ranyishere
AI, Mathematics, and Software Engineering Walking the line between abstract and applied.
California
Pinned Repositories
deep-tda
deep-tda
DRECPEN
Dimensionality Reducing Encoding for Classification of Pythagorean Engendered Numbers
Food-Lab
AngularJS App with Django Backend
fungal_automata_comap2021
KramersMoyal
kramersmoyal: Kramers-Moyal coefficients for stochastic data of any dimension, to any desired order
logic
Logic Framework
ML-From-Scratch
Bare bones Python implementations of some of the fundamental Machine Learning models and algorithms.
ontology
TimeOrderedProduct
Time Ordered Product Expansion in Lean4
ranyishere's Repositories
ranyishere/Food-Lab
AngularJS App with Django Backend
ranyishere/KramersMoyal
kramersmoyal: Kramers-Moyal coefficients for stochastic data of any dimension, to any desired order
ranyishere/ontology
ranyishere/fungal_automata_comap2021
ranyishere/logic
Logic Framework
ranyishere/TimeOrderedProduct
Time Ordered Product Expansion in Lean4
ranyishere/acorns
Annotated Corpus of Natural Signing
ranyishere/biol002
:alien: BIOL 002: Cellular Basis of Life course website
ranyishere/categorytheory
ranyishere/deep-symbolic-optimization
Source code for deep symbolic optimization.
ranyishere/ditto
IDE for Differential Dynamic Logic in Electron
ranyishere/ditto_ide
ranyishere/draw.io
Diagrams from draw.io
ranyishere/GeometricFlux.jl
Geometric Deep Learning for Flux
ranyishere/gflownet
Generative Flow Networks
ranyishere/GitHubGraduation-2022
Join the GitHub Graduation Yearbook and "walk the stage" on June 11.
ranyishere/googletest
GoogleTest - Google Testing and Mocking Framework
ranyishere/InhibitoryNeuronalModel
ranyishere/leanblueprint
plasTeX plugin to build formalization blueprints.
ranyishere/los-angeles
Papers We ❤️ Los Angeles
ranyishere/MCSBBootcamp2023
UC Irvine Mathematical Computational Systems Biology Bootcamp Computational Modules
ranyishere/MCSBBootcamp2023_OurStory
editing story to tryout git hello
ranyishere/modal_abm
ranyishere/ranyishere
Config files for my GitHub profile.
ranyishere/ranyishere.github.io
Personal Website for Rany
ranyishere/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.
ranyishere/state-spaces
Sequence Modeling with Structured State Spaces
ranyishere/Steerable_CNPs
ranyishere/tuning_playbook
A playbook for systematically maximizing the performance of deep learning models.
ranyishere/vsrl-framework
The Verifiably Safe Reinforcement Learning Framework