarchical probabilistic 3D U-Net, with attention mechanisms (βππ΅π΅π¦π―π΅πͺπ°π― π-ππ¦π΅, ππππ¦π΄ππ¦π΅) and a nested decoder structure with deep supervision (βπππ¦π΅++). Built in TensorFlow 2.5. Configured for voxel-level clinically significant prostate cancer detection in multi-channel 3D bpMRI scans.
Assessing the Influence of Models on the Performance of Reinforcement Learning Algorithms applied on Continuous Control Tasks
Assessing the Influence of Models on the Performance of Reinforcement Learning Algorithms applied on Continuous Control Tasks This is the master thesi
CUP-DNN is a deep neural network model used to predict tissues of origin for cancers of unknown of primary.
CUP-DNN CUP-DNN is a deep neural network model used to predict tissues of origin for cancers of unknown of primary. The model was trained on the expre
Use Jax functions in Pytorch with DLPack
Use Jax functions in Pytorch with DLPack
Implementation of ConvMixer-Patches Are All You Need? in TensorFlow and Keras
Patches Are All You Need? - ConvMixer ConvMixer, an extremely simple model that is similar in spirit to the ViT and the even-more-basic MLP-Mixer in t
This repository is the code of the paper "Sparse Spatial Transformers for Few-Shot Learning".
π Sparse Spatial Transformers for Few-Shot Learning This code implements the Sparse Spatial Transformers for Few-Shot Learning(SSFormers). Our code i
A PyTorch-based library for fast prototyping and sharing of deep neural network models.
A PyTorch-based library for fast prototyping and sharing of deep neural network models.
PyTorch Implementation of ByteDance's Cross-speaker Emotion Transfer Based on Speaker Condition Layer Normalization and Semi-Supervised Training in Text-To-Speech
Cross-Speaker-Emotion-Transfer - PyTorch Implementation PyTorch Implementation of ByteDance's Cross-speaker Emotion Transfer Based on Speaker Conditio
pytorch implementation of the ICCV'21 paper "MVTN: Multi-View Transformation Network for 3D Shape Recognition"
MVTN: Multi-View Transformation Network for 3D Shape Recognition (ICCV 2021) By Abdullah Hamdi, Silvio Giancola, Bernard Ghanem Paper | Video | Tutori
Implementation of Enformer, Deepmind's attention network for predicting gene expression, in Pytorch
Enformer - Pytorch (wip) Implementation of Enformer, Deepmind's attention network for predicting gene expression, in Pytorch. The original tensorflow
Deep Networks with Recurrent Layer Aggregation
RLA-Net: Recurrent Layer Aggregation Recurrence along Depth: Deep Networks with Recurrent Layer Aggregation This is an implementation of RLA-Net (acce
SEJE is a prototype for the paper Learning Text-Image Joint Embedding for Efficient Cross-Modal Retrieval with Deep Feature Engineering.
SEJE is a prototype for the paper Learning Text-Image Joint Embedding for Efficient Cross-Modal Retrieval with Deep Feature Engineering. Contents Inst
Official implementation of "Learning Proposals for Practical Energy-Based Regression", 2021.
ebms_proposals Official implementation (PyTorch) of the paper: Learning Proposals for Practical Energy-Based Regression, 2021 [arXiv] [project]. Fredr
PyTorch framework for Deep Learning research and development.
