regularization

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

Neural Network Distiller by Intel AI Lab: a Python package for neural network compression research. https://intellabs.github.io/distiller

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

Early stopping for PyTorch

Official Pytorch implementation of CutMix regularizer

Training neural models with structured signals.

Implementation of DropBlock: A regularization method for convolutional networks in PyTorch.

Code for reproducing Manifold Mixup results (ICML 2019)

Image-processing software for cryo-electron microscopy

Simple Implementation of many GAN models with PyTorch.

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

2.86% and 15.85% on CIFAR-10 and CIFAR-100

Deep Learning Specialization courses by Andrew Ng, deeplearning.ai

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

机器学习-Coursera-吴恩达- python+Matlab代码实现

Starter code of Prof. Andrew Ng's machine learning MOOC in R statistical language

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

This Repository contains Solutions to the Quizes & Lab Assignments of the Machine Learning Specialization (2022) from Deeplearning.AI on Coursera taught by Andrew Ng, Eddy Shyu, Aarti Bagul, Geoff Ladwig.

Generalized Linear Models in Sklearn Style

Codes and Datasets for paper RecSys'20 "SSE-PT: Sequential Recommendation Via Personalized Transformer" and NurIPS'19 "Stochastic Shared Embeddings: Data-driven Regularization of Embedding Layers"