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531 search results found

Differentialmobilityanalyzers.jl ⭐ 8

A Julia package for working differential mobility analyzers.

User2016 Notes ⭐ 8

Notes for tutorials and sessions at useR! 2016 Conference 📝

Tensorflow Rl ⭐ 8

텐서플로우 강화학습 튜토리얼 : AlphaGo부터 스타크래프트2 강화학습 에이전트 만들어보기

Regularized Multi-task Learning in R

Cvxpyrepair ⭐ 7

Code for "Automatic repair of convex optimization problems".

R package for the sparse-group lasso problem with regularization parameter selection (iSGL)

Saliency 2018 Videosalgan ⭐ 7

Temporal Regularization of Saliency Maps in Egocentric Videos

[PY]thon [R]ec[O]mmender [S]ystems library

Machine Learning ⭐ 7

Andrew Ng's Machine Learning Course

Gan Techniques Tensorflow ⭐ 7

GANs: Losses, Regularizations and Normalizations

Regularized Rbm ⭐ 7

A regularized version of RBM for unsupervised feature selection.

Logistic Regression Classifier With L2 Regularization ⭐ 7

Logistic regression with L2 regularization for binary classification

Relaxedlasso ⭐ 7

Implementation of Relaxed Lasso Algorithm for Linear Regression.

Drop Activation ⭐ 7

The official implementation of paper "Drop-Activation: Implicit Parameter Reduction and Harmonious Regularization".

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..

l1l2py is a Python package to perform variable selection by means of l1l2 regularization with double optimization.

Improving Deep Neural Networks ⭐ 7

Improving-Deep-Neural-Networks

Confidence Fusion ⭐ 7

Confidence driven image fusion based on TGV regularization

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

Capstoneproject_house_prices_prediction ⭐ 7

Understand the relationships between various features in relation with the sale price of a house using exploratory data analysis and statistical analysis. Applied ML algorithms such as Multiple Linear Regression, Ridge Regression and Lasso Regression in combination with cross validation. Performed parameter tuning, compared the test scores and suggested a best model to predict the final sale price of a house. Seaborn is used to plot graphs and scikit learn package is used for statistical analysi

Drophead Pytorch ⭐ 7

An implementation of drophead regularization for pytorch transformers

Predicting Housing Prices ⭐ 7

Public Repo of my machine learning project to predict home prices

Dmn Chatbot ⭐ 7

Chat bot using Dynamic Memory Network

structured sparsity regularization

Human Activity Recognition With Temporal Regularization ⭐ 7

Shake Shake Tensorflow ⭐ 7

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

Removing Bias In Multi Modal Classifiers ⭐ 7

Machine_learning ⭐ 7

Machine Learning - Coursera.org

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

Smoothed Energy Regularization ⭐ 7

Smoothed Quadratic Energies on Meshes - Martinez Esturo et. al - ACM TOG 2014 - Reference Implementation

Machine Learning Resources ⭐ 7

This cover everything you need to know if you want to learn Machine Learning from basics to advance. It covers how to do exploratory data analysis over datasets, build machine learning models, evaluate their performance and deploy them.

This repository is made to publish code used in "Regularization by Denoising: Clarifications and New Interpretations" by Reehorst, Schniter

Few-view CT reconstruction with group-sparsity regularization

This is an implementation of Truncated Nuclear Norm Regularization Method.

Improved_glmnet ⭐ 7

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.

Credible_learning ⭐ 7

Code for Learning Credible Models

Imp_reg_dl_not_norms ⭐ 7

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

Optimal Transport ⭐ 7

Group project "Algorithms for large-scale optimal transport". Implement ADMMs and Sinkhorn's Algorithms.

SPM implementation of https://github.com/JosePMarques/MP2RAGE-related-sc

Top 15 Google Ai Research Papers ⭐ 6

"Henry Ford is quoted as saying. "History is more or less bunk." Now, if he never spoke those words, doesn't that just prove he was right when he didn't say them?"― Alex Bosworth

Library which can be used to build feed forward NN, Convolutional Nets, Linear Regression, and Logistic Regression Models.

Crfpp Extensions ⭐ 6

CRF++-0.58 extended with a few stochastic gradient based optimization routines

Deeplearning ⭐ 6

implement MLP, CNN RNN using chainer

Constrainedlasso.jl ⭐ 6

Algorithms for fit constrained lasso

Ellzerotrendfiltering.jl ⭐ 6

ℓ0 Trend Filtering - Continuous, Piecewise Linear Approximations with few segments.

