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Management

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관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.

https://github.com/collinarnett/safex_trading_bot

A Deep Reinforcement Learning Framework for the Financial Portfolio Management Problem

https://github.com/collinarnett/xcalibra_trading_bot

A Deep Reinforcement Learning Framework for the Financial Portfolio Management Problem

https://github.com/cove9988/TradingGym

A Deep Reinforcement Learning Framework for the Financial Portfolio Management Problem

https://github.com/cpacker/memgpt

MemGPT: Towards LLMs as Operating Systems

https://github.com/d3m-research-group/odtlearn

Strong Optimal Classification Trees

https://github.com/daajoe/thp_docker_build

Towards Faster Reasoners By Using Transparent Huge Pages

https://github.com/daniel-hain/ML_course_maastricht

Introduction to Rare-Event Predictive Modeling for Inferential Statisticians -- A Hands-On Application in the Prediction of Breakthrough Patents

https://github.com/danielrossi1/takunet

Deep-Learning-Based Aerial Image Classification for Emergency Response Applications Using Unmanned Aerial Vehicles

https://github.com/danishgufran/FedHIL

FedHIL: Heterogeneity Resilient Federated Learning for Robust Indoor Localization with Mobile Devices

https://github.com/dao-ailab/flash-attention

Efficient Memory Management for Large Language Model Serving with PagedAttention

https://github.com/darwinai/FibrosisNet

Fibrosis-Net: A Tailored Deep Convolutional Neural Network Design for Prediction of Pulmonary Fibrosis Progression from Chest CT Images

https://github.com/deepcrypto/Reinforcement-learning-in-portfolio-management-

A Deep Reinforcement Learning Framework for the Financial Portfolio Management Problem

https://github.com/depexo/BigDL-master

BigDL: A Distributed Deep Learning Framework for Big Data

https://github.com/derecho-project/cascade

Cascade: A Platform for Delay-Sensitive Edge Intelligence

https://github.com/dhelms1/plant_pathology

The Plant Pathology 2020 challenge dataset to classify foliar disease of apples

https://github.com/dmmiller612/bert-extractive-summarizer

Leveraging BERT for Extractive Text Summarization on Lectures

https://github.com/dns43/fairness

Achieving Fairness through Adversarial Learning: an Application to Recidivism Prediction

https://github.com/doserjef/Doser_etal_2020_MR-MS-RS

Trends in bird abundance differ among protected forests but not bird guilds

https://github.com/duyhlzu/GMG

Deep Spatio-Temporal Residual Networks for Citywide Crowd Flows Prediction

https://github.com/earthnet2021/earthnet-model-intercomparison-suite

EarthNet2021: A novel large-scale dataset and challenge for forecasting localized climate impacts

https://github.com/eddyhkchiu/mahalanobis_3d_multi_object_tracking

Probabilistic 3D Multi-Modal, Multi-Object Tracking for Autonomous Driving

https://github.com/edogdu/covid19

Causal Modeling of Twitter Activity During COVID-19

https://github.com/eduardoramosp/multitransformer

Multi-Transformer: A New Neural Network-Based Architecture for Forecasting S&P Volatility

https://github.com/edwardwardward/crypto_ml

Cryptocurrency Portfolio Management with Deep Reinforcement Learning

https://github.com/eeci/bsim23-voi-examples

Rationalising data collection for supporting decision making in building energy systems using Value of Information analysis

https://github.com/facebookresearch/TensorComprehensions

Tensor Comprehensions: Framework-Agnostic High-Performance Machine Learning Abstractions

https://github.com/facebookresearch/rl

RL4CO: an Extensive Reinforcement Learning for Combinatorial Optimization Benchmark

https://github.com/ferencberes/twittertennis

PyTorch Geometric Temporal: Spatiotemporal Signal Processing with Neural Machine Learning Models

https://github.com/flow-project/flow

DRLE: Decentralized Reinforcement Learning at the Edge for Traffic Light Control in the IoV

https://github.com/fminference/flexgen

Can Foundation Models Wrangle Your Data?

https://github.com/fredriko/draviz

Data Readiness Levels

https://github.com/g-u-n/pycil

RMM: Reinforced Memory Management for Class-Incremental Learning

https://github.com/gbotev/PGPortfolio

A Deep Reinforcement Learning Framework for the Financial Portfolio Management Problem

https://github.com/google/XNNPACK

Efficient Memory Management for Deep Neural Net Inference

https://github.com/gpspelle/Crowd-Counting

MRCNet: Crowd Counting and Density Map Estimation in Aerial and Ground Imagery

https://github.com/gradjitta/bertsum-streamlit

Leveraging BERT for Extractive Text Summarization on Lectures

출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.