Accelerated DL & RL PyTorch framework for Deep Learning research and development. It was developed with a focus on reproducibility, fast experimentati
PyTorch implementation of Convolutional Neural Fabrics http://arxiv.org/abs/1606.02492
PyTorch implementation of Convolutional Neural Fabrics arxiv:1606.02492 There are some minor differences: The raw image is first convolved, to obtain
Very Deep Convolutional Networks for Large-Scale Image Recognition
pytorch-vgg Some scripts to convert the VGG-16 and VGG-19 models [1] from Caffe to PyTorch. The converted models can be used with the PyTorch model zo
an implementation of Video Frame Interpolation via Adaptive Separable Convolution using PyTorch
This work has now been superseded by: https://github.com/sniklaus/revisiting-sepconv sepconv-slomo This is a reference implementation of Video Frame I
Training Very Deep Neural Networks Without Skip-Connections
DiracNets v2 update (January 2018): The code was updated for DiracNets-v2 in which we removed NCReLU by adding per-channel a and b multipliers without
PyTorch code for the "Deep Neural Networks with Box Convolutions" paper
Box Convolution Layer for ConvNets Single-box-conv network (from `examples/mnist.py`) learns patterns on MNIST What This Is This is a PyTorch implemen
PyTorch implementation of Octave Convolution with pre-trained Oct-ResNet and Oct-MobileNet models
octconv.pytorch PyTorch implementation of Octave Convolution in Drop an Octave: Reducing Spatial Redundancy in Convolutional Neural Networks with Octa
Convolutional Neural Network for 3D meshes in PyTorch
MeshCNN in PyTorch SIGGRAPH 2019 [Paper] [Project Page] MeshCNN is a general-purpose deep neural network for 3D triangular meshes, which can be used f
Deep Reinforcement Learning for Multiplayer Online Battle Arena
MOBA_RL Deep Reinforcement Learning for Multiplayer Online Battle Arena Prerequisite Python 3 gym-derk Tensorflow 2.4.1 Dotaservice of TimZaman Seed R
Adaptive, interpretable wavelets across domains (NeurIPS 2021)
Adaptive wavelets Wavelets which adapt given data (and optionally a pre-trained model). This yields models which are faster, more compressible, and mo
PyTorch Implementation of Unsupervised Depth Completion with Calibrated Backprojection Layers (ORAL, ICCV 2021)
Unsupervised Depth Completion with Calibrated Backprojection Layers PyTorch implementation of Unsupervised Depth Completion with Calibrated Backprojec
In this project, we create and implement a deep learning library from scratch.
ARA In this project, we create and implement a deep learning library from scratch. Table of Contents Deep Leaning Library Table of Contents About The
This project helps to colorize grayscale images using multiple exemplars.
Multiple Exemplar-based Deep Colorization (Pytorch Implementation) Pretrained Model [Jitendra Chautharia](IIT Jodhpur)1,3, Prerequisites Python 3.6+ N
PyTorch Implementation of Unsupervised Depth Completion with Calibrated Backprojection Layers (ORAL, ICCV 2021)
PyTorch Implementation of Unsupervised Depth Completion with Calibrated Backprojection Layers (ORAL, ICCV 2021)
Kaggle: Cell Instance Segmentation
Kaggle: Cell Instance Segmentation The goal of this challenge is to detect cells in microscope images. with simple view on how many cels have been ann
Facilitates implementing deep neural-network backbones, data augmentations
Introduction Nowadays, the training of Deep Learning models is fragmented and unified. When AI engineers face up with one specific task, the common wa
[NeurIPS2021] Exploring Architectural Ingredients of Adversarially Robust Deep Neural Networks
Exploring Architectural Ingredients of Adversarially Robust Deep Neural Networks Code for NeurIPS 2021 Paper "Exploring Architectural Ingredients of A
A project that uses optical flow and machine learning to detect aimhacking in video clips.
waldo-anticheat A project that aims to use optical flow and machine learning to visually detect cheating or hacking in video clips from fps games. Che
Official and maintained implementation of the paper "OSS-Net: Memory Efficient High Resolution Semantic Segmentation of 3D Medical Data" [BMVC 2021].
OSS-Net: Memory Efficient High Resolution Semantic Segmentation of 3D Medical Data Christoph Reich, Tim Prangemeier, Γzdemir Cetin & Heinz Koeppl | Pr
Huggingface transformers for discord
disformers Huggingface transformers for discord base source butyr/huggingface-transformer-chatbots install pip install -U disformers example see examp
Official and maintained implementation of the paper "OSS-Net: Memory Efficient High Resolution Semantic Segmentation of 3D Medical Data" [BMVC 2021].
OSS-Net: Memory Efficient High Resolution Semantic Segmentation of 3D Medical Data Christoph Reich, Tim Prangemeier, Γzdemir Cetin & Heinz Koeppl | Pr
Optimal Adaptive Allocation using Deep Reinforcement Learning in a Dose-Response Study
Optimal Adaptive Allocation using Deep Reinforcement Learning in a Dose-Response Study Supplementary Materials for Kentaro Matsuura, Junya Honda, Imad
This is an official source code for implementation on Extensive Deep Temporal Point Process
Extensive Deep Temporal Point Process This is an official source code for implementation on Extensive Deep Temporal Point Process, which is composed o
A new mini-batch framework for optimal transport in deep generative models, deep domain adaptation, approximate Bayesian computation, color transfer, and gradient flow.
