4011 Repositories
Python deep-neural-networks Libraries
The Implicit Bias of Gradient Descent on Generalized Gated Linear Networks
The Implicit Bias of Gradient Descent on Generalized Gated Linear Networks This folder contains the code to reproduce the data in "The Implicit Bias o
PyTorch-Geometric Implementation of MarkovGNN: Graph Neural Networks on Markov Diffusion
MarkovGNN This is the official PyTorch-Geometric implementation of MarkovGNN paper under the title "MarkovGNN: Graph Neural Networks on Markov Diffusi
TorchMD-Net provides state-of-the-art graph neural networks and equivariant transformer neural networks potentials for learning molecular potentials
TorchMD-net TorchMD-Net provides state-of-the-art graph neural networks and equivariant transformer neural networks potentials for learning molecular
LyaNet: A Lyapunov Framework for Training Neural ODEs
LyaNet: A Lyapunov Framework for Training Neural ODEs Provide the model type--config-name to train and test models configured as those shown in the pa
Numerical differential equation solvers in JAX. Autodifferentiable and GPU-capable.
Diffrax Numerical differential equation solvers in JAX. Autodifferentiable and GPU-capable. Diffrax is a JAX-based library providing numerical differe
This is the replication package for paper submission: Towards Training Reproducible Deep Learning Models.
This is the replication package for paper submission: Towards Training Reproducible Deep Learning Models.
OMLT: Optimization and Machine Learning Toolkit
OMLT is a Python package for representing machine learning models (neural networks and gradient-boosted trees) within the Pyomo optimization environment.
Implemenets the Contourlet-CNN as described in C-CNN: Contourlet Convolutional Neural Networks, using PyTorch
C-CNN: Contourlet Convolutional Neural Networks This repo implemenets the Contourlet-CNN as described in C-CNN: Contourlet Convolutional Neural Networ
MoCap-Solver: A Neural Solver for Optical Motion Capture Data
MoCap-Solver is a data-driven-based robust marker denoising method, which takes raw mocap markers as input and outputs corresponding clean markers and skeleton motions.
EquiBind: Geometric Deep Learning for Drug Binding Structure Prediction
EquiBind: geometric deep learning for fast predictions of the 3D structure in which a small molecule binds to a protein
Non-Autoregressive Translation with Layer-Wise Prediction and Deep Supervision
Deeply Supervised, Layer-wise Prediction-aware (DSLP) Transformer for Non-autoregressive Neural Machine Translation
Tensorflow 2 implementation of our high quality frame interpolation neural network
FILM: Frame Interpolation for Large Scene Motion Project | Paper | YouTube | Benchmark Scores Tensorflow 2 implementation of our high quality frame in
Julia package for contraction of tensor networks, based on the sweep line algorithm outlined in the paper General tensor network decoding of 2D Pauli codes
Julia package for contraction of tensor networks, based on the sweep line algorithm outlined in the paper General tensor network decoding of 2D Pauli codes
From Canonical Correlation Analysis to Self-supervised Graph Neural Networks
Code for CCA-SSG model proposed in the NeurIPS 2021 paper From Canonical Correlation Analysis to Self-supervised Graph Neural Networks.
Fortuitous Forgetting in Connectionist Networks
Fortuitous Forgetting in Connectionist Networks Introduction This repository includes reference code for the paper Fortuitous Forgetting in Connection
DrNAS: Dirichlet Neural Architecture Search
This paper proposes a novel differentiable architecture search method by formulating it into a distribution learning problem. We treat the continuously relaxed architecture mixing weight as random variables, modeled by Dirichlet distribution.
One-Shot Neural Ensemble Architecture Search by Diversity-Guided Search Space Shrinking
One-Shot Neural Ensemble Architecture Search by Diversity-Guided Search Space Shrinking This is an official implementation for NEAS presented in CVPR
CATE: Computation-aware Neural Architecture Encoding with Transformers
CATE: Computation-aware Neural Architecture Encoding with Transformers Code for paper: CATE: Computation-aware Neural Architecture Encoding with Trans
A curated list of automated deep learning (including neural architecture search and hyper-parameter optimization) resources.
Awesome AutoDL A curated list of automated deep learning related resources. Inspired by awesome-deep-vision, awesome-adversarial-machine-learning, awe
PyTorch implementation of DD3D: Is Pseudo-Lidar needed for Monocular 3D Object detection?
PyTorch implementation of DD3D: Is Pseudo-Lidar needed for Monocular 3D Object detection? (ICCV 2021), Dennis Park*, Rares Ambrus*, Vitor Guizilini, Jie Li, and Adrien Gaidon.
