quangtiencs
Bet on myself & Beat the odds. Personal Blog: quangtiencs.com. Vietnamese Blog at: thetalog.com.
Momo M_ServiceHo Chi Minh city, Viet Nam
quangtiencs's Stars
WerWolv/ImHex
🔍 A Hex Editor for Reverse Engineers, Programmers and people who value their retinas when working at 3 AM.
scikit-learn-contrib/MAPIE
A scikit-learn-compatible module to estimate prediction intervals and control risks based on conformal predictions.
scheinerman/Permutations.jl
Permutations class for Julia.
kashif/pytorch-transformer-ts
Repository of Transformer based PyTorch Time Series Models
boyboi86/AFML
All the answers for exercises from Advances in Financial Machine Learning by Dr Marco Lopez de Parodo.
StanJulia/Stan.jl
Stan.jl illustrates the usage of the 'single method' packages, e.g. StanSample, StanOptimize, etc.
facebookresearch/xformers
Hackable and optimized Transformers building blocks, supporting a composable construction.
pytorch-labs/gpt-fast
Simple and efficient pytorch-native transformer text generation in <1000 LOC of python.
JakobRobnik/MicroCanonicalHMC
MCHMC: sampler from an arbitrary differentiable distribution
huggingface/peft
🤗 PEFT: State-of-the-art Parameter-Efficient Fine-Tuning.
adapter-hub/adapters
A Unified Library for Parameter-Efficient and Modular Transfer Learning
YavorGIvanov/sam.cpp
reasoning-machines/pal
PaL: Program-Aided Language Models (ICML 2023)
BasisResearch/chirho
An experimental language for causal reasoning
vllm-project/vllm
A high-throughput and memory-efficient inference and serving engine for LLMs
DEAP/deap
Distributed Evolutionary Algorithms in Python
spotify/voyager
🛰️ An approximate nearest-neighbor search library for Python and Java with a focus on ease of use, simplicity, and deployability.
JuliaTrustworthyAI/ConformalPrediction.jl
Predictive Uncertainty Quantification through Conformal Prediction for Machine Learning models trained in MLJ.
poloclub/wizmap
Explore and interpret large embeddings in your browser with interactive visualization! 📍
theislab/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.
hudson-and-thames/portfoliolab
PortfolioLab is a python library that enables traders to take advantage of the latest portfolio optimisation algorithms used by professionals in the industry.
pablosanjose/Quantica.jl
Simulation of quantum systems on a lattice
SymbolicML/DynamicQuantities.jl
Efficient and type-stable physical quantities in Julia
ag-grid/ag-grid
The best JavaScript Data Table for building Enterprise Applications. Supports React / Angular / Vue / Plain JavaScript.
probabilistic-numerics/probnum
Probabilistic Numerics in Python.
JuliaStats/HypothesisTests.jl
Hypothesis tests for Julia
stefanradev93/BayesFlow
A Python library for amortized Bayesian workflows using generative neural networks.
sozi-projects/Sozi
A "zooming" presentation editor
facebookresearch/nougat
Implementation of Nougat Neural Optical Understanding for Academic Documents
dysonance/Indicators.jl
Financial market technical analysis & indicators in Julia