coursekevin
PhD student at the University of Toronto. Working on scalable Bayesian methods for time-dependent problems.
University of TorontoToronto, Canada
Pinned Repositories
arlatentsde
Accompanying code for the paper "Amortized reparametrization: efficient and scalable variational inference for latent SDEs
avlpy
A high level python wrapper for Drela and Youngren's AVL. The intent is to be able easily script multiple avl sessions for iterative aircraft design.
Benchmark-Models
A collection of ODE models with experimental data as benchmark problems in order to evaluate new and existing methodologies for data-based modelling
fairgame
Tool to help us buy hard to find items.
gpytorch
A highly efficient and modular implementation of Gaussian Processes in PyTorch
gradoptorch
Classical gradient based optimization with line-search in PyTorch
repopacker
A low-tech solution to large files in git
svise
Accompanying code for "State Estimation of a Physical System without Governing Equations"
variationalsparsebayes
A Pytorch library for stochastic variational inference with sparsity inducing priors.
weakformghnn
Accompanying code for "Weak form generalized Hamiltonian learning"
coursekevin's Repositories
coursekevin/svise
Accompanying code for "State Estimation of a Physical System without Governing Equations"
coursekevin/weakformghnn
Accompanying code for "Weak form generalized Hamiltonian learning"
coursekevin/arlatentsde
Accompanying code for the paper "Amortized reparametrization: efficient and scalable variational inference for latent SDEs
coursekevin/variationalsparsebayes
A Pytorch library for stochastic variational inference with sparsity inducing priors.
coursekevin/gradoptorch
Classical gradient based optimization with line-search in PyTorch
coursekevin/repopacker
A low-tech solution to large files in git
coursekevin/avlpy
A high level python wrapper for Drela and Youngren's AVL. The intent is to be able easily script multiple avl sessions for iterative aircraft design.
coursekevin/gpytorch
A highly efficient and modular implementation of Gaussian Processes in PyTorch
coursekevin/Benchmark-Models
A collection of ODE models with experimental data as benchmark problems in order to evaluate new and existing methodologies for data-based modelling
coursekevin/fairgame
Tool to help us buy hard to find items.
coursekevin/gpustat-web
đź‘“ A web interface of gpustat: monitor GPU clusters at a look
coursekevin/image-extraction
Extract images from PDFs
coursekevin/Intensio-Obfuscator
Obfuscate a python code 2.x and 3.x
coursekevin/guided-diffusion
coursekevin/LNets
Lipschitz Neural Networks described in "Sorting Out Lipschitz Function Approximation" (ICML 2019).
coursekevin/Mini-Conf
Run a conference from your backyard.
coursekevin/NNlib.jl
Neural Network primitives with multiple backends
coursekevin/olcPixelGameEngine
The official distribution of olcPixelGameEngine, a tool used in javidx9's YouTube videos and projects
coursekevin/pathos
parallel graph management and execution in heterogeneous computing
coursekevin/pyLDAvis
Python library for interactive topic model visualization. Port of the R LDAvis package.
coursekevin/releasing-research-code
Tips for releasing research code in Machine Learning (with official NeurIPS 2020 recommendations)
coursekevin/ROM-OpInf-Combustion-2D
Source code for the paper "Data-driven reduced-order models via regularised Operator Inference for a single-injector combustion process" by S. A. McQuarrie, C. Huang, and K. E. Willcox.
coursekevin/sklearn-rvm
An sklearn style implementation of the Relevance Vector Machine (RVM).
coursekevin/smop
Small Matlab to Python compiler
coursekevin/theMLbook
The Python code to reproduce the illustrations from The Hundred-Page Machine Learning Book.
coursekevin/transformers
🤗Transformers: State-of-the-art Natural Language Processing for Pytorch and TensorFlow 2.0.
coursekevin/tvregdiff
Python version of Rick Chartrand's algorithm for numerical differentiation of noisy data