BoMb-OT Python3 implementation of the papers On Transportation of Mini-batches: A Hierarchical Approach and Improving Mini-batch Optimal Transport via
Official implementation of CVPR2020 paper "Deep Generative Model for Robust Imbalance Classification"
Deep Generative Model for Robust Imbalance Classification Deep Generative Model for Robust Imbalance Classification Xinyue Wang, Yilin Lyu, Liping Jin
A Python/Pytorch app for easily synthesising human voices
Voice Cloning App A Python/Pytorch app for easily synthesising human voices Documentation Discord Server Video guide Voice Sharing Hub FAQ's System Re
Hippocampal segmentation using the UNet network for each axis
Hipposeg Hippocampal segmentation using the UNet network for each axis, inspired by https://github.com/MICLab-Unicamp/e2dhipseg Red: False Positive Gr
Blue Brain text mining toolbox for semantic search and structured information extraction
Blue Brain Search Source Code DOI Data & Models DOI Documentation Latest Release Python Versions License Build Status Static Typing Code Style Securit
A bare-bones Python library for quality diversity optimization.
pyribs Website Source PyPI Conda CI/CD Docs Docs Status Twitter pyribs.org GitHub docs.pyribs.org A bare-bones Python library for quality diversity op
A Word Level Transformer layer based on PyTorch and π€ Transformers.
Transformer Embedder A Word Level Transformer layer based on PyTorch and π€ Transformers. How to use Install the library from PyPI: pip install transf
Urban mobility simulations with Python3, RLlib (Deep Reinforcement Learning) and Mesa (Agent-based modeling)
Deep Reinforcement Learning for Smart Cities Documentation RLlib: https://docs.ray.io/en/master/rllib.html Mesa: https://mesa.readthedocs.io/en/stable
A library for preparing, training, and evaluating scalable deep learning hybrid recommender systems using PyTorch.
collie Collie is a library for preparing, training, and evaluating implicit deep learning hybrid recommender systems, named after the Border Collie do
A library for Deep Learning Implementations and utils
deeply A Deep Learning library Table of Contents Features Quick Start Usage License Features Python 2.7+ and Python 3.4+ compatible. Quick Start $ pip
automated systems to assist guarding corona Virus precautions for Closed Rooms (e.g. Halls, offices, etc..)
Automatic-precautionary-guard automated systems to assist guarding corona Virus precautions for Closed Rooms (e.g. Halls, offices, etc..) what is this
Website which uses Deep Learning to generate horror stories.
Creepypasta - Text Generator Website which uses Deep Learning to generate horror stories. View Demo Β· View Website Repo Β· Report Bug Β· Request Feature
a reimplementation of Holistically-Nested Edge Detection in PyTorch
pytorch-hed This is a personal reimplementation of Holistically-Nested Edge Detection [1] using PyTorch. Should you be making use of this work, please
a reimplementation of LiteFlowNet in PyTorch that matches the official Caffe version
pytorch-liteflownet This is a personal reimplementation of LiteFlowNet [1] using PyTorch. Should you be making use of this work, please cite the paper
a reimplementation of UnFlow in PyTorch that matches the official TensorFlow version
pytorch-unflow This is a personal reimplementation of UnFlow [1] using PyTorch. Should you be making use of this work, please cite the paper according
an implementation of softmax splatting for differentiable forward warping using PyTorch
softmax-splatting This is a reference implementation of the softmax splatting operator, which has been proposed in Softmax Splatting for Video Frame I
an implementation of 3D Ken Burns Effect from a Single Image using PyTorch
3d-ken-burns This is a reference implementation of 3D Ken Burns Effect from a Single Image [1] using PyTorch. Given a single input image, it animates
LWCC: A LightWeight Crowd Counting library for Python that includes several pretrained state-of-the-art models.
