Pinned Repositories
Adam-experiments
Experiments with Adam/AdamW/amsgrad
Adaptive_Activation_Functions
We proposed the simple adaptive activation functions deep neural networks. The proposed method is simple and easy to implement in any neural networks architecture.
AiLearning
AiLearning: 机器学习 - MachineLearning - ML、深度学习 - DeepLearning - DL、自然语言处理 NLP
annotated_deep_learning_paper_implementations
🧑🏫 59 Implementations/tutorials of deep learning papers with side-by-side notes 📝; including transformers (original, xl, switch, feedback, vit, ...), optimizers (adam, adabelief, ...), gans(cyclegan, stylegan2, ...), 🎮 reinforcement learning (ppo, dqn), capsnet, distillation, ... 🧠
apachecn_ml
机器学习
CANN
Constitutive Artificial Neural Networks (CANNs) for modeling of hyperelastic materials
CANN-1
when using, please cite "A new family of Constitutive Artificial Neural Networks towards automated model discovery", CMAME, https://arxiv.org/abs/2210.02202
CEC2006
code-of-learn-deep-learning-with-pytorch
This is code of book "Learn Deep Learning with PyTorch"
CODES
Codes for some of my co-authored journal/conference papers
XDFLYQ's Repositories
XDFLYQ/Adaptive_Activation_Functions
We proposed the simple adaptive activation functions deep neural networks. The proposed method is simple and easy to implement in any neural networks architecture.
XDFLYQ/annotated_deep_learning_paper_implementations
🧑🏫 59 Implementations/tutorials of deep learning papers with side-by-side notes 📝; including transformers (original, xl, switch, feedback, vit, ...), optimizers (adam, adabelief, ...), gans(cyclegan, stylegan2, ...), 🎮 reinforcement learning (ppo, dqn), capsnet, distillation, ... 🧠
XDFLYQ/CANN-1
when using, please cite "A new family of Constitutive Artificial Neural Networks towards automated model discovery", CMAME, https://arxiv.org/abs/2210.02202
XDFLYQ/CODES
Codes for some of my co-authored journal/conference papers
XDFLYQ/Deep-Polynomial-Chaos-Neural-Network-Method
XDFLYQ/DeepRL-Chinese
XDFLYQ/DRL
Deep Reinforcement Learning
XDFLYQ/easyrobust
EasyRobust: an Easy-to-use library for state-of-the-art Robust Computer Vision Research with PyTorch.
XDFLYQ/Examples
All benchmarks, examples and applications cases to be run by Kratos. Note that unit tests are in Kratos repository and NOT here
XDFLYQ/ismo_airfoil
XDFLYQ/keras
Deep Learning for humans
XDFLYQ/LabelFree-DNN-Surrogate
Surrogate Modeling for Fluid Flows Based on Physics-Constrained Label-Free Deep Learning
XDFLYQ/LSWR_loss_function_PINN
A kind of loss function based on Least Squares Weighted Residual method for computational solid mechanics
XDFLYQ/Machine-Learning-for-Beginner-by-Python3
为机器学习的入门者提供多种基于实例的sklearn、TensorFlow以及自编函数(AnFany)的ML算法程序。
XDFLYQ/Matlab-Machine
哔哩哔哩视频代码
XDFLYQ/minGPT
A minimal PyTorch re-implementation of the OpenAI GPT (Generative Pretrained Transformer) training
XDFLYQ/neural-structural-identification
XDFLYQ/PGNN
Physics-guided Neural Networks (PGNN) : An Application In Lake Temperature Modelling
XDFLYQ/Physics-informed-DeepONets
XDFLYQ/PiNN
A Python library for building atomic neural networks
XDFLYQ/PINN_Comp_Mech
PINN program for computational mechanics
XDFLYQ/PINN_TFI-HSS
The code for the paper Temperature field inversion of heat-source systems via physics-informed neural networks
XDFLYQ/PINNs-1
XDFLYQ/Predictions-of-thermal-fields-in-additive-manufacturing
Predicting Thermal Fields in AdditiveManufacturing by FEM simulations andMachine Learning
XDFLYQ/PSO-PINN
Physics-Informed Neural Networks Trained with Particle Swarm Optimization
XDFLYQ/python-and-physics
XDFLYQ/pytorch
Tensors and Dynamic neural networks in Python with strong GPU acceleration
XDFLYQ/Road2Coding
编程之路
XDFLYQ/Strong-yet-ductile-nanolamellar-high-entropy-alloys-by-additive-manufacturing
Crystal plasticity finite element code, VUMAT file for Abaqus
XDFLYQ/transformers
🤗 Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.