4318 Repositories
Python deep-neural-network Libraries
Autolfads-tf2 - A TensorFlow 2.0 implementation of Latent Factor Analysis via Dynamical Systems (LFADS) and AutoLFADS
autolfads-tf2 A TensorFlow 2.0 implementation of LFADS and AutoLFADS. Installati
Digan - Official PyTorch implementation of Generating Videos with Dynamics-aware Implicit Generative Adversarial Networks
DIGAN (ICLR 2022) Official PyTorch implementation of "Generating Videos with Dyn
S2s2net - Sentinel-2 Super-Resolution Segmentation Network
S2S2Net Sentinel-2 Super-Resolution Segmentation Network Getting started Install
SimCTG - A Contrastive Framework for Neural Text Generation
A Contrastive Framework for Neural Text Generation Authors: Yixuan Su, Tian Lan,
Job-Recommend-Competition - Vectorwise Interpretable Attentions for Multimodal Tabular Data
SiD - Simple Deep Model Vectorwise Interpretable Attentions for Multimodal Tabul
HashNeRF-pytorch - Pure PyTorch Implementation of NVIDIA paper on Instant Training of Neural Graphics primitives
HashNeRF-pytorch Instant-NGP recently introduced a Multi-resolution Hash Encodin
Hierarchical-Bayesian-Defense - Towards Adversarial Robustness of Bayesian Neural Network through Hierarchical Variational Inference (Openreview)
Towards Adversarial Robustness of Bayesian Neural Network through Hierarchical V
LotteryBuyPredictionWebApp - Lottery Purchase Prediction Model
Lottery Purchase Prediction Model Objective and Goal Predict the lottery type th
Point-NeRF: Point-based Neural Radiance Fields
Point-NeRF: Point-based Neural Radiance Fields Project Sites | Paper | Primary c
GEA - Code for Guided Evolution for Neural Architecture Search
Efficient Guided Evolution for Neural Architecture Search Usage Create a conda e
PINN(s): Physics-Informed Neural Network(s) for von Karman vortex street
PINN(s): Physics-Informed Neural Network(s) for von Karman vortex street This is
OpenDelta - An Open-Source Framework for Paramter Efficient Tuning.
OpenDelta is a toolkit for parameter efficient methods (we dub it as delta tuning), by which users could flexibly assign (or add) a small amount parameters to update while keeping the most paramters frozen. By using OpenDelta, users could easily implement prefix-tuning, adapters, Lora, or any other types of delta tuning with preferred PTMs.
Detecting drunk people through thermal images using Deep Learning (CNN)
Drunk Detection CNN Detecting drunk people through thermal images using Deep Learning (CNN) Dataset We used thermal images provided by Electronics Lab
RIFE - Real-Time Intermediate Flow Estimation for Video Frame Interpolation
RIFE - Real-Time Intermediate Flow Estimation for Video Frame Interpolation YouTube | BiliBili 16X interpolation results from two input images: Introd
A lossless neural compression framework built on top of JAX.
Kompressor Branch CI Coverage main (active) main development A neural compression framework built on top of JAX. Install setup.py assumes a compatible
A small module to communicate with Triller's API
A small, UNOFFICIAL module to communicate with Triller's API. I plan to add more features/methods in the future.
The visual framework is designed on the idea of module and implemented by mixin method
Visual Framework The visual framework is designed on the idea of module and implemented by mixin method. Its biggest feature is the mixins module whic
Collection of TensorFlow2 implementations of Generative Adversarial Network varieties presented in research papers.
TensorFlow2-GAN Collection of tf2.0 implementations of Generative Adversarial Network varieties presented in research papers. Model architectures will
OpenFed: A Comprehensive and Versatile Open-Source Federated Learning Framework
OpenFed: A Comprehensive and Versatile Open-Source Federated Learning Framework Introduction OpenFed is a foundational library for federated learning
B2EA: An Evolutionary Algorithm Assisted by Two Bayesian Optimization Modules for Neural Architecture Search
B2EA: An Evolutionary Algorithm Assisted by Two Bayesian Optimization Modules for Neural Architecture Search This is the offical implementation of the
An open software package to develop BCI based brain and cognitive computing technology for recognizing user's intention using deep learning
An open software package to develop BCI based brain and cognitive computing technology for recognizing user's intention using deep learning
Locally Differentially Private Distributed Deep Learning via Knowledge Distillation (LDP-DL)
Locally Differentially Private Distributed Deep Learning via Knowledge Distillation (LDP-DL) A preprint version of our paper: Link here This is a samp
Source code of our work: "Benchmarking Deep Models for Salient Object Detection"
SALOD Source code of our work: "Benchmarking Deep Models for Salient Object Detection". In this works, we propose a new benchmark for SALient Object D
CZU-MHAD: A multimodal dataset for human action recognition utilizing a depth camera and 10 wearable inertial sensors
CZU-MHAD: A multimodal dataset for human action recognition utilizing a depth camera and 10 wearable inertial sensors In order to facilitate the res
Neighbor2Seq: Deep Learning on Massive Graphs by Transforming Neighbors to Sequences
Neighbor2Seq: Deep Learning on Massive Graphs by Transforming Neighbors to Sequences This repository is an official PyTorch implementation of Neighbor
Using deep learning model to detect breast cancer.
