carrtesy

carrtesy's Stars

• bitzhangcy/Deep-Learning-Based-Anomaly-Detection

  21522

• LG-AI-EXAONE/EXAONE-3.0

  Official repository for EXAONE built by LG AI Research

  16111

• kuleshov-group/dgm-resources

  Language:HTML345

• swyoon/normalized-autoencoders

  The official repository for <Autoencoding Under Normalization Constraints> (Yoon, Noh and Park, ICML 2021).

  Language:Jupyter Notebook4218

• Sinaptik-AI/pandas-ai

  Chat with your database (SQL, CSV, pandas, polars, mongodb, noSQL, etc). PandasAI makes data analysis conversational using LLMs (GPT 3.5 / 4, Anthropic, VertexAI) and RAG.

  Language:Python12.6k1.2k

• vivian1993/logic-rules-based-reasoning-tutorial

  A Reading List of logic rules-based reasoning

  17

• karpathy/LLM101n

  LLM101n: Let's build a Storyteller

  28.3k1.5k

• inouye-lab/explaining-distribution-shifts

  The repo for the work "Towards Explaining Distribution Shifts"

  Language:Jupyter Notebook4

• huytransformer/Awesome-Out-Of-Distribution-Detection

  Out-of-distribution detection, robustness, and generalization resources. The repository contains a professionally curated list of papers, tutorials, books, videos, articles and open-source libraries etc

  67564

• jacobyhsi/InterpreTabNet

  [ICML 2024 (Spotlight)] InterpreTabNet: Distilling Predictive Signals from Tabular Data by Salient Feature Interpretation. Paper: https://arxiv.org/abs/2406.00426.

  Language:Jupyter Notebook10

• jshwang0311/ODIM

  Language:Python3

• maxim5/cs229-2018-autumn

  All notes and materials for the CS229: Machine Learning course by Stanford University

  Language:Jupyter Notebook1.7k752

• mlfoundations/tableshift

  A benchmark for distribution shift in tabular data

  Language:Python407

• fungtion/DANN_py3

  python 3 pytorch implementation of DANN

  Language:Python50496

• fungtion/DANN

  pytorch implementation of Domain-Adversarial Training of Neural Networks

  Language:Python832149

• karpathy/build-nanogpt

  Video+code lecture on building nanoGPT from scratch

  Language:Python3.4k463

• hanzhaoml/MDAN

  Demo code for the MDAN paper.

  Language:Python11519

• zhaoxin94/awesome-domain-adaptation

  A collection of AWESOME things about domian adaptation

  5k866

• mil-tokyo/MCD_DA

  Language:Python552152

• KindXiaoming/pykan

  Kolmogorov Arnold Networks

  Language:Jupyter Notebook14.5k1.3k

• SeldonIO/alibi-detect

  Algorithms for outlier, adversarial and drift detection

  Language:Python2.2k219

• vijaylee/Continual_Anomaly_Detection

  Official code for ACMMM 2022 paper: Towards Continual Adaptation in Industrial Anomaly Detection

  Language:Python132

• cure-lab/deep-active-learning

  An implementation of the state-of-the-art Deep Active Learning algorithms

  Language:Python9716

• AI-sandbox/HyperFast

  Language:Python6011

• descriptinc/descript-audio-codec

  State-of-the-art audio codec with 90x compression factor. Supports 44.1kHz, 24kHz, and 16kHz mono/stereo audio.

  Language:Python1.1k101

• rinongal/textual_inversion

  Language:Jupyter Notebook2.9k277

• carrtesy/M2N2

  Official repository for the paper "When Model Meets New Normals: Test-time Adaptation for Unsupervised Time-series Anomaly Detection", AAAI 2024.

  Language:Jupyter Notebook184

• hoon9405/GenHPF

  General Healthcare Predictive Framework

  Language:Python121

• jrzaurin/pytorch-widedeep

  A flexible package for multimodal-deep-learning to combine tabular data with text and images using Wide and Deep models in Pytorch

  Language:Python1.3k188

• IDEA-Research/GroundingDINO

  [ECCV 2024] Official implementation of the paper "Grounding DINO: Marrying DINO with Grounded Pre-Training for Open-Set Object Detection"

  Language:Python6.3k650