6818 Repositories
Python Deep-Learning-Image-Captioning Libraries
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
Concept Modeling: Topic Modeling on Images and Text
Concept is a technique that leverages CLIP and BERTopic-based techniques to perform Concept Modeling on images.
Generalized Jensen-Shannon Divergence Loss for Learning with Noisy Labels
The official code for the NeurIPS 2021 paper Generalized Jensen-Shannon Divergence Loss for Learning with Noisy Labels
MultiMix: Sparingly Supervised, Extreme Multitask Learning From Medical Images (ISBI 2021, MELBA 2021)
MultiMix This repository contains the implementation of MultiMix. Our publications for this project are listed below: "MultiMix: Sparingly Supervised,
Code of the paper "Multi-Task Meta-Learning Modification with Stochastic Approximation".
Multi-Task Meta-Learning Modification with Stochastic Approximation This repository contains the code for the paper "Multi-Task Meta-Learning Modifica
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
This is a five-step framework for the development of intrusion detection systems (IDS) using machine learning (ML) considering model realization, and performance evaluation.
AB-TRAP: building invisibility shields to protect network devices The AB-TRAP framework is applicable to the development of Network Intrusion Detectio
Can we visualize a large scientific data set with a surrogate model? We're building a GAN for the Earth's Mantle Convection data set to see if we can!
EarthGAN - Earth Mantle Surrogate Modeling Can a surrogate model of the Earthβs Mantle Convection data set be built such that it can be readily run in
Exponential Graph is Provably Efficient for Decentralized Deep Training
Exponential Graph is Provably Efficient for Decentralized Deep Training This code repository is for the paper Exponential Graph is Provably Efficient
Code Release for the paper "TriBERT: Full-body Human-centric Audio-visual Representation Learning for Visual Sound Separation"
TriBERT This repository contains the code for the NeurIPS 2021 paper titled "TriBERT: Full-body Human-centric Audio-visual Representation Learning for
PyTorch code accompanying the paper "Landmark-Guided Subgoal Generation in Hierarchical Reinforcement Learning" (NeurIPS 2021).
HIGL This is a PyTorch implementation for our paper: Landmark-Guided Subgoal Generation in Hierarchical Reinforcement Learning (NeurIPS 2021). Our cod
Audio Domain Adaptation for Acoustic Scene Classification using Disentanglement Learning
Audio Domain Adaptation for Acoustic Scene Classification using Disentanglement Learning Reference AbeΓer, J. & MΓΌller, M. Towards Audio Domain Adapt
Attack on Confidence Estimation algorithm from the paper "Disrupting Deep Uncertainty Estimation Without Harming Accuracy"
Attack on Confidence Estimation (ACE) This repository is the official implementation of "Disrupting Deep Uncertainty Estimation Without Harming Accura
A Closer Look at Reference Learning for Fourier Phase Retrieval
A Closer Look at Reference Learning for Fourier Phase Retrieval This repository contains code for our NeurIPS 2021 Workshop on Deep Learning and Inver
[NeurIPS'21] "AugMax: Adversarial Composition of Random Augmentations for Robust Training" by Haotao Wang, Chaowei Xiao, Jean Kossaifi, Zhiding Yu, Animashree Anandkumar, and Zhangyang Wang.
AugMax: Adversarial Composition of Random Augmentations for Robust Training Haotao Wang, Chaowei Xiao, Jean Kossaifi, Zhiding Yu, Anima Anandkumar, an
Dynamica causal Bayesian optimisation
Dynamic Causal Bayesian Optimization This is a Python implementation of Dynamic Causal Bayesian Optimization as presented at NeurIPS 2021. Abstract Th
FL-WBC: Enhancing Robustness against Model Poisoning Attacks in Federated Learning from a Client Perspective
FL-WBC: Enhancing Robustness against Model Poisoning Attacks in Federated Learning from a Client Perspective Official implementation of "FL-WBC: Enhan
Code for our paper: Online Variational Filtering and Parameter Learning
Variational Filtering To run phi learning on linear gaussian (Fig1a) python linear_gaussian_phi_learning.py To run phi and theta learning on linear g
[NeurIPS 2021] Source code for the paper "Qu-ANTI-zation: Exploiting Neural Network Quantization for Achieving Adversarial Outcomes"
Qu-ANTI-zation This repository contains the code for reproducing the results of our paper: Qu-ANTI-zation: Exploiting Quantization Artifacts for Achie
Code repository for the paper: Hierarchical Kinematic Probability Distributions for 3D Human Shape and Pose Estimation from Images in the Wild (ICCV 2021)
Hierarchical Kinematic Probability Distributions for 3D Human Shape and Pose Estimation from Images in the Wild Akash Sengupta, Ignas Budvytis, Robert
This is an official PyTorch implementation of Task-Adaptive Neural Network Search with Meta-Contrastive Learning (NeurIPS 2021, Spotlight).
