Haejoong Lee (DeepHaeJoong)

DeepHaeJoong

Geek Repo

Company:sogang univ. NICELAB https://nice.sogang.ac.kr/

Location:Seoul, KOREA

Home Page:https://daljoong2.tistory.com/category

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Haejoong Lee's repositories

modAL

A modular active learning framework for Python

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AppAgent

AppAgent: Multimodal Agents as Smartphone Users, an LLM-based multimodal agent framework designed to operate smartphone apps.

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babyai

BabyAI platform. A testbed for training agents to understand and execute language commands.

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direct-preference-optimization

Reference implementation for DPO (Direct Preference Optimization)

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e3b

Official repo for the E3B algorithm described in the paper "Exploration via Elliptical Episodic Bonuses".

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ecmwf-opendata

A package to download ECMWF open data

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ExaGO

High-performance power grid optimization for stochastic, security-constrained, and multi-period ACOPF problems.

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generative_agents

Generative Agents: Interactive Simulacra of Human Behavior

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Gymnasium

A standard API for reinforcement learning and a diverse set of reference environments (formerly Gym)

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HEFTcom24

Repository for the Hybrid Renewable Energy Forecasting and Trading Competition containing utilities and a "Getting Started" guide.

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HowToTrainYourMAMLPytorch

The original code for the paper "How to train your MAML" along with a replication of the original "Model Agnostic Meta Learning" (MAML) paper in Pytorch.

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hyper-nn

Easy Hypernetworks in Pytorch and Jax

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imp_marl

IMP-MARL: a Suite of Environments for Large-scale Infrastructure Management Planning via MARL

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interpret

Fit interpretable models. Explain blackbox machine learning.

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knowledge-distillation-pytorch

A PyTorch implementation for exploring deep and shallow knowledge distillation (KD) experiments with flexibility

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machine-learning-and-simulation

All the handwritten notes 📝 and source code files 🖥️ used in my YouTube Videos on Machine Learning & Simulation (https://www.youtube.com/channel/UCh0P7KwJhuQ4vrzc3IRuw4Q)

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Meta-learning-without-memorization

A study on the following problems: what the memorization problem is in meta-learning; why memorization problem happens; and how we can prevent it. (ICLR 2020)

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purejaxrl

Really Fast End-to-End Jax RL Implementations

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rl-exploration-baselines

RLeXplore provides stable baselines of exploration methods in reinforcement learning, such as intrinsic curiosity module (ICM), random network distillation (RND) and rewarding impact-driven exploration (RIDE).

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SMARTS

Scalable Multi-Agent RL Training School for Autonomous Driving

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styleguide

Style guides for Google-originated open-source projects

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Time-LLM

[ICLR 2024] Official implementation of "Time-LLM: Time Series Forecasting by Reprogramming Large Language Models"

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uncertainty

Building a Bayesian deep learning models

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Unity_ML_Agents_2.0

Repository for implementing Unity ML-Agents 1.0

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