Softmax Classifier ⭐ 6

Jrl_tcsvt2014 ⭐ 6

Source code of our TCSVT 2014 paper "Learning Cross-Media Joint Representation with Sparse and Semisupervised Regularization"

Carnd Semantic Segmentation ⭐ 6

My solution for the semantic segmentation project at Udacity Self Driving Car Nanodegree

Multi_task_learning ⭐ 6

Multi-task feature learning

Fisher Rao Regularization ⭐ 6

Dropblock_mxnet_bottom_implemention ⭐ 6

用C++实现一个mxnet版本dropblock Op 最后可以用mx.sym.Dropblock（）调用

Learning Gaussian Graphical Models with Ordered Weighted L1 Regularization

Port of P.C. Hansen's notable AIRtools Matlab suite of inversion / regularization tools

Resnet Regularization Pruning ⭐ 6

An implementation of ResNet with mixup and cutout regularizations and soft filter pruning.

Dynamical Isometry From Orthogonality Neural Nets ⭐ 6

Mathematical consequences of orthogonal weights initialization and regularization in deep learning. Experiments with gain-adjusted orthogonal regularizer on RNNs with SeqMNIST dataset.

Adversarial_lipschitz_regularization ⭐ 6

Adversarial Lipschitz Regularization

Applied Machine Learning ⭐ 6

Applied Machine Learning

ICML 2013. Semi-supervised classifier with squared-loss mutual information regularization

Counterfactual Explanation Based On Gradual Construction For Deep Networks ⭐ 6

Counterfactual Explanation Based on Gradual Construction for Deep Networks Pytorch

Word2Vec in pure Python

Temporal_regularization ⭐ 6

Temporal Regularization for Markov Decision Process

Adversarial Vqa ⭐ 6

Safe_grid_search ⭐ 6

Approximation path and optimal selection of regularization hyperparameter for some machine learning problems.

Regularization_for_machine_learning ⭐ 6

Regularization for Machine Learning-RegML GUI

Tf.estimator_tutorial ⭐ 6

A real life tutorial for the new TF high level API

Sparseblockjacobians.jl ⭐ 6

Tools for large and sparse least-squares problems

Pytorch Sigua ⭐ 6

Pytorch implemetations of SIGUA

BNNR is a novel computational method, which utilizes Bounded Nuclear Norm Regularization algorithm to identify potential novel indications for known or new drugs. The code in this package implements Bounded Nuclear Norm Regularization (BNNR) for drug repositioning, which is implemented in Matlab2014a.

Sgdforlinearmodels ⭐ 6

This package implements the Stochastic Gradient Descent algorithm in Python for Linear Regression, Ridge Regression, Logistic Regression and Logistic Regression with L2 Regularization.

Interp_regularization ⭐ 6

A novel neural network gradient regularization scheme for adversarial robustness and interpretability.

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.

lessSEM estimates sparse structural equation models.

Efficient boosting methods for linear regression.

Weight Decay ⭐ 6

PyTorch code for Group Orthogonalization regularization

Work_mesh_regularization ⭐ 6

Facebook Network Analysis Big5 Personality ⭐ 6

Analyzed users’ Big 5 personality traits to predicting network centrality within organic Facebook friend networks using linear regression with lasso regularization and k-folds cross validation.

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

Source Code for IJCAI 2018 paper "Biased Random Walk based Social Regularization for Word Embeddings"

Variational Autoencoder For Novelty Detection ⭐ 6

A Variational AutoEncoder implemented with Keras and used to perform Novelty Detection with the EMNIST-Letters Dataset.

Ml Privacy Regulization ⭐ 6

Sk Regularization ⭐ 6

Code for "Learning a smooth kernel regularizer for convolutional neural networks" (Feinman & Lake, 2019)

Scproject ⭐ 6

Transfer Learning of Gene Expression Signatures in Python.

Structuredsparsityregularization ⭐ 5

Structured Sparisty Regularizers

Stochastic Computing for Deep Neural Networks

PyTorch code of my WACV 2022 paper Improving Model Generalization by Agreement of Learned Representations from Data Augmentation

Sparsesvm ⭐ 5

Solution Paths of Sparse Linear Support Vector Machine with Lasso or ELastic-Net Regularization

Parallel Implementations of the Empirical Bayesian Elastic Net Cross-Validation in R

Neural Classifier ⭐ 5

My attempt to write classification library based on neural networks.

Logistic Sgd ⭐ 5

Is2019 Vae ⭐ 5

Tensorflow and kaldi implementation of our paper "VAE-based regularization for deep speaker embedding"

Code for Towards a Better Understanding and Regularization of GAN Training Dynamics

401-500 of 531 search results

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