LWCC: A LightWeight Crowd Counting library for Python LWCC is a lightweight crowd counting framework for Python. It wraps four state-of-the-art models
JittorVis - Visual understanding of deep learning models
JittorVis: Visual understanding of deep learning model JittorVis is an open-source library for understanding the inner workings of Jittor models by vi
meProp: Sparsified Back Propagation for Accelerated Deep Learning (ICML 2017)
meProp The codes were used for the paper meProp: Sparsified Back Propagation for Accelerated Deep Learning with Reduced Overfitting (ICML 2017) [pdf]
A modular framework for vision & language multimodal research from Facebook AI Research (FAIR)
MMF is a modular framework for vision and language multimodal research from Facebook AI Research. MMF contains reference implementations of state-of-t
Deepparse is a state-of-the-art library for parsing multinational street addresses using deep learning
Here is deepparse. Deepparse is a state-of-the-art library for parsing multinational street addresses using deep learning. Use deepparse to Use the pr
The end-to-end platform for building voice products at scale
Picovoice Made in Vancouver, Canada by Picovoice Picovoice is the end-to-end platform for building voice products on your terms. Unlike Alexa and Goog
A multi-functional library for full-stack Deep Learning. Simplifies Model Building, API development, and Model Deployment.
chitra What is chitra? chitra (ΰ€ΰ€Ώΰ€€ΰ₯ΰ€°) is a multi-functional library for full-stack Deep Learning. It simplifies Model Building, API development, and M
On-device speech-to-intent engine powered by deep learning
Rhino Made in Vancouver, Canada by Picovoice Rhino is Picovoice's Speech-to-Intent engine. It directly infers intent from spoken commands within a giv
ML From Scratch
ML from Scratch MACHINE LEARNING TOPICS COVERED - FROM SCRATCH Linear Regression Logistic Regression K Means Clustering K Nearest Neighbours Decision
Vision Deep-Learning using Tensorflow, Keras.
Welcome! I am a computer vision deep learning developer working in Korea. This is my blog, and you can see everything I've studied here. https://www.n
A MNIST-like fashion product database. Benchmark
Fashion-MNIST Table of Contents Why we made Fashion-MNIST Get the Data Usage Benchmark Visualization Contributing Contact Citing Fashion-MNIST License
A plug-and-play library for neural networks written in Python
A plug-and-play library for neural networks written in Python!
Deep Learning to Create StepMania SM FIles
StepCOVNet Running Audio to SM File Generator Currently only produces .txt files. Use SMDataTools to convert .txt to .sm python stepmania_note_generat
General purpose GPU compute framework for cross vendor graphics cards (AMD, Qualcomm, NVIDIA & friends)
General purpose GPU compute framework for cross vendor graphics cards (AMD, Qualcomm, NVIDIA & friends). Blazing fast, mobile-enabled, asynchronous and optimized for advanced GPU data processing usecases. Backed by the Linux Foundation.
Code for Parameter Prediction for Unseen Deep Architectures (NeurIPS 2021)
Parameter Prediction for Unseen Deep Architectures (NeurIPS 2021) authors: Boris Knyazev, Michal Drozdzal, Graham Taylor, Adriana Romero-Soriano Overv
Train a state-of-the-art yolov3 object detector from scratch!
TrainYourOwnYOLO: Building a Custom Object Detector from Scratch This repo let's you train a custom image detector using the state-of-the-art YOLOv3 c
Deep learning library for solving differential equations and more
DeepXDE Voting on whether we should have a Slack channel for discussion. DeepXDE is a library for scientific machine learning. Use DeepXDE if you need
On-device wake word detection powered by deep learning.
Porcupine Made in Vancouver, Canada by Picovoice Porcupine is a highly-accurate and lightweight wake word engine. It enables building always-listening
A Real-Time-Strategy game for Deep Learning research
Description DeepRTS is a high-performance Real-TIme strategy game for Reinforcement Learning research. It is written in C++ for performance, but provi
QuakeLabeler is a Python package to create and manage your seismic training data, processes, and visualization in a single place β so you can focus on building the next big thing.
