GitHub
https://github.com/kimjisoo443/python-for-coding-test
"이것이 취업을 위한 코딩 테스트다 with 파이썬"
https://github.com/kimjisoo443/yolact
A simple, fully convolutional model for real-time instance segmentation.
https://github.com/koordinates/proj
PROJ - Cartographic Projections and Coordinate Transformations Library
https://github.com/koordinates/pdal
PDAL is Point Data Abstraction Library. GDAL for point cloud data.
https://github.com/kubecub/go-project-layout
🔮 A canonical Go project structure and layout for generating scaffolding projects.
https://github.com/kubecub/github-label-syncer
An cross-repository syncing and pull loacl saved GitHub tags CLI or actions tool.
https://github.com/kubecub/typecheck
Typecheck is a github actions robust tool designed for cross-platform source code type checking across all Go build platforms. This utility leverages Go’s built-in parsing and type-check libraries (`go/parser` and `go/types`) to deliver efficient and reliable code analysis.
https://github.com/kubranarci/vcftodata
a python package using pysam to parse VCF file to simple table formats
https://github.com/kubranarci/isoform-spesific-pi3k-inhibitor-analysis
Isoform spesific PI3K inhibitor analysis
https://github.com/kuffmode/oi-and-cms
Characterizing Optimal Signal Propagation in the Human Brain Network
https://github.com/kul-optec/c_proximal_functions
library of functions with the proximal function in C.
https://github.com/kul-optec/drn
Newton-type Douglas-Rachford splitting method and ADMM for structured nonconvex optimization
https://github.com/kul-optec/nmpc-codegen-python
Python version of nmpc-codegen
https://github.com/kul-optec/pantr-cdc2023-experiments
PANTR: A proximal algorithm with regularized Newton updates for nonconvex constrained optimization
https://github.com/kul-optec/panoc
Fast solver for nonlinear model predictive control
https://github.com/kul-optec/panoc.jl
Newton-type accelerated proximal gradient method in Julia
https://github.com/kul-optec/dc_dc_simulator
Simulator for DC-DC power converters
https://github.com/kuleshov-group/awesome-discrete-diffusion-models
A curated list for awesome discrete diffusion models resources.
https://github.com/kuleshov-group/bd3lms
Block Diffusion: Interpolating Between Autoregressive and Diffusion Language Models
https://github.com/kuleshov-group/caduceus
Bi-Directional Equivariant Long-Range DNA Sequence Modeling
https://github.com/kuleshov-group/discrete-diffusion-guidance
Simple Guidance Mechanisms for Discrete Diffusion Models
https://github.com/kuleshov-group/genomics-lrb-viztool
Visualization of results on Genomics Long-Range Benchmark by annotations
https://github.com/kuleuven-cosic/leuvenshtein-db-demo
Database demo of the Leuvenshtein Algorithm
https://github.com/kuleuven-cosic/3_3_isogenies
Magma code to efficiently compute chains of (3,3)-isogenies
https://github.com/kuleuven-cosic/2r-pi-vss
Source code for implementations of round-optimal VSS schemes presented in the paper "On Round-Optimal Computational VSS" published at CiC journal (https://cic.iacr.org/).
https://github.com/kuleuven-cosic/integral-cryptanalysis-characteristic-p
Supplementary material to the paper "Integral cryptanalysis in characteristic"
https://github.com/kuleuven-cosic/final
The fully homomorhic encryption scheme based on NTRU and LWE.
https://github.com/kuleuven-cosic/maestro
MAESTRO: Multi-party AES using Lookup Tables - Various oblivious AES protocols for passively and actively secure three-party secure computation
https://github.com/kuleuven-cosic/pi-vss
Source code for implementations of VSS schemes Π_P and Π_LA built by the general framework Π presented at PKC 2025 (https://eprint.iacr.org/2023/1669).
https://github.com/kuleuven-cosic/jitter_pipeline_trng
A pipelined TRNG ASIC implementation
https://github.com/kuleuven-cosic/flicker_entropy_model
An entropy model for the ERO-TRNG incorporating both white FM noise and flicker FM noise.
https://github.com/kuleuven-cosic/fast_batched_transciphering
This repository contains the code necessary to replicate the timings and other results from the paper "Fast Transciphering Via Batched And Reconfigurable LUT Evaluation"
hamp_processing
Simplified approach of processing raw data from HAMP radar and radiometer.
https://github.com/kull-centre/_2024_theisen_proline_selection
Repository for code and data related to publication
teigarage
EGE RESTful web service. Provides EGE functionality through RESTful web service way.
skinstression
Perform skin stress-strain curve regression on SHG images using deep learning
prime-bus-factor
A tool to calculate the bus factor metric of a Git repository
indice_mercado_trabajo_ingresos
¿Cómo trabajan las mujeres en las provincias argentinas? Un Índice de Género, Trabajo e Ingresos
https://github.com/ai-readi/dataset-documentation-paper-code
Code associated with the data documentation paper
dataset-fish-detection-low-visibility
A fully annotated baited underwater dataset of poor and fair visibility videos for the development of fish detection models and image pre-processing tools.
azimuth
Helping AI practitioners better understand their datasets and models in text classification. From ServiceNow.
https://github.com/ai2cm/aimip
Specification for intercomparison of AI-based climate models
mag_pipeline
🐍 🧬 Turning my metagenomic MAG (metagenome-assembled genome) pipeline into a snakemake pipeline for increased reproducibility and scalability.
android-x32
Android x32 is a community project to virtualize and DeGoogle the Android operating system by Google, specifically the 32 bit versions.
m4ma
An R package containing C++ implementations to speed up the simulation and parameter estimation of the Predictive Pedestrian model.
thesis
Scripts and materials used for thesis "Unveiling the Usability of Reactive Programming APIs: Findings, Tools, and Recommendations"
modification-of-talys-for-tmc-simulations
Necessary modifications to the TALYS source code in order to allow the user to choose which fission fragment file TALYS uses in its simulations with fymodel 4 (Okumura).
segmenting-subsurface
Deep Learning solution for multi-layer seismic data segmentation using Meta's SAM, trained on a dataset of 9,000 volumes for improved subsurface mapping.
