ranyishere

deep-tda

Food-Lab

AngularJS App with Django Backend

KramersMoyal

kramersmoyal: Kramers-Moyal coefficients for stochastic data of any dimension, to any desired order

ontology

fungal_automata_comap2021

logic

Logic Framework

reactjs-django-boilerplate

My personal react django boilerplate

TimeOrderedProduct

Time Ordered Product Expansion in Lean4

acorns

Annotated Corpus of Natural Signing

biol002

:alien: BIOL 002: Cellular Basis of Life course website

categorytheory

coq-au-vim

deep-symbolic-optimization

Source code for deep symbolic optimization.

ditto

IDE for Differential Dynamic Logic in Electron

ditto_ide

draw.io

Diagrams from draw.io

gflownet

Generative Flow Networks

GitHubGraduation-2022

Join the GitHub Graduation Yearbook and "walk the stage" on June 11.

googletest

GoogleTest - Google Testing and Mocking Framework

leanblueprint

plasTeX plugin to build formalization blueprints.

los-angeles

Papers We ❤️ Los Angeles

MCSBBootcamp2023

UC Irvine Mathematical Computational Systems Biology Bootcamp Computational Modules

MCSBBootcamp2023_OurStory

editing story to tryout git hello

modal_abm

ranyishere

Config files for my GitHub profile.

ranyishere.github.io

Personal Website for Rany

Reduceron

FPGA Haskell machine with game changing performance. Reduceron is Matthew Naylor, Colin Runciman and Jason Reich's high performance FPGA softcore for running lazy functional programs, including hardware garbage collection. Reduceron has been implemented on various FPGAs with clock frequency ranging from 60 to 150 MHz depending on the FPGA. A high degree of parallelism allows Reduceron to implement graph evaluation very efficiently. This fork aims to continue development on this, with a view to practical applications. Comments, questions, etc are welcome.

state-spaces

Sequence Modeling with Structured State Spaces

Steerable_CNPs

vsrl-framework

The Verifiably Safe Reinforcement Learning Framework