tommyfuu

tommyfuu's Stars

• shap/shap

  A game theoretic approach to explain the output of any machine learning model.

  Language:Jupyter Notebook23.2k2452.6k3.3k

• ekzhang/sshx

  Fast, collaborative live terminal sharing over the web

  Language:Rust6.1k2875196

• lucidrains/x-transformers

  A concise but complete full-attention transformer with a set of promising experimental features from various papers

  Language:Python5k58236429

• MIT-LCP/mimic-code

  MIMIC Code Repository: Code shared by the research community for the MIMIC family of databases

  Language:Jupyter Notebook2.7k1341.2k1.5k

• hila-chefer/Transformer-Explainability

  [CVPR 2021] Official PyTorch implementation for Transformer Interpretability Beyond Attention Visualization, a novel method to visualize classifications by Transformer based networks.

  Language:Jupyter Notebook1.8k2163242

• lucidrains/alphafold3-pytorch

  Implementation of Alphafold 3 from Google Deepmind in Pytorch

  Language:Python1.3k4756158

• Ma-Lab-Berkeley/CRATE

  Code for CRATE (Coding RAte reduction TransformEr).

  Language:Python1.2k212296

• Pseudomanifold/latex-mimosis

  A minimal & modern LaTeX template for your (bachelor's | master's | doctoral) thesis

  Language:TeX1.2k2226131

• kmkurn/pytorch-crf

  (Linear-chain) Conditional random field in PyTorch.

  Language:Python955895152

• hila-chefer/Transformer-MM-Explainability

  [ICCV 2021- Oral] Official PyTorch implementation for Generic Attention-model Explainability for Interpreting Bi-Modal and Encoder-Decoder Transformers, a novel method to visualize any Transformer-based network. Including examples for DETR, VQA.

  Language:Jupyter Notebook811836107

• slaypni/fastdtw

  A Python implementation of FastDTW

  Language:Python8021835123

• yrosseel/lavaan

  an R package for structural equation modeling and more

  Language:R44444254101

• taesiri/ArXivQA

  WIP - Automated Question Answering for ArXiv Papers with Large Language Models (https://arxiv.taesiri.xyz/)

  Language:Python32511714

• GenomicSEM/GenomicSEM

  R-package for structural equation modeling based on GWAS summary data

  Language:R213167056

• irinagain/Awesome-CGM

  List of CGM datasets

  Language:R16610339

• Navidfoumani/ConvTran

  This is a PyTorch implementation of ConvTran

  Language:Python1372118

• reml-lab/mTAN

  Code for "Multi-Time Attention Networks for Irregularly Sampled Time Series", ICLR 2021.

  Language:Python1253923

• BorgwardtLab/Set_Functions_for_Time_Series

  Repository of the ICML 2020 paper "Set Functions for Time Series"

  Language:Python12281228

• mlds-lab/interp-net

  Code for "Interpolation-Prediction Networks for Irregularly Sampled Time Series", ICLR 2019.

  Language:Python9591415

• ZhouYuxuanYX/Hyperformer

  This is the official implementation of our paper "Hypergraph Transformer for Skeleton-based Action Recognition."

  Language:Python8741814

• rondolab/MR-PRESSO

  Performs the Mendelian Randomization Pleiotropy RESidual Sum and Outlier (MR-PRESSO) method.

  Language:R8642730

• BrunakSanderLabs/CancerRiskNet

  Language:Python577323

• philipdarke/torchtime

  Benchmark time series data sets for PyTorch

  Language:Python34335

• ritaranx/CACHE

  [ML4H 2022] This is the code for our paper `Counterfactual and Factual Reasoning over Hypergraphs for Interpretable Clinical Predictions on EHR'.

  Language:Python24123

• alistairewj/challenge2012

  Python code parsing data from PhysioNet Challenge 2012

  Language:Jupyter Notebook19126

• dgarrimar/manta

  Non-parametric, asymptotic P-value computation for multivariate linear models

  Language:R13010

• euxhenh/Truffle

  Trajectory Inference of clinical data via Multi-commodity Flow

  Language:Jupyter Notebook4201

• clinical-data-mining/msk_cdm

  Prototype for new CDM repo layout

  Language:Python12181

• jennylsl/MicroBNetwork

  MicroBNetwork is a a computationally efficient and statistically powerful methods for microbial network analyses: Hubs, Multiple Conditions, and Complex Design.

  Language:R1100

• mhmondol/geefirthr

  Language:R1001