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A collection of open-source GPU accelerated Python tools and examples for quantitative analyst tasks and leverages RAPIDS AI project, Numba, cuDF, and Dask.
Implementation of the vanilla Deep Hedging engine
A Python implementation of Partial Least Squares (PLS) decomposition
Avellaneda-Stoikov HFT market making algorithm implementation
Code for the paper: Sparse Cholesky Factorization for Solving Nonlinear PDEs via Gaussian Processes
Composable transformations of Python+NumPy programs: differentiate, vectorize, JIT to GPU/TPU, and more
Code for the paper: Solving and Learning Nonlinear PDEs with Gaussian Processes
Lecture slides and homework assignments for MA5233 Computational Mathematics at the National University of Singapore.
Cracking the Coding Interview 6th Ed. Python Solutions
the resources I use to learn computer science in my spare time
ALICE (Automated Learning and Intelligence for Causation and Economics) is a Microsoft Research project aimed at applying Artificial Intelligence concepts to economic decision making. One of its go…
DoWhy is a Python library for causal inference that supports explicit modeling and testing of causal assumptions. DoWhy is based on a unified language for causal inference, combining causal graphic…
In this repository, I place my solution for the exercises in multiple famous math textbooks, including Stochastic Differential Equation, Partial Differential Equation, Optimization and so on.
European and Forward-start option pricing and implied volatility in the Heston and rough Heston model
MATLAB library for working with alpha stable distributions
We implement the paper: Deep Learning Volatility
Model Calibration with Neural Networks
OpenSpiel is a collection of environments and algorithms for research in general reinforcement learning and search/planning in games.
Source code, datasets and trained models for the paper Learning Advanced Mathematical Computations from Examples (ICLR 2021), by François Charton, Amaury Hayat (ENPC-Rutgers) and Guillaume Lample
Collected study materials in Numerical Optimization ANU@MATH3514(HPC)
清华大学新版网络学堂课程自动下载脚本 / A python script to clone all files from learn.tsinghua.edu.cn
scikit-fmm is a Python extension module which implements the fast marching method.
Deep Residual Learning for Image Recognition
N-Dimensional Fast Methods: Fast Marching, Fast Sweeping, Group Marching, Fast Iterative, etc.