https://github.com/bandframework/rose
The Reduced-Order Scattering Emulator (rose) is a user-friendly software for building efficient surrogate models for nuclear scattering
https://github.com/bandframework/rose_playground
A place to start playing with ROSE notebooks
https://github.com/bandframework/bandframework
This contains the public repository for the BAND framework project.
https://github.com/banesullivan/vtkbool
A new boolean operations filter for VTK
https://github.com/banesullivan/pyvista-mpl-slicer
Slice PyVista meshes with Matplotlib interactively
https://github.com/banesullivan/mimebytes
Make repr of bytes better in ipython
https://github.com/banesullivan/learnpy-dsp
Learn Python! A set of Jupyter notebooks for learning Python hosted on Binder
https://github.com/banesullivan/banesullivan
The source for my personal website
https://github.com/bansallab/dolphin_metapop
Code and data assoicated with "Seasonal contact and migration structure mass epidemics and inform outbreak preparedness in a vulnerable marine mammal"
https://github.com/bansallab/modular_graph_generator
An algorithm that generates random graphs with a specified modularity.
https://github.com/bansallab/holidayflu
An age-specific metapopulation model for disease spread.
https://github.com/banterle/nor-vdpnet
A no-reference version of HDR-VDP using deep-learning
https://github.com/bao231/stanford_alpaca
Code and documentation to train Stanford's Alpaca models, and generate the data.
https://github.com/bao231/multi-task-learning-example
A multi-task learning example for the paper https://arxiv.org/abs/1705.07115
https://github.com/bao231/loglizer
A log analysis toolkit for automated anomaly detection [ISSRE'16]
https://github.com/bao231/logparser
A toolkit for automated log parsing [ICSE'19, TDSC'18, DSN'16]
https://github.com/bao231/liveness-detection-introduction
活体检测方法调研，introduction to liveness detection
https://github.com/bao231/deep-learning-models
Keras code and weights files for popular deep learning models.
https://github.com/bao231/awesome-machine-learning
A curated list of awesome Machine Learning frameworks, libraries and software.
https://github.com/baoblei/story-adapter
A Training-free Iterative Framework for Long Story Visualization
https://github.com/baoblei/nerfies_capture_processing
Process a video into a Nerfie dataset, for NeRF or 3DGS series task
https://github.com/baoblei/ddpm-uie
a demo of paper “A Patch-based Method for Underwater Image Enhancement with Denoising Diffusion Models”
https://github.com/baohaoliao/vllm
A high-throughput and memory-efficient inference and serving engine for LLMs
https://github.com/baohaoliao/fairseq-1
Facebook AI Research Sequence-to-Sequence Toolkit written in Python.
https://github.com/baohaoliao/unify-parameter-efficient-tuning
Implementation of paper "Towards a Unified View of Parameter-Efficient Transfer Learning" (ICLR 2022)
https://github.com/baophann/awesome-ff
A repository about awesome Forward-forward learning algorithm paper.
https://github.com/baophann/tuning_playbook
A playbook for systematically maximizing the performance of deep learning models.
https://github.com/baquer/awesome_flutter_apps
Flutter is the most growing technology in the field of mobile development 📱. Here is the list of basics flutter apps for the beginner and flutter developers. Show your love by giving ⭐️ to this repo 😎📱
https://github.com/baquer/food_ordering_app
CSE600A Project - Java Command Line Application For Food Ordering
https://github.com/baquer/roundaddbutton
Round Add Button is a simple Round Button , which changes its color in every opening.
https://github.com/baquer/kaolin-wisp
NVIDIA Kaolin Wisp is a PyTorch library powered by NVIDIA Kaolin Core to work with neural fields (including NeRFs, NGLOD, instant-ngp and VQAD).