A framework for GPU based high-performance medical image processing and visualization
FAST is an open-source cross-platform framework with the main goal of making it easier to do high-performance processing and visualization of medical images on heterogeneous systems utilizing both multi-core CPUs and GPUs. To achieve this, FAST use modern C++, OpenCL and OpenGL.
JAXMAPP: JAX-based Library for Multi-Agent Path Planning in Continuous Spaces
JAXMAPP: JAX-based Library for Multi-Agent Path Planning in Continuous Spaces JAXMAPP is a JAX-based library for multi-agent path planning (MAPP) in c
Convolutional Neural Network to detect deforestation in the Amazon Rainforest
Convolutional Neural Network to detect deforestation in the Amazon Rainforest This project is part of my final work as an Aerospace Engineering studen
PyTorch implementations of the NeRF model described in "NeRF: Representing Scenes as Neural Radiance Fields for View Synthesis"
PyTorch NeRF and pixelNeRF NeRF: Tiny NeRF: pixelNeRF: This repository contains minimal PyTorch implementations of the NeRF model described in "NeRF:
Price Prediction model is used to develop an LSTM model to predict the future market price of Bitcoin and Ethereum.
Price Prediction model is used to develop an LSTM model to predict the future market price of Bitcoin and Ethereum.
Self-Correcting Quantum Many-Body Control using Reinforcement Learning with Tensor Networks
Self-Correcting Quantum Many-Body Control using Reinforcement Learning with Tensor Networks This repository contains the code and data for the corresp
Artificial Neural network regression model to predict the energy output in a combined cycle power plant.
Energy_Output_Predictor Artificial Neural network regression model to predict the energy output in a combined cycle power plant. Abstract Energy outpu
Neural Radiance Fields Using PyTorch
This project is a PyTorch implementation of Neural Radiance Fields (NeRF) for reproduction of results whilst running at a faster speed.
Create a semantic search engine with a neural network (i.e. BERT) whose knowledge base can be updated
Create a semantic search engine with a neural network (i.e. BERT) whose knowledge base can be updated. This engine can later be used for downstream tasks in NLP such as Q&A, summarization, generation, and natural language understanding (NLU).
HiPAL: A Deep Framework for Physician Burnout Prediction Using Activity Logs in Electronic Health Records
HiPAL Code for KDD'22 Applied Data Science Track submission -- HiPAL: A Deep Framework for Physician Burnout Prediction Using Activity Logs in Electro
NeuroGen: activation optimized image synthesis for discovery neuroscience
NeuroGen: activation optimized image synthesis for discovery neuroscience NeuroGen is a framework for synthesizing images that control brain activatio
Deep Surface Reconstruction from Point Clouds with Visibility Information
Data, code and pretrained models for the paper Deep Surface Reconstruction from Point Clouds with Visibility Information.
PyTorch implementation of the ExORL: Exploratory Data for Offline Reinforcement Learning
ExORL: Exploratory Data for Offline Reinforcement Learning This is an original PyTorch implementation of the ExORL framework from Don't Change the Alg
Galois is an auto code completer for code editors (or any text editor) based on OpenAI GPT-2.
Galois is an auto code completer for code editors (or any text editor) based on OpenAI GPT-2. It is trained (finetuned) on a curated list of approximately 45K Python (~470MB) files gathered from the Github. Currently, it just works properly on Python but not bad at other languages (thanks to GPT-2's power).
Python code to fuse multiple RGB-D images into a TSDF voxel volume.
Volumetric TSDF Fusion of RGB-D Images in Python This is a lightweight python script that fuses multiple registered color and depth images into a proj
The proliferation of disinformation across social media has led the application of deep learning techniques to detect fake news.
Fake News Detection Overview The proliferation of disinformation across social media has led the application of deep learning techniques to detect fak
PyZebrascope - an open-source Python platform for brain-wide neural activity imaging in behaving zebrafish
PyZebrascope - an open-source Python platform for brain-wide neural activity imaging in behaving zebrafish
HAIS_2GNN: 3D Visual Grounding with Graph and Attention
HAIS_2GNN: 3D Visual Grounding with Graph and Attention This repository is for the HAIS_2GNN research project. Tao Gu, Yue Chen Introduction The motiv
Multi-Stage Spatial-Temporal Convolutional Neural Network (MS-GCN)
Multi-Stage Spatial-Temporal Convolutional Neural Network (MS-GCN) This code implements the skeleton-based action segmentation MS-GCN model from Autom
SBINN: Systems-biology informed neural network
SBINN: Systems-biology informed neural network The source code for the paper M. Daneker, Z. Zhang, G. E. Karniadakis, & L. Lu. Systems biology: Identi
Non-Vacuous Generalisation Bounds for Shallow Neural Networks
This package requires jax, tensorflow, and numpy. Either tensorflow or scikit-learn can be used for loading data. To run in a nix-shell with required
Efficient Deep Learning Systems course
Efficient Deep Learning Systems This repository contains materials for the Efficient Deep Learning Systems course taught at the Faculty of Computer Sc
Deep Learning agent of Starcraft2, similar to AlphaStar of DeepMind except size of network.
