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CNP team's Projects

alphamod icon alphamod

AlphaMod's official repository for protein folding

annotated_deep_learning_paper_implementations icon 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, ... 🧠

applied-ml icon applied-ml

📚 Papers & tech blogs by companies sharing their work on data science & machine learning in production.

autocoder icon autocoder

We introduced a new model designed for the Code generation task. Its test accuracy on the HumanEval base dataset surpasses that of GPT-4 Turbo (April 2024) and GPT-4o.

awesome-kan icon awesome-kan

A comprehensive collection of KAN(Kolmogorov-Arnold Network)-related resources, including libraries, projects, tutorials, papers, and more, for researchers and developers in the Kolmogorov-Arnold Network field.

calm icon calm

Protein language model trained on coding DNA

chebykan icon chebykan

Kolmogorov-Arnold Networks (KAN) using Chebyshev polynomials instead of B-splines.

chroma icon chroma

A generative model for programmable protein design

clean icon clean

CLEAN: a contrastive learning model for high-quality functional prediction of proteins

colabdesign icon colabdesign

Making Protein Design accessible to all via Google Colab!

colossalai icon colossalai

Making large AI models cheaper, faster and more accessible

courses icon courses

This repository is a curated collection of links to various courses and resources about Artificial Intelligence (AI)

deepes icon deepes

A deep learning-based framework for enzyme screening

esm icon esm

Evolutionary Scale Modeling (esm): Pretrained language models for proteins

evodiff icon evodiff

Generation of protein sequences and evolutionary alignments via discrete diffusion models

evoprotgrad icon evoprotgrad

Directed evolution of proteins in sequence space with gradients

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