NeurIPS 2021 (Spotlight): Task-Adaptive Neural Network Search with Meta-Contrastive Learning This is an official PyTorch implementation of Task-Adapti
This repository contains the implementation of the paper: "Towards Frequency-Based Explanation for Robust CNN"
RobustFreqCNN About This repository contains the implementation of the paper "Towards Frequency-Based Explanation for Robust CNN" arxiv. It primarly d
An implementation for the loss function proposed in Decoupled Contrastive Loss paper.
Decoupled-Contrastive-Learning This repository is an implementation for the loss function proposed in Decoupled Contrastive Loss paper. Requirements P
In this project I played with mlflow, streamlit and fastapi to create a training and prediction app on digits
Fastapi + MLflow + streamlit Setup env. I hope I covered all. pip install -r requirements.txt Start app Go in the root dir and run these Streamlit str
Create and implement a deep learning library from scratch.
In this project, we create and implement a deep learning library from scratch. Table of Contents Deep Leaning Library Table of Contents About The Proj
Implementation of UNET architecture for Image Segmentation.
Semantic Segmentation using UNET This is the implementation of UNET on Carvana Image Masking Kaggle Challenge About the Dataset This dataset contains
JAXDL: JAX (Flax) Deep Learning Library
JAXDL: JAX (Flax) Deep Learning Library Simple and clean JAX/Flax deep learning algorithm implementations: Soft-Actor-Critic (arXiv:1812.05905) Transf
This is a python package that turns any images into MIDI files that views the same as them
image_to_midi This is a python package that turns any images into MIDI files that views the same as them. This package firstly convert the image to AS
(Py)TOD: Tensor-based Outlier Detection, A General GPU-Accelerated Framework
(Py)TOD: Tensor-based Outlier Detection, A General GPU-Accelerated Framework Background: Outlier detection (OD) is a key data mining task for identify
A PyTorch Lightning Callback for pushing models to the Hugging Face Hub π€β‘οΈ
hf-hub-lightning A callback for pushing lightning models to the Hugging Face Hub. Note: I made this package for myself, mostly...if folks seem to be i
PyTorch implementation of "A Simple Baseline for Low-Budget Active Learning".
A Simple Baseline for Low-Budget Active Learning This repository is the implementation of A Simple Baseline for Low-Budget Active Learning. In this pa
An interactive interface for using OpenCV's GrabCut algorithm for image segmentation.
Interactive GrabCut An interactive interface for using OpenCV's GrabCut algorithm for image segmentation. Setup Install dependencies: pip install nump
The PyTorch implementation of Directed Graph Contrastive Learning (DiGCL), NeurIPS-2021
Directed Graph Contrastive Learning The PyTorch implementation of Directed Graph Contrastive Learning (DiGCL). In this paper, we present the first con
The Empirical Investigation of Representation Learning for Imitation (EIRLI)
The Empirical Investigation of Representation Learning for Imitation (EIRLI)
A lightweight python AUTOmatic-arRAY library.
A lightweight python AUTOmatic-arRAY library. Write numeric code that works for: numpy cupy dask autograd jax mars tensorflow pytorch ... and indeed a
Simple PyTorch hierarchical models.
A python package adding basic hierarchal networks in pytorch for classification tasks. It implements a simple hierarchal network structure based on feed-backward outputs.
A Nim frontend for pytorch, aiming to be mostly auto-generated and internally using ATen.
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+
Quantile Regression DQN a Minimal Working Example, Distributional Reinforcement Learning with Quantile Regression
Quantile Regression DQN Quantile Regression DQN a Minimal Working Example, Distributional Reinforcement Learning with Quantile Regression (https://arx
PyTorch implementation of SmoothGrad: removing noise by adding noise.