Introduction This repository is for Deep Learning agent of Starcraft2. It is very similar to AlphaStar of DeepMind except size of network. I only test
The mini-AlphaStar (mini-AS, or mAS) - mini-scale version (non-official) of the AlphaStar (AS)
A mini-scale reproduction code of the AlphaStar program. Note: the original AlphaStar is the AI proposed by DeepMind to play StarCraft II.
LocUNet is a deep learning method to localize a UE based solely on the reported signal strengths from a set of BSs.
LocUNet LocUNet is a deep learning method to localize a UE based solely on the reported signal strengths from a set of BSs. The method utilizes accura
FewBit — a library for memory efficient training of large neural networks
FewBit FewBit — a library for memory efficient training of large neural networks. Its efficiency originates from storage optimizations applied to back
This repository is the code of the paper Accelerating Deep Reinforcement Learning for Digital Twin Network Optimization with Evolutionary Strategies
ES_OTN_Public Carlos Güemes Palau, Paul Almasan, Pere Barlet Ros, Albert Cabellos Aparicio Contact us: [email protected], contactus@bn
DNA sequence classification by Deep Neural Network
DNA sequence classification by Deep Neural Network: Project Overview worked on the DNA sequence classification problem where the input is the DNA sequ
A convolutional recurrent neural network for classifying A/B phases in EEG signals recorded for sleep analysis.
CAP-Classification-CRNN A deep learning model based on Inception modules paired with gated recurrent units (GRU) for the classification of CAP phases
Official code for paper "ISNet: Costless and Implicit Image Segmentation for Deep Classifiers, with Application in COVID-19 Detection"
Official code for paper "ISNet: Costless and Implicit Image Segmentation for Deep Classifiers, with Application in COVID-19 Detection". LRPDenseNet.py
Code for Phase diagram of Stochastic Gradient Descent in high-dimensional two-layer neural networks
Phase diagram of Stochastic Gradient Descent in high-dimensional two-layer neural networks Under construction. Description Code for Phase diagram of S
MinkLoc++: Lidar and Monocular Image Fusion for Place Recognition
MinkLoc++: Lidar and Monocular Image Fusion for Place Recognition Paper: MinkLoc++: Lidar and Monocular Image Fusion for Place Recognition accepted fo
N-HiTS: Neural Hierarchical Interpolation for Time Series Forecasting
N-HiTS: Neural Hierarchical Interpolation for Time Series Forecasting Recent progress in neural forecasting instigated significant improvements in the
DiffStride: Learning strides in convolutional neural networks
DiffStride is a pooling layer with learnable strides. Unlike strided convolutions, average pooling or max-pooling that require cross-validating stride values at each layer, DiffStride can be initialized with an arbitrary value at each layer (e.g. (2, 2) and during training its strides will be optimized for the task at hand.
ElasticFace: Elastic Margin Loss for Deep Face Recognition
This is the official repository of the paper: ElasticFace: Elastic Margin Loss for Deep Face Recognition Paper on arxiv: arxiv Model Log file Pretrain
This repository provides an efficient PyTorch-based library for training deep models.
