Jantory

Jantory's Stars

• codecrafters-io/build-your-own-x

  Master programming by recreating your favorite technologies from scratch.

  Language:Markdown301k5.4k67628.2k

• azl397985856/leetcode

  LeetCode Solutions: A Record of My Problem Solving Journey.( leetcode题解，记录自己的leetcode解题之路。)

  Language:JavaScript54.5k1.3k2549.5k

• Light-City/CPlusPlusThings

  C++那些事

  Language:C++38.9k5492218.5k

• run-llama/llama_index

  LlamaIndex is a data framework for your LLM applications

  Language:Python35.5k2465.1k5k

• junyanz/pytorch-CycleGAN-and-pix2pix

  Image-to-Image Translation in PyTorch

  Language:Python22.7k3491.5k6.3k

• rougier/numpy-100

  100 numpy exercises (with solutions)

  Language:Python12k205835.7k

• academicpages/academicpages.github.io

  Github Pages template for academic personal websites, forked from mmistakes/minimal-mistakes

  Language:JavaScript11.7k9036042.1k

• soumith/ganhacks

  starter from "How to Train a GAN?" at NIPS2016

  11.4k347691.7k

• hyunwoongko/transformer

  Transformer: PyTorch Implementation of "Attention Is All You Need"

  Language:Python2.8k720415

• adapter-hub/adapters

  A Unified Library for Parameter-Efficient and Modular Transfer Learning

  Language:Jupyter Notebook2.5k31381339

• chemprop/chemprop

  Message Passing Neural Networks for Molecule Property Prediction

  Language:Python1.7k38522570

• dsgiitr/graph_nets

  PyTorch Implementation and Explanation of Graph Representation Learning papers: DeepWalk, GCN, GraphSAGE, ChebNet & GAT.

  Language:Jupyter Notebook1.1k374224

• Oldpan/Pytorch-Memory-Utils

  pytorch memory track code

  Language:Python9941622155

• taynaud/python-louvain

  Louvain Community Detection

  Language:Python9512378199

• EdinburghNLP/awesome-hallucination-detection

  List of papers on hallucination detection in LLMs.

  56227443

• visinf/n3net

  Neural Nearest Neighbors Networks (NIPS*2018)

  Language:Python283142045

• facebookresearch/CPA

  The Compositional Perturbation Autoencoder (CPA) is a deep generative framework to learn effects of perturbations at the single-cell level. CPA performs OOD predictions of unseen combinations of drugs, learns interpretable embeddings, estimates dose-response curves, and provides uncertainty estimates.

  Language:Jupyter Notebook174141148

• xw-hu/Mask-ShadowGAN

  Mask-ShadowGAN: Learning to Remove Shadows from Unpaired Data | ICCV 2019

  Language:Python141101625

• LSIR/DIS

  CS-423 Distributed Information Systems

  Language:Jupyter Notebook69210104

• benedekrozemberczki/RolX

  An alternative implementation of Recursive Feature and Role Extraction (KDD11 & KDD12)

  Language:Python652419

• AI-sandbox/HyperFast

  Language:Python605411

• TianjinYellow/EdgeDeviceLLMCompetition-Starting-Kit

  Language:Python38239

• jgwiese/gdemo_pancreassegmentation

  demo of a vae model for pancreas segmentation.

  Language:Python28423

• thongnt99/acl22-depression-phq9

  Language:Python21233

• dennishnf/latex-paper-format-neurips2019

  This is an example of a paper in LaTeX for the conference NeurIPS 2019.

  Language:TeX16203

• MichiganNLP/micromodels

  Micromodels -- A framework for accurate, explainable, data efficient, and reusable NLP models.

  Language:Python13303

• theislab/cpa-reproducibility

  Notebooks for CPA figures

  Language:Jupyter Notebook7211

• vitutorial/tour

  The various editions of the VITutorial

  Language:TeX6301

• rbookr/cpp-quick-learn

  c++快速入门

  Language:C++2201

• Cinofix/cinofix.github.io

  Template for Academic Wep Page

  Language:CSS100