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A Dual-space Multilevel Kernel-splitting (DMK) Framework for Discrete and Continuous Convolution
A code formatter for Julia with rules set in stone.
Code for the paper "XTrace: Making the most of every sample in stochastic trace estimation"
Code for Hutch++: Optimal Stochastic Trace Estimation
Julia Package for Trace Estimation of implicitly available matrix on a smooth function such as inverse and log determinant.
Model and solve optimal control problems in Julia, both on CPU and GPU.
Open Source Optimization of Dynamic Multidisciplinary Systems
Approximate non-singular kernel functions by sum-of-exponentials or sum-of-gaussians by VP sum and model reduction.
An implementation of the VPMR algorithm, approximating decaying kernels by sum of exponentials.
Julia package to compute weights and points for the classical Gauss quadrature rules
A trajectory optimization library for Matlab
All the handwritten notes 📝 and source code files 🖥️ used in my YouTube Videos on Machine Learning & Simulation (https://www.youtube.com/channel/UCh0P7KwJhuQ4vrzc3IRuw4Q)
Learning in infinite dimension with neural operators.
A domain specific language (DSL) for probabilistic graphical models
Prototype for sparse automatic differentiation in JAX + Julia
Cross-architecture parallel algorithms for Julia's CPU and GPU backends. Targets multithreaded CPUs, and GPUs via Intel oneAPI, AMD ROCm, Apple Metal, Nvidia CUDA.
Least squares and curve fitting in Julia with speed and robustness
Coloring algorithms for sparse Jacobian and Hessian matrices
Rejection-minimal, non-reversible, and continuous-time samplers
Vectorised log density targets for Markov chain Monte Carlo
Robust, modular and efficient implementation of advanced Hamiltonian Monte Carlo algorithms
Optimize Julia Functions With MLIR and XLA for High-Performance Execution on CPU, GPU, TPU and more.
Tools for building non-allocating pre-cached functions in Julia, allowing for GC-free usage of automatic differentiation in complex codes