🥷 C++/Python implementation of the VPMR algorithm

A research agent system deeply rooted in your Zotero library.

Creating beautiful plots of data maps

Tool for producing high quality forecasts for time series data that has multiple seasonality with linear or non-linear growth.

A modular graph-based Retrieval-Augmented Generation (RAG) system

A curated list of retrieval-augmented generation (RAG) in large language models

Unsupervised clustering of high content screen samples

Neural Walk-on-Spheres

Up or down? Maybe both?

The Julia module for Multilevel Monte Carlo methods

Lightweight and easy generation of quasi-Monte Carlo sequences with a ton of different methods on one API for easy parameter exploration in scientific machine learning (SciML)

Deep BSDE implementation in TensorFlow with XLA support. Examples for pricing European options are provided

Deep BSDE solver in Pytorch

This repository contains Python scripts that implement backward stochastic differential equations (BSDEs) solutions to several partial differential equations in high dimension using Pytorch.

This repository contains the code for the paper: Monte Carlo Neural PDE Solver for Learning PDEs via Probabilistic Representation (IEEE TPAMI 2025)

A Julia package for Deep Backwards Stochastic Differential Equation (Deep BSDE) and Feynman-Kac methods to solve high-dimensional PDEs without the curse of dimensionality

A visual labeling system implemented in Jupyter widgets.

Grid-Free Monte Carlo Solvers for Physics Simulations Involving Partial Differential Equations

Randomized algorithms for numerical linear algebra in Julia

Code for paper https://arxiv.org/abs/2306.07961

Research package for automatic differentiation of programs containing discrete randomness.