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Search results for deep learning regularization

deep-learning x

regularization x

77 search results found

Deeplearning_ai_books ⭐ 14,417

deeplearning.ai（吴恩达老师的深度学习课程笔记及资源）

Mxnet The Straight Dope ⭐ 2,507

An interactive book on deep learning. Much easy, so MXNet. Wow. [Straight Dope is growing up] ---> Much of this content has been incorporated into the new Dive into Deep Learning Book available at https://d2l.ai/.

Coursera Deep Learning Specialization ⭐ 2,459

Notes, programming assignments and quizzes from all courses within the Coursera Deep Learning specialization offered by deeplearning.ai: (i) Neural Networks and Deep Learning; (ii) Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization; (iii) Structuring Machine Learning Projects; (iv) Convolutional Neural Networks; (v) Sequence Models

Deeplearning ⭐ 2,347

Python for《Deep Learning》，该书为《深度学习》(花书) 数学推导、原理剖析与源码级别代码实现

Deep Learning Notes ⭐ 1,257

Experiments with Deep Learning

Cs231n 2017 Summary ⭐ 1,118

After watching all the videos of the famous Standford's CS231n course that took place in 2017, i decided to take summary of the whole course to help me to remember and to anyone who would like to know about it. I've skipped some contents in some lectures as it wasn't important to me.

Morph Net ⭐ 1,010

Fast & Simple Resource-Constrained Learning of Deep Network Structure

Stylegan2 Tensorflow 2.0 ⭐ 419

StyleGAN 2 in Tensorflow 2.0

Deep Learning Tricks ⭐ 381

Enumerate diverse machine learning training tricks.

Caffe for Sparse and Low-rank Deep Neural Networks

Neural Collaborative Filtering ⭐ 312

pytorch version of neural collaborative filtering

Deepnet ⭐ 267

Implementations of CNNs, RNNs and deep learning techniques in pure Numpy

Manifold_mixup ⭐ 262

Code for reproducing Manifold Mixup results (ICML 2019)

Diffusionerf ⭐ 248

[CVPR 2023] DiffusioNeRF: Regularizing Neural Radiance Fields with Denoising Diffusion Models

Official Implementation of Early-Learning Regularization Prevents Memorization of Noisy Labels

3d Mri Brain Tumor Segmentation Using Autoencoder Regularization ⭐ 243

Keras implementation of the paper "3D MRI brain tumor segmentation using autoencoder regularization" by Myronenko A. (https://arxiv.org/abs/1810.11654).

Machine Learning Notebooks ⭐ 241

Machine Learning notebooks for refreshing concepts.

Dmn Tensorflow ⭐ 235

Dynamic Memory Networks (https://arxiv.org/abs/1603.01417) in Tensorflow

Liteflownet2 ⭐ 230

A Lightweight Optical Flow CNN - Revisiting Data Fidelity and Regularization, TPAMI 2020

Js Mind ⭐ 186

Deep Learning Library Written in ES2015.

Modelnet40 C ⭐ 184

Repo for "Benchmarking Robustness of 3D Point Cloud Recognition against Common Corruptions" https://arxiv.org/abs/2201.12296

Continual Learning Benchmark ⭐ 158

Evaluate three types of task shifting with popular continual learning algorithms.

Adversarial Examples In Pytorch ⭐ 103

Pytorch code to generate adversarial examples on mnist and ImageNet data.

Deep Learning Specialization Coursera ⭐ 92

Deep Learning Specialization courses by Andrew Ng, deeplearning.ai

a Ready-to-use PyTorch Extension of Unofficial CutMix Implementations with more improved performance.

Facial Keypoints Detection ⭐ 70

Pytorch_ard ⭐ 70

Pytorch implementation of Variational Dropout Sparsifies Deep Neural Networks

Deep Learning Explained ⭐ 68

This repository contains the lab files for Microsoft course DAT236x: Deep Learning Explained

Deep Learning In Asset Pricing ⭐ 64

https://arxiv.org/abs/1805.01104

Brain Tumor Segmentation Using Deep Neural Networks ⭐ 63

Keras implementation of paper by the same name

Dropneuron ⭐ 58

DropNeuron: Simplifying the Structure of Deep Neural Networks

Deep Learning 101 ⭐ 56

The tools and syntax you need to code neural networks from day one.