QuakeLabeler Quake Labeler was born from the need for seismologists and developers who are not AI specialists to easily, quickly, and independently bu
a pytorch implementation of auto-punctuation learned character by character
Learning Auto-Punctuation by Reading Engadget Articles Link to Other of my work π Deep Learning Notes: A collection of my notes going from basic mult
Deep Learning (with PyTorch)
Deep Learning (with PyTorch) This notebook repository now has a companion website, where all the course material can be found in video and textual for
π₯π₯High-Performance Face Recognition Library on PaddlePaddle & PyTorchπ₯π₯
face.evoLVe: High-Performance Face Recognition Library based on PaddlePaddle & PyTorch Evolve to be more comprehensive, effective and efficient for fa
A deep learning library that makes face recognition efficient and effective
Distributed Arcface Training in Pytorch This is a deep learning library that makes face recognition efficient, and effective, which can train tens of
PyTorch implementation of the paper Ultra Fast Structure-aware Deep Lane Detection
PyTorch implementation of the paper Ultra Fast Structure-aware Deep Lane Detection
Code image classification of MNIST dataset using different architectures: simple linear NN, autoencoder, and highway network
Deep Learning for image classification pip install -r http://webia.lip6.fr/~baskiotisn/requirements-amal.txt Train an autoencoder python3 train_auto
A NLP program: tokenize method, PoS Tagging with deep learning
IRIS NLP SYSTEM A NLP program: tokenize method, PoS Tagging with deep learning Report Bug Β· Request Feature Table of Contents About The Project Built
RealTime Emotion Recognizer for Machine Learning Study Jam's demo
Emotion recognizer Table of contents Clone project Dataset Install dependencies Main program Demo 1. Clone project git clone https://github.com/GDSC20
Deep Reinforcement Learning by using an on-policy adaptation of Maximum a Posteriori Policy Optimization (MPO)
V-MPO Simple code to demonstrate Deep Reinforcement Learning by using an on-policy adaptation of Maximum a Posteriori Policy Optimization (MPO) in Pyt
It is a system used to detect bone fractures. using techniques deep learning and image processing
MohammedHussiengadalla-Intelligent-Classification-System-for-Bone-Fractures It is a system used to detect bone fractures. using techniques deep learni
Deep Learning Interviews book: Hundreds of fully solved job interview questions from a wide range of key topics in AI.
This book was written for you: an aspiring data scientist with a quantitative background, facing down the gauntlet of the interview process in an increasingly competitive field. For most of you, the interview process is the most significant hurdle between you and a dream job.
Finetuner allows one to tune the weights of any deep neural network for better embeddings on search tasks
Finetuner allows one to tune the weights of any deep neural network for better embeddings on search tasks
Nest - A flexible tool for building and sharing deep learning modules
Nest - A flexible tool for building and sharing deep learning modules Nest is a flexible deep learning module manager, which aims at encouraging code
Ranger - a synergistic optimizer using RAdam (Rectified Adam), Gradient Centralization and LookAhead in one codebase
Ranger-Deep-Learning-Optimizer Ranger - a synergistic optimizer combining RAdam (Rectified Adam) and LookAhead, and now GC (gradient centralization) i
Vector AI β A platform for building vector based applications. Encode, query and analyse data using vectors.
Vector AI is a framework designed to make the process of building production grade vector based applications as quickly and easily as possible. Create
A Deep Learning based project for creating line art portraits.
ArtLine The main aim of the project is to create amazing line art portraits. Sounds Intresting,let's get to the pictures!! Model-(Smooth) Model-(Quali
The Self-Supervised Learner can be used to train a classifier with fewer labeled examples needed using self-supervised learning.
Published by SpaceML β’ About SpaceML β’ Quick Colab Example Self-Supervised Learner The Self-Supervised Learner can be used to train a classifier with
PyTorch image models, scripts, pretrained weights -- ResNet, ResNeXT, EfficientNet, EfficientNetV2, NFNet, Vision Transformer, MixNet, MobileNet-V3/V2, RegNet, DPN, CSPNet, and more
PyTorch Image Models Sponsors What's New Introduction Models Features Results Getting Started (Documentation) Train, Validation, Inference Scripts Awe
Direct design of biquad filter cascades with deep learning by sampling random polynomials.
IIRNet Direct design of biquad filter cascades with deep learning by sampling random polynomials. Usage git clone https://github.com/csteinmetz1/IIRNe
Synthetic structured data generators
Join us on What is Synthetic Data? Synthetic data is artificially generated data that is not collected from real world events. It replicates the stati
Official pytorch implementation of Active Learning for deep object detection via probabilistic modeling (ICCV 2021)
Active Learning for Deep Object Detection via Probabilistic Modeling This repository is the official PyTorch implementation of Active Learning for Dee
This is a collection of simple PyTorch implementations of neural networks and related algorithms. These implementations are documented with explanations,
labml.ai Deep Learning Paper Implementations This is a collection of simple PyTorch implementations of neural networks and related algorithms. These i