chrischia06's Stars
jmanchuck/pixelator
Image pixelator
monkeytim19/proof-repair-LLM-Lean4
winedarksea/AutoTS
Automated Time Series Forecasting
huawei-noah/trustworthyAI
Trustworthy AI related projects
e2b-dev/awesome-ai-agents
A list of AI autonomous agents
functime-org/functime
Time-series machine learning at scale. Built with Polars for embarrassingly parallel feature extraction and forecasts on panel data.
srush/MiniChain
A tiny library for coding with large language models.
langchain-ai/langchain
🦜🔗 Build context-aware reasoning applications
huggingface/peft
🤗 PEFT: State-of-the-art Parameter-Efficient Fine-Tuning.
Stability-AI/StableLM
StableLM: Stability AI Language Models
uncertainty-toolbox/uncertainty-toolbox
Uncertainty Toolbox: a Python toolbox for predictive uncertainty quantification, calibration, metrics, and visualization
awslabs/graphstorm
Enterprise graph machine learning framework for billion-scale graphs for ML scientists and data scientists.
DrSasanBarak/metats
MetaTS | Time Series Forecasting using Meta Learning
WenjieDu/PyPOTS
A Python toolkit/library for reality-centric machine/deep learning and data mining on partially-observed time series, including SOTA neural network models for scientific analysis tasks of imputation/classification/clustering/forecasting/anomaly detection/cleaning on incomplete industrial (irregularly-sampled) multivariate TS with NaN missing values
labmlai/annotated_deep_learning_paper_implementations
🧑🏫 60+ Implementations/tutorials of deep learning papers with side-by-side notes 📝; including transformers (original, xl, switch, feedback, vit, ...), optimizers (adam, adabelief, sophia, ...), gans(cyclegan, stylegan2, ...), 🎮 reinforcement learning (ppo, dqn), capsnet, distillation, ... 🧠
ddotta/awesome-polars
A curated list of Polars talks, tools, examples & articles. Contributions welcome !
janosh/awesome-normalizing-flows
Awesome resources on normalizing flows.
illustrated-machine-learning/illustrated-machine-learning.github.io
Website containing illustrations about Machine Learning theory!
NVIDIA/DeepLearningExamples
State-of-the-Art Deep Learning scripts organized by models - easy to train and deploy with reproducible accuracy and performance on enterprise-grade infrastructure.
pgmpy/pgmpy
Python Library for learning (Structure and Parameter), inference (Probabilistic and Causal), and simulations in Bayesian Networks.
eriklindernoren/PyTorch-GAN
PyTorch implementations of Generative Adversarial Networks.
karpathy/minGPT
A minimal PyTorch re-implementation of the OpenAI GPT (Generative Pretrained Transformer) training
google-research/tuning_playbook
A playbook for systematically maximizing the performance of deep learning models.
quantgirluk/aleatory
📦 Python library for Stochastic Processes Simulation and Visualisation
scikit-learn-contrib/MAPIE
A scikit-learn-compatible module to estimate prediction intervals and control risks based on conformal predictions.
ultrafunkamsterdam/undetected-chromedriver
Custom Selenium Chromedriver | Zero-Config | Passes ALL bot mitigation systems (like Distil / Imperva/ Datadadome / CloudFlare IUAM)
awslabs/fortuna
A Library for Uncertainty Quantification.
openai/whisper
Robust Speech Recognition via Large-Scale Weak Supervision
chaos-genius/chaos_genius
ML powered analytics engine for outlier detection and root cause analysis.
probml/sts-jax
Structural Time Series in JAX