Welltunedsimplenets ⭐ 55

[NeurIPS 2021] Well-tuned Simple Nets Excel on Tabular Datasets

Onlinelabelsmoothing ⭐ 45

The official code for the paper "Delving Deep into Label Smoothing", IEEE TIP 2021

Ai_learning_hub ⭐ 45

AI Learning Hub for Machine Learning, Deep Learning, Computer Vision and Statistics

Numpy Neuralnet Exercise ⭐ 42

Implementation of key concepts of neuralnetwork via numpy

Artificial Neural Networks With Jupyter ⭐ 41

Artificial Neural Networks - Gradient descent, BFGS, Regularization with Jupyter notebook

The Deep Learning With Keras Workshop ⭐ 40

An Interactive Approach to Understanding Deep Learning with Keras

Deep Learning Notes ⭐ 40

Notes from the DeepLearning.AI courses

Deeplearning Padhai ⭐ 39

All the code files related to the deep learning course from PadhAI

Deep Learning Specialization Coursera ⭐ 36

Deep Learning Specialization Course by Coursera. Neural Networks, Deep Learning, Hyper Tuning, Regularization, Optimization, Data Processing, Convolutional NN, Sequence Models are including this Course.

Deeplearning.ai ⭐ 36

deeplearning.ai

Box Embeddings ⭐ 35

Box Embeddings as Modules

Stable Weight Decay Regularization ⭐ 31

[NeurIPS 2023] The PyTorch Implementation of Scheduled (Stable) Weight Decay.

Dlai S2 2020 ⭐ 26

Teaching material for the course of Deep Learning and Applied AI, 2nd semester 2020, Sapienza University of Rome

Amp Regularizer ⭐ 25

Code for our paper "Regularizing Neural Networks via Adversarial Model Perturbation", CVPR2021

Getting Started With Tensorflow 2 ⭐ 25

Understand Tensorflow 2.0 step by step. Well Written and Commented for Anyone to learn tf2. Check out the Markdowns for every folder.

Spherenet ⭐ 25

Implementing Deep Hyperspherical Learning

Numpy_neural_net ⭐ 24

A simple neural network (multilayer perceptron) with backpropagation implemented in Python with NumPy

Knowledge_tracing ⭐ 22

自适应学习模型 - 知识追踪

Deep Learning For Inverse Problems ⭐ 21

This project hosts the code and datasets I used for Deep Learning course at Boston University. It aims to post-process the images the low quality images produced as a result of solving inverse problems in imaging (particularly Computed Tomography) and produce high-quality images.

DeepRED: Deep Image Prior Powered by RED

Smoothing Consistency ⭐ 19

Code for the paper "Consistency Regularization for Certified Robustness of Smoothed Classifiers" (NeurIPS 2020)

Deep Learning Topics ⭐ 18

Textadain Robust Recognition ⭐ 18

TextAdaIN: Paying Attention to Shortcut Learning in Text Recognizers

Simple Implementation Of Ml Algorithms ⭐ 17

My simplest implementations of common ML algorithms

SANNet Neural Network Framework

Morph.py ⭐ 16

A neural architecture optimizer, targeted at model-size w.r.t. accuracy

Deeplearning_from_scratch ⭐ 16

A Deep Learning framework for CNNs and LSTMs from scratch, using NumPy.

Implementation for <Regularizing Neural Networks via Minimizing Hyperspherical Energy> in CVPR'20.

Deep Learning Notes ⭐ 15

Deep Learning Coursera Specialization • Lecture Notes • Lab Assignments

Kernel_reg ⭐ 14

Pytorch implementation of regularization methods for deep networks obtained via kernel methods.

Scaleable input gradient regularization

[CVPR 2021] Rigid Subset Mix (RSMix): Regularization Strategy for Point Cloud via Rigidly Mixed Samples

Coursera Machine Learning ⭐ 13

[WIP] In this repository I implemented all assignments in python. (No octave to python library)

Pytorch Finetuner ⭐ 13

Stochastic Downsampling for Cost-Adjustable Inference and Improved Regularization in Convolutional Networks

Deeplearninghandbook ⭐ 12

Lecture Slides and Programming Exercises that may help study the deep learning book by Goodfellow, Bengio and Courville.

Labelrelaxation ⭐ 12

Supplementary material and code for the novel label relaxation approach as presented at AAAI21 by Julian Lienen and Eyke Hüllermeier.