An Efficient Library for Training Deep Models This repository provides an efficient PyTorch-based library for training deep models. Installation Make
Build upon neural radiance fields to create a scene-specific implicit 3D semantic representation, Semantic-NeRF
Semantic-NeRF: Semantic Neural Radiance Fields Project Page | Video | Paper | Data In-Place Scene Labelling and Understanding with Implicit Scene Repr
Temporal Dynamic Convolutional Neural Network for Text-Independent Speaker Verification and Phonemetic Analysis
TDY-CNN for Text-Independent Speaker Verification Official implementation of Temporal Dynamic Convolutional Neural Network for Text-Independent Speake
This code is the implementation of Text Emotion Recognition (TER) with linguistic features
APSIPA-TER This code is the implementation of Text Emotion Recognition (TER) with linguistic features. The network model is BERT with a pretrained mod
SeisComP/SeisBench interface to enable deep-learning (re)picking in SeisComP
scdlpicker SeisComP/SeisBench interface to enable deep-learning (re)picking in SeisComP Objective This is a simple deep learning (DL) repicker module
Speech Emotion Recognition with Fusion of Acoustic- and Linguistic-Feature-Based Decisions
APSIPA-SER-with-A-and-T This code is the implementation of Speech Emotion Recognition (SER) with acoustic and linguistic features. The network model i
Unofficial Tensorflow 2 implementation of the paper Implicit Neural Representations with Periodic Activation Functions
Siren: Implicit Neural Representations with Periodic Activation Functions The unofficial Tensorflow 2 implementation of the paper Implicit Neural Repr
NeuralForecast is a Python library for time series forecasting with deep learning models
NeuralForecast is a Python library for time series forecasting with deep learning models. It includes benchmark datasets, data-loading utilities, evaluation functions, statistical tests, univariate model benchmarks and SOTA models implemented in PyTorch and PyTorchLightning.
This repository has automation content to test Arista devices.
Network tests automation Network tests automation About this repository Requirements Requirements on your laptop Requirements on the switches Quick te
A python package for deep multilingual punctuation prediction.
This python library predicts the punctuation of English, Italian, French and German texts. We developed it to restore the punctuation of transcribed spoken language.
To create a deep learning model which can explain the content of an image in the form of speech through caption generation with attention mechanism on Flickr8K dataset.
To create a deep learning model which can explain the content of an image in the form of speech through caption generation with attention mechanism on Flickr8K dataset.
Brain tumor detection using Convolution-Neural Network (CNN)
Detect and Classify Brain Tumor using CNN. A system performing detection and classification by using Deep Learning Algorithms using Convolution-Neural Network (CNN).
CT Based COVID 19 Diagnose by Image Processing and Deep Learning
This project proposed the deep learning and image processing method to undertake the diagnosis on 2D CT image and 3D CT volume.
Earthquake detection via fiber optic cables using deep learning
Earthquake detection via fiber optic cables using deep learning Author: Fantine Huot Getting started Update the submodules After cloning the repositor
A pure PyTorch implementation of the loss described in "Online Segment to Segment Neural Transduction"
ssnt-loss ℹ️ This is a WIP project. the implementation is still being tested. A pure PyTorch implementation of the loss described in "Online Segment t
Cascaded Deep Video Deblurring Using Temporal Sharpness Prior and Non-local Spatial-Temporal Similarity
This repository is the official PyTorch implementation of Cascaded Deep Video Deblurring Using Temporal Sharpness Prior and Non-local Spatial-Temporal Similarity
Sequence-tagging using deep learning
Classification using Deep Learning Requirements PyTorch version = 1.9.1+cu111 Python version = 3.8.10 PyTorch-Lightning version = 1.4.9 Huggingface
CRF-RNN for Semantic Image Segmentation - PyTorch version
This repository contains the official PyTorch implementation of the "CRF-RNN" semantic image segmentation method, published in the ICCV 2015
Open source simulator for autonomous vehicles built on Unreal Engine / Unity, from Microsoft AI & Research
Welcome to AirSim AirSim is a simulator for drones, cars and more, built on Unreal Engine (we now also have an experimental Unity release). It is open
An implementation of IMLE-Net: An Interpretable Multi-level Multi-channel Model for ECG Classification
IMLE-Net: An Interpretable Multi-level Multi-channel Model for ECG Classification The repostiory consists of the code, results and data set links for
A web porting for NVlabs' StyleGAN2, to facilitate exploring all kinds characteristic of StyleGAN networks
This project is a web porting for NVlabs' StyleGAN2, to facilitate exploring all kinds characteristic of StyleGAN networks. Thanks for NVlabs' excelle
Generate Cartoon Images using Generative Adversarial Network
AvatarGAN ✨ Generate Cartoon Images using DC-GAN Deep Convolutional GAN is a generative adversarial network architecture. It uses a couple of guidelin
Generating retro pixel game characters with Generative Adversarial Networks. Dataset "TinyHero" included.
pixel_character_generator Generating retro pixel game characters with Generative Adversarial Networks. Dataset "TinyHero" included. Dataset TinyHero D
A curated list of Machine Learning and Deep Learning tutorials in Jupyter Notebook format ready to run in Google Colaboratory
Awesome Machine Learning Jupyter Notebooks for Google Colaboratory A curated list of Machine Learning and Deep Learning tutorials in Jupyter Notebook
A curated list of Generative Deep Art projects, tools, artworks, and models
Generative Deep Art A curated list of Generative Deep Art projects, tools, artworks, and models Inbox Get started with making AI art in 2022 – deeplea
The unified machine learning framework, enabling framework-agnostic functions, layers and libraries.
