Popular GitHub Repositories for Theoretical

Sharing both practical insights and theoretical knowledge about LLM evaluation that we gathered while managing the Open LLM Leaderboard and designing lighteval!

For deep RL and the future of AI.

Implementations of (theoretical) generative adversarial networks and comparison without cherry-picking

[SIGMOD 2024] RaBitQ: Quantizing High-Dimensional Vectors with a Theoretical Error Bound for Approximate Nearest Neighbor Search

llm theoretical performance analysis tools and support params, flops, memory and latency analysis.

[NeurIPS2021] Federated Reinforcement Learning with Theoretical Guarantees. The repo contains code and experiments for our Federated Policy Gradient with Byzantine Resilience framework for improving sample efficiency of RL agents.

This paper list focuses on the theoretical and empirical analysis of language models, especially large language models (LLMs). The papers in this list investigate the learning behavior, generalization ability, and other properties of language models through theoretical analysis, empirical analysis, or a combination of both.

Quantum computational chemistry based on TensorCircuit

PyTorch Implementation of Personalized federated learning with theoretical guarantees: A model-agnostic meta-learning approach

extensive Python library for rock physics modelling

ShinRL: A Library for Evaluating RL Algorithms from Theoretical and Practical Perspectives (Deep RL Workshop 2021)

Resources and Implementations (PyTorch) for Information Theoretical concepts in Deep Learning

An implementation of Olshausen and Field (96) in PyTorch

? Discrete ? Mathematics ✈ Lab an ? amazing hands ? on repository ? designed to ? make discrete ? math practical ? visual and ? intuitive Whether ? you're a ? computer science ? student a ? mathematics ? enthusiast ⚽ preparing coding ⛸ interviews ? this lab brings ? the theoretical ? foundations of ? logic and computation to life

Active Test-Time Adaptation: Theoretical Analyses and An Algorithm [ICLR 2024]

Theoretical Machine Learning (APPM 4490) class, Spring 2022

Certified (approximate) machine unlearning for simplified graph convolutional networks (SGCs) with theoretical guarantees (ICLR 2023)

[ICML 2023] Decentralized SGD and Average-direction SAM are Asymptotically Equivalent

This is an initiative to help understand Statistical methods and Machine learning in a naive manner. You will find scripts, and theoretical contents required to clarify concepts, especially for bio-informatic students.

This repository is for every beginner who just finished with the theoretical part of Machine Learning and wants to have a hands on experience of various kinds of algorithm and make predictions on a real time dataset.