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WhySoSerious's Projects

acwj icon acwj

A Compiler Writing Journey

awesome-latex-drawing icon awesome-latex-drawing

Drawing Bayesian networks, graphical models, tensors, and technical frameworks and illustrations in LaTeX.

basicreservoircomputing icon basicreservoircomputing

Implementation of a reservoir computer with functions to optimize the parameters and calculate the Lyapunov exponents

brainpy icon brainpy

Brain Dynamics Programming in Python

clearml icon clearml

ClearML - Auto-Magical CI/CD to streamline your ML workflow. Experiment Manager, MLOps and Data-Management

das icon das

DAS-PINNs: A deep adaptive sampling method for solving high-dimensional partial differential equations

das-paddlepaddle icon das-paddlepaddle

PaddlePaddle implementation for "DAS-PINNs: A deep adaptive sampling method for solving high-dimensional partial differential equations"

deeponet icon deeponet

Learning nonlinear operators via DeepONet

deepxde icon deepxde

A library for scientific machine learning and physics-informed learning

flax icon flax

Flax is a neural network library for JAX that is designed for flexibility.

hpm icon hpm

Hidden physics models: Machine learning of nonlinear partial differential equations

jax icon jax

Composable transformations of Python+NumPy programs: differentiate, vectorize, JIT to GPU/TPU, and more

mockingbird icon mockingbird

๐Ÿš€AIๆ‹Ÿๅฃฐ: 5็ง’ๅ†…ๅ…‹้š†ๆ‚จ็š„ๅฃฐ้Ÿณๅนถ็”Ÿๆˆไปปๆ„่ฏญ้Ÿณๅ†…ๅฎน Clone a voice in 5 seconds to generate arbitrary speech in real-time

neuralcde icon neuralcde

Code for "Neural Controlled Differential Equations for Irregular Time Series" (Neurips 2020 Spotlight)

neuralrdes icon neuralrdes

Code for: "Neural Rough Differential Equations for Long Time Series", (ICML 2021)

online-neural-cdes icon online-neural-cdes

Code for: "Neural Controlled Differential Equations for Online Prediction Tasks"

physical_network icon physical_network

Boosting physics solver with neural network / Injecting physical prior into neural networks

pinnpapers icon pinnpapers

Must-read Papers on Physics-Informed Neural Networks.

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