SmoothGrad implementation in PyTorch PyTorch implementation of SmoothGrad: removing noise by adding noise. Vanilla Gradients SmoothGrad Guided backpro
Anuvada: Interpretable Models for NLP using PyTorch
Anuvada: Interpretable Models for NLP using PyTorch So, you want to know why your classifier arrived at a particular decision or why your flashy new d
Revisiting Oxford and Paris: Large-Scale Image Retrieval Benchmarking
Revisiting Oxford and Paris: Large-Scale Image Retrieval Benchmarking We revisit and address issues with Oxford 5k and Paris 6k image retrieval benchm
PyTorch implementation of Advantage Actor Critic (A2C), Proximal Policy Optimization (PPO), Scalable trust-region method for deep reinforcement learning using Kronecker-factored approximation (ACKTR) and Generative Adversarial Imitation Learning (GAIL).
PyTorch implementation of Advantage Actor Critic (A2C), Proximal Policy Optimization (PPO), Scalable trust-region method for deep reinforcement learning using Kronecker-factored approximation (ACKTR) and Generative Adversarial Imitation Learning (GAIL).
A method for cleaning and classifying text using transformers.
NLP Translation and Classification The repository contains a method for classifying and cleaning text using NLP transformers. Overview The input data
A Pytorch Implementation of a continuously rate adjustable learned image compression framework.
GainedVAE A Pytorch Implementation of a continuously rate adjustable learned image compression framework, Gained Variational Autoencoder(GainedVAE). N
Simple Machine Learning Tool Kit
Getting started smltk (Simple Machine Learning Tool Kit) package is implemented for helping your work during data preparation testing your model The g
Deep learning image registration library for PyTorch
TorchIR: Pytorch Image Registration TorchIR is a image registration library for deep learning image registration (DLIR). I have integrated several ide
NeurIPS 2021, "Fine Samples for Learning with Noisy Labels"
[Official] FINE Samples for Learning with Noisy Labels This repository is the official implementation of "FINE Samples for Learning with Noisy Labels"
Official Pytorch implementation of "Unbiased Classification Through Bias-Contrastive and Bias-Balanced Learning (NeurIPS 2021)
Unbiased Classification Through Bias-Contrastive and Bias-Balanced Learning (NeurIPS 2021) Official Pytorch implementation of Unbiased Classification
Deep Learning for Computer Vision final project
Deep Learning for Computer Vision final project
DirectML is a high-performance, hardware-accelerated DirectX 12 library for machine learning.
DirectML is a high-performance, hardware-accelerated DirectX 12 library for machine learning. DirectML provides GPU acceleration for common machine learning tasks across a broad range of supported hardware and drivers, including all DirectX 12-capable GPUs from vendors such as AMD, Intel, NVIDIA, and Qualcomm.
Anti-Backdoor learning (NeurIPS 2021)
Anti-Backdoor Learning PyTorch Code for NeurIPS 2021 paper Anti-Backdoor Learning: Training Clean Models on Poisoned Data. The Anti-Backdoor Learning
Code repository for the work "Multi-Domain Incremental Learning for Semantic Segmentation", accepted at WACV 2022
Multi-Domain Incremental Learning for Semantic Segmentation This is the Pytorch implementation of our work "Multi-Domain Incremental Learning for Sema
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
Official PyTorch implementation of the paper Image-Based CLIP-Guided Essence Transfer.
TargetCLIP- official pytorch implementation of the paper Image-Based CLIP-Guided Essence Transfer This repository finds a global direction in StyleGAN
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.