The unified machine learning framework, enabling framework-agnostic functions, layers and libraries. Contents Overview In a Nutshell Where Next? Overv
Semantic Segmentation Architectures Implemented in PyTorch
pytorch-semseg Semantic Segmentation Algorithms Implemented in PyTorch This repository aims at mirroring popular semantic segmentation architectures i
Semantic Segmentation Suite in TensorFlow
Semantic Segmentation Suite in TensorFlow. Implement, train, and test new Semantic Segmentation models easily!
Evaluation framework for testing segmentation networks in PyTorch
Evaluation framework for testing segmentation networks in PyTorch. What segmentation network to choose for next Kaggle competition? This benchmark knows the answer!
Human segmentation models, training/inference code, and trained weights, implemented in PyTorch
Human-Segmentation-PyTorch Human segmentation models, training/inference code, and trained weights, implemented in PyTorch. Supported networks UNet: b
Example of semantic segmentation in Keras
keras-semantic-segmentation-example Example of semantic segmentation in Keras Single class example: Generated data: random ellipse with random color o
RuCLIP tiny (Russian Contrastive Language–Image Pretraining) is a neural network trained to work with different pairs (images, texts).
RuCLIPtiny Zero-shot image classification model for Russian language RuCLIP tiny (Russian Contrastive Language–Image Pretraining) is a neural network
YOLTv5 rapidly detects objects in arbitrarily large aerial or satellite images that far exceed the ~600×600 pixel size typically ingested by deep learning object detection frameworks
YOLTv5 rapidly detects objects in arbitrarily large aerial or satellite images that far exceed the ~600×600 pixel size typically ingested by deep learning object detection frameworks.
Generative Flow Networks for Discrete Probabilistic Modeling
Energy-based GFlowNets Code for Generative Flow Networks for Discrete Probabilistic Modeling by Dinghuai Zhang, Nikolay Malkin, Zhen Liu, Alexandra Vo
Drslmarkov - Distributionally Robust Structure Learning for Discrete Pairwise Markov Networks
Distributionally Robust Structure Learning for Discrete Pairwise Markov Networks
Pytorch implementation of various High Dynamic Range (HDR) Imaging algorithms
Deep High Dynamic Range Imaging Benchmark This repository is the pytorch impleme
Builds a LoRa radio frequency fingerprint identification (RFFI) system based on deep learning techiniques
This project builds a LoRa radio frequency fingerprint identification (RFFI) system based on deep learning techiniques.
Sub-tomogram-Detection - Deep learning based model for Cyro ET Sub-tomogram-Detection
Deep learning based model for Cyro ET Sub-tomogram-Detection High degree of stru
This is a model made out of Neural Network specifically a Convolutional Neural Network model
This is a model made out of Neural Network specifically a Convolutional Neural Network model. This was done with a pre-built dataset from the tensorflow and keras packages. There are other alternative libraries that can be used for this purpose, one of which is the PyTorch library.
Python Assignments for the Deep Learning lectures by Andrew NG on coursera with complete submission for grading capability.
Python Assignments for the Deep Learning lectures by Andrew NG on coursera with complete submission for grading capability.
Convolutional neural network that analyzes self-generated images in a variety of languages to find etymological similarities
This project is a convolutional neural network (CNN) that analyzes self-generated images in a variety of languages to find etymological similarities. Specifically, the goal is to prove that computer vision can be used to identify cognates known to exist, and perhaps lead linguists to evidence of unknown cognates.
SuperSonic, a new open-source framework to allow compiler developers to integrate RL into compilers easily, regardless of their RL expertise
Automating reinforcement learning architecture design for code optimization. Che
RefineGNN - Iterative refinement graph neural network for antibody sequence-structure co-design (RefineGNN)
Iterative refinement graph neural network for antibody sequence-structure co-des
Training a deep learning model on the noisy CIFAR dataset
Training-a-deep-learning-model-on-the-noisy-CIFAR-dataset This repository contai
Simple codebase for flexible neural net training
neural-modular Simple codebase for flexible neural net training. Allows for seamless exchange of models, dataset, and optimizers. Uses hydra for confi