https://github.com/barabasi-lab/geneformer-networkmedicine
Application of Geneformer for Network Medicine
https://github.com/barabasi-lab/ai-bind
Interpretable AI pipeline improving binding predictions for novel protein targets and ligands
https://github.com/barabasi-lab/covid-19
Supplementary code for the paper: Network Medicine Framework for Identifying Drug Repurposing Opportunities for COVID-19
https://github.com/barahona-research-group/multiscalemobilitypatterns
Code for the paper "Multiscale mobility patterns and the restriction of human movement" by Juni Schindler, Jonathan M Clarke and Mauricio Barahona: https://arxiv.org/abs/2201.06323
https://github.com/barahona-research-group/ice-node
Integration of Clinical Embeddings with Neural ODEs
https://github.com/barahona-research-group/scihpf
single-cell Integrative Hierarchical Poisson Factorisation
https://github.com/barahona-research-group/raman-unmixing-aes
Codebase supporting "Hyperspectral unmixing for Raman spectroscopy via physics-constrained autoencoders"
https://github.com/barahona-research-group/pissaridesreview
Pissarides Review webpage
https://github.com/barahona-research-group/pops
POPs: Propensity Optimised Paths
https://github.com/barahona-research-group/step
Contact tracing is a key tool in epidemiology to identify and control outbreaks of infectious diseases. Existing contact tracing methodologies produce linked networks of individuals based on a binary decision of contact which can be hampered by missing data and indirect contacts. Here, we present our Spatial-temporal Epidemiological Proximity (StEP) model to recover contact maps in disease outbreaks based on movement data. The StEP model accounts for imperfect data by considering probabilistic contacts between individuals based on spatial-temporal proximity of their movement trajectories, creating a robust movement network despite possible missing data and unseen transmission routes. We showcase the potential of StEP for contact tracing with outbreaks of multidrug-resistant bacterial infections and COVID-19 in a large hospital group in London, UK. In addition to the core structure of contacts that can be recovered using traditional methods of contact tracing, the StEP models are able to reveal missing contacts that connect seemingly separate outbreaks. Comparison with genomic data further confirmed that these additional contacts indeed improve characterisation of disease transmission and so highlights how the StEP framework can inform effective strategies of infection control and prevention.
https://github.com/barahona-research-group/gdr
Graph Diffusion Reclassification - Code from the paper "Semi-supervised classification on graphs using explicit diffusion dynamics" by RL Peach, A Arnaudon and M Barahona, Foundations of Data Science 2 (1), 19-33 (2020)
https://github.com/barahona-research-group/graphbasedclustering
Multiresolution clustering of data using geometric graphs --- Code from "Graph-based data clustering via multiscale community detection" by Z Liu and M Barahona, Applied Network Science, 5 (3) (2020). See also: https://wwwf.imperial.ac.uk/~mpbara/Partition_Stability/
https://github.com/barakcohenlab/crx-dms-manuscript
Code for data analysis relevant to CRX DMS project
https://github.com/barakcohenlab/crx-information-content
Code for processing and analyzing massively parallel reporter assay data and computing information content of cis-regulatory sequences.
https://github.com/barakhirshberg/molecular-simulations-final-project-barda-and-yotam
The repository for the final project in the molecular simulations course
https://github.com/barakhirshberg/pimd_for_fermions_data
Raw data for https://doi.org/10.1063/5.0008720 and https://arxiv.org/abs/2003.10317
https://github.com/barathme/hen_multiscale_lowk
Explainable Multiscale Modeling of High-Entropy Nitride Superlattices for Low-Thermal-Conductivity Coatings
https://github.com/barbagroup/snake-lips-2d
2d cfd study (PetIBM on Azure) on the lateral lips of a gliding snake
https://github.com/barbagroup/pygbe-papers
Manuscript source files for two papers submitted for peer review on June 2015.
https://github.com/barbagroup/rescience-rollingpitching
Manuscript for ReScience C about the replication study on the pitching and rolling wing
https://github.com/barbagroup/snake-lips-3d
3d cfd study (OpenFOAM on Azure) on the lateral lips of a gliding snake
https://github.com/barbagroup/pygbe_validation_paper
Paper on Validation for PyGBe and replication studies.
https://github.com/barbagroup/essential_skills_rrc
Essential skills for reproducible research computing
https://github.com/barbagroup/snake-repro
An article reporting the travails of reproducibility in unsteady CFD studies