Manifold_mixup ⭐ 12

Tensorflow implementation of the Manifold Mixup machine learning research paper

Deeplearning_models_classifier_tutorial ⭐ 12

使用常见的CNN架构实现CIFAR分类。

Traffic Sign Cnn ⭐ 12

Deep learning network for traffic sign image classification

Learning Class Invariant Features ⭐ 11

Repository for the code of the paper "Neural Networks Regularization Through Class-wise Invariant Representation Learning".

Dropout_tutorial_in_pytorch ⭐ 11

Dropout as Regularization and Bayesian Approximation

Deeplearning_ai_books ⭐ 10

黄海广博士整理的【吴恩达】深度学习笔记

Coursera Ng Improving Deep Neural Networks Hyperparameter Tuning Regularization And Optimization ⭐ 9

Short description for quick search

Neuralnetwork ⭐ 9

Neural Network implementation in Numpy and Keras. Batch Normalization, Dropout, L2 Regularization and Optimizers

Neural Networks And Deep Learning ⭐ 9

Deep learning projects including applications (face recognition, neural style transfer, autonomous driving, sign language reading, music generation, translation, speech recognition and NLP) and theories (CNNs, RNNs, LSTM, Adam, Dropout, BatchNorm, Xavier/He initialization, hyperparameter tuning, regularization, optimization, Residual Networks). Deep Learning Specialization by Andrew Ng, deeplearning.ai

Deepexperiments ⭐ 9

TensorFlow/Keras experiments on computer vision and natural language processing

Eigenvalue Decay Regularizer For Keras ⭐ 8

Eigenvalue Decay is a new option of weight regularizer to the deep learning practitioner that aims at maximum-margin learning.

Shake Shake Keras ⭐ 8

Keras implementation of Shake-Shake regularization

Shadow semi-supervised consistency regularization PyTorch library

Deep_matrix_factorization ⭐ 8

Code for Implicit Regularization in Deep Matrix Factorization.

Google Ml Bootcamp ⭐ 8

구글 머신러닝 부트캠프 - 관련 파일 자료 (과제 번역 포함)

Coursera Deep Learning Specialization ⭐ 7

Notes, programming assignments and quizzes from all courses within the Coursera Deep Learning specialization offered by deeplearning.ai: (i) Neural Networks and Deep Learning; (ii) Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization; (iii) Structuring Machine Learning Projects; (iv) Convolutional Neural Networks..

Imp_reg_dl_not_norms ⭐ 7

Code for Implicit Regularization in Deep Learning May Not Be Explainable by Norms

[ICTAI 2018] This code is a TensorFlow implementation of the paper "Using State Predictions for Value Regularization in Curiosity Driven Deep Reinforcement Learning"

Shake Shake Tensorflow ⭐ 7

Simple Code Implementation of "Shake-Shake Regularization using TensorFlow.

Deep Learning ⭐ 7

Implemented the deep learning techniques using Google Tensorflow that cover deep neural networks with a fully connected network using SGD and ReLUs; Regularization with a multi-layer neural network using ReLUs, L2-regularization, and dropout, to prevent overfitting; Convolutional Neural Networks (CNNs) with learning rate decay and dropout; and Recurrent Neural Networks (RNNs) for text and sequences with Long Short-Term Memory (LSTM) networks.

Improving Deep Neural Networks ⭐ 7

Improving-Deep-Neural-Networks

Auxiliary Image Regularization for Deep CNNs with Noisy labels at ICLR 2016

Counterfactual Explanation Based On Gradual Construction For Deep Networks ⭐ 6

Counterfactual Explanation Based on Gradual Construction for Deep Networks Pytorch

A C++ deep learning library for the construction and optimization of neural networks ranging from simple feedforward architectures to state-of-the-art convolutional ResNets and LSTMs.

Deep Generative Models ⭐ 6

Deep generative models in Tensorflow

Pytorch Sigua ⭐ 6

Pytorch implemetations of SIGUA

PyTorch code for Group Orthogonalization regularization

Tenet_training ⭐ 6

This is an official pytorch implementation of 'Group-wise Inhibition based Feature Regularization for Robust Classification' (ICCV 2021 accepted paper). p.s.: The current repository is the version originally submitted to CMT as supplementary materials.

Deep_learning_keras ⭐ 5

notebooks of learning Deep learning by Keras

Tensornet ⭐ 5

A high-level deep learning library built on top of PyTorch.

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