sfragkoul

sfragkoul's Stars

• DILiS-lab/SimbaML

  SimbaML is an all-in-one framework for integrating prior knowledge of ODE models into the ML process by synthetic data augmentation. It allows for the convenient generation of realistic synthetic data by sparsifying and adding noise. Furthermore, our framework provides customizable pipelines for various ML experiments, such as transfer learning.

  Language:Python41

• google/deepvariant

  DeepVariant is an analysis pipeline that uses a deep neural network to call genetic variants from next-generation DNA sequencing data.

  Language:Python3.3k732

• ManimCommunity/manim

  A community-maintained Python framework for creating mathematical animations.

  Language:Python29.1k2k

• PhysiBoSS/PhysiBoSS

  PhysiBoSS 2.0: a sustainable integration of stochastic Boolean and agent-based modelling frameworks

  Language:C++239

• quinlan-lab/applied-computational-genomics

  Applied Computational Genomics Course at UU: Spring 2020

  Language:HTML955212

• worldbank/REaLTabFormer

  A suite of auto-regressive and Seq2Seq (sequence-to-sequence) transformer models for tabular and relational synthetic data generation.

  Language:Jupyter Notebook21724

• TPC-AI/genAI-SE

  Site for "Generative AI for Science and Engineering" course

  92

• 4MedBox/Synthetic_DNA_Simulator

  Creating synthetic DNA based off of real public data.

  Language:Python3

• 123xiaochen/VCFshiny

  Language:HTML277

• jphall663/awesome-machine-learning-interpretability

  A curated list of awesome responsible machine learning resources.

  3.7k591

• rajewsky-lab/mirdeep2

  Discovering known and novel miRNAs from small RNA sequencing data

  Language:Perl14149

• understandable-machine-intelligence-lab/Quantus

  Quantus is an eXplainable AI toolkit for responsible evaluation of neural network explanations

  Language:Jupyter Notebook57375

• pliang279/awesome-phd-advice

  Collection of advice for prospective and current PhD students

  1.7k127

• zic12345/SR2019

  Language:Python124