Breast-Cancer-Detection Breast cancer is the most frequent cancer among women, with around one in every 19 women at risk. The number of cases of breas
You are AllSet: A Multiset Function Framework for Hypergraph Neural Networks.
AllSet This is the repo for our paper: You are AllSet: A Multiset Function Framework for Hypergraph Neural Networks. We prepared all codes and a subse
This repository contains code from the paper "TTS-GAN: A Transformer-based Time-Series Generative Adversarial Network"
TTS-GAN: A Transformer-based Time-Series Generative Adversarial Network This repository contains code from the paper "TTS-GAN: A Transformer-based Tim
Tensorflow implementation of our method: "Triangle Graph Interest Network for Click-through Rate Prediction".
TGIN Tensorflow implementation of our method: "Triangle Graph Interest Network for Click-through Rate Prediction". Files in the folder dataset/ electr
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
Transfer Reinforcement Learning for Differing Action Spaces via Q-Network Representations
Transfer-Learning-in-Reinforcement-Learning Transfer Reinforcement Learning for Differing Action Spaces via Q-Network Representations Final Report Tra
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.
HGCN: Harmonic Gated Compensation Network For Speech Enhancement
HGCN The official repo of "HGCN: Harmonic Gated Compensation Network For Speech Enhancement", which was accepted at ICASSP2022. How to use step1: Calc
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.
Community and sentiment analysis based on tweets
The project has set itself the goal of analyzing the thoughts and interaction of Italian users through the social posts expressed through the Twitter platform on the day of the entry into force of the new measures. In particular, we want to research the reference hubs present on the network, but also the sentiment and emotions of peoples with respect to the new limitations.
UMPNet: Universal Manipulation Policy Network for Articulated Objects
UMPNet: Universal Manipulation Policy Network for Articulated Objects Zhenjia Xu, Zhanpeng He, Shuran Song Columbia University Robotics and Automation
These are Simple python scripts to test/scan your network
Disclaimer This tool is for Educational purpose only. We do not promote or encourage any illegal activities. Summary These are Simple python scripts t
PacketPy is an open-source solution for stress testing network devices using different testing methods
PacketPy About PacketPy is an open-source solution for stress testing network devices using different testing methods. Currently, there are only two c
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
A minimalist tool to display a network graph.
A tool to get a minimalist view of any architecture This tool has only be tested with the models included in this repo. Therefore, I can't guarantee t
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
TONet: Tone-Octave Network for Singing Melody Extraction from Polyphonic Music
TONet Introduction The official implementation of "TONet: Tone-Octave Network for Singing Melody Extraction from Polyphonic Music", in ICASSP 2022 We
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
Pytorch Implementation of "Desigining Network Design Spaces", Radosavovic et al. CVPR 2020.
RegNet Pytorch Implementation of "Desigining Network Design Spaces", Radosavovic et al. CVPR 2020. Paper | Official Implementation RegNet offer a very
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
This is a python based command line Network Scanner utility, which input as an argument for the exact IP address or the relative IP Address range you wish to do the Network Scan for and returns all the available IP addresses with their MAC addresses on your current Network.
This is a python based command line Network Scanner utility, which input as an argument for the exact IP address or the relative IP Address range you wish to do the Network Scan for and returns all the available IP addresses with their MAC addresses on your current Network.
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.
Anonymously Reverse shell over Tor Network using Hidden Services without portfortwarding
Anonymously Reverse shell over Tor Network using Hidden Services without portfortwarding Tor ağı ile Dark Web servislerini kullanarak anonim biçimde p