Project repo for the paper SILT: Self-supervised Lighting Transfer Using Implicit Image Decomposition
SILT: Self-supervised Lighting Transfer Using Implicit Image Decomposition (BMVC 2021) Project repo for the paper SILT: Self-supervised Lighting Trans
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
Instance-Dependent Partial Label Learning
Instance-Dependent Partial Label Learning Installation pip install -r requirements.txt Run the Demo benchmark-random mnist python -u main.py --gpu 0 -
Learning-Augmented Dynamic Power Management
Learning-Augmented Dynamic Power Management This repository contains source code accompanying paper Learning-Augmented Dynamic Power Management with M
Off-policy continuous control in PyTorch, with RDPG, RTD3 & RSAC
arXiv technical report soon available. we are updating the readme to be as comprehensive as possible Please ask any questions in Issues, thanks. Intro
Code for "AutoMTL: A Programming Framework for Automated Multi-Task Learning"
AutoMTL: A Programming Framework for Automated Multi-Task Learning This is the website for our paper "AutoMTL: A Programming Framework for Automated M
Avalanche RL: an End-to-End Library for Continual Reinforcement Learning
Avalanche RL: an End-to-End Library for Continual Reinforcement Learning Avalanche Website | Getting Started | Examples | Tutorial | API Doc | Paper |
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
A simple voice detection system which can be applied practically for designing a device with capability to detect a babyβs cry and automatically turning on music
Auto-Baby-Cry-Detection-with-Music-Player A simple voice detection system which can be applied practically for designing a device with capability to d
Use Jax functions in Pytorch with DLPack
Use Jax functions in Pytorch with DLPack
One-Stop Destination for codes of all Data Structures & Algorithms
CodingSimplified_GK This repository is aimed at creating a One stop Destination of codes of all Data structures and Algorithms along with basic explai
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.
Hacking and Learning consistently for 100 days straight af.
#100DaysOfHacking Hacking and Learning consistently for 100 days straight af. [yes, no breaks except mental-break ones, Obviously.] This Repo is one s
Official PyTorch implementation of the paper Image-Based CLIP-Guided Essence Transfer.
TargetCLIP- official pytorch implementation of the paper Image-Based CLIP-Guided Essence Transfer This repository finds a global direction in StyleGAN
Polynomial-time Meta-Interpretive Learning
Louise - polynomial-time Program Learning Getting help with Louise Louise's author can be reached by email at [email protected]. Please use this email t
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
ICLR 2021 i-Mix: A Domain-Agnostic Strategy for Contrastive Representation Learning
Introduction PyTorch code for the ICLR 2021 paper [i-Mix: A Domain-Agnostic Strategy for Contrastive Representation Learning]. @inproceedings{lee2021i
PyTorch Code for NeurIPS 2021 paper Anti-Backdoor Learning: Training Clean Models on Poisoned Data.
Anti-Backdoor Learning PyTorch Code for NeurIPS 2021 paper Anti-Backdoor Learning: Training Clean Models on Poisoned Data. Check the unlearning effect
π΅ A repository for manually annotating files to create labeled acoustic datasets for machine learning.
π΅ A repository for manually annotating files to create labeled acoustic datasets for machine learning.
This repository has the lessons of the gamming programming course
learning-python-game-programming This repository has the lessons of the gamming programming course Na faculdade, estou fazendo a disciplina de program
Official implementation of the paper WAV2CLIP: LEARNING ROBUST AUDIO REPRESENTATIONS FROM CLIP
Wav2CLIP π§ WIP π§ Official implementation of the paper WAV2CLIP: LEARNING ROBUST AUDIO REPRESENTATIONS FROM CLIP π π Ho-Hsiang Wu, Prem Seetharaman
A little Python application to auto tag your photos with the power of machine learning.
Tag Machine A little Python application to auto tag your photos with the power of machine learning. Report a bug or request a feature Table of Content
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
Official PyTorch implementation of "Improving Face Recognition with Large AgeGaps by Learning to Distinguish Children" (BMVC 2021)
Inter-Prototype (BMVC 2021): Official Project Webpage This repository provides the official PyTorch implementation of the following paper: Improving F
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
Segmentation models with pretrained backbones. PyTorch.
Python library with Neural Networks for Image Segmentation based on PyTorch. The main features of this library are: High level API (just two lines to
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
Super-BPD: Super Boundary-to-Pixel Direction for Fast Image Segmentation (CVPR 2020)
Super-BPD for Fast Image Segmentation (CVPR 2020) Introduction We propose direction-based super-BPD, an alternative to superpixel, for fast generic im
Classifying cat and dog images using Kaggle dataset
PyTorch Image Classification Classifies an image as containing either a dog or a cat (using Kaggle's public dataset), but could easily be extended to
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
Convolutional Recurrent Neural Network (CRNN) for image-based sequence recognition.
Convolutional Recurrent Neural Network This software implements the Convolutional Recurrent Neural Network (CRNN), a combination of CNN, RNN and CTC l
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