only-changer's Stars
overleaf/overleaf
A web-based collaborative LaTeX editor
higgsfield-ai/higgsfield
Fault-tolerant, highly scalable GPU orchestration, and a machine learning framework designed for training models with billions to trillions of parameters
yangxue0827/RotationDetection
This is a tensorflow-based rotation detection benchmark, also called AlphaRotate.
kaixindelele/DRLib
DRLib:a Concise Deep Reinforcement Learning Library, Integrating HER, PER and D2SR for Almost Off-Policy RL Algorithms.
Hanjun-Dai/graph_comb_opt
Implementation of "Learning Combinatorial Optimization Algorithms over Graphs"
jackguagua/awesome-nas-papers
Awesome Neural Architecture Search Papers
huawei-noah/xingtian
xingtian is a componentized library for the development and verification of reinforcement learning algorithms
chaitjo/graph-convnet-tsp
Code for the paper 'An Efficient Graph Convolutional Network Technique for the Travelling Salesman Problem' (INFORMS Annual Meeting Session 2019)
rlcode/per
Prioritized Experience Replay (PER) implementation in PyTorch
VITA-Group/Open-L2O
Open-L2O: A Comprehensive and Reproducible Benchmark for Learning to Optimize Algorithms
Thinklab-SJTU/CSL_RetinaNet_Tensorflow
Code for ECCV 2020 paper: Arbitrary-Oriented Object Detection with Circular Smooth Label
uber-research/ape-x
This repo replicates the results Horgan et al obtained in "Distributed Prioritized Experience Replay"
Doragd/Awesome-Paper-List
A curated list of repositories in which many NLP/CV/ML papers and related area resources are collected.
yunshengb/SimGNN
Spider-scnu/TSP
alibaba/drl_binpacking
3D bin packing is a classical and challenging combinatorial optimization problem in logistics and production systems. An effective bin packing algorithm means the reduction of total packing cost and increase in utilization of resources. Because the cost of packing materials, which is mainly determined by their surface area, occupies the most part of packing cost, and in many real business scenarios there is no bin with fixed size, so AI Department of Cainiao proposed a new type of 3D bin packing problem. The objective of this new type of 3D bin packing problem is to pack all items into a bin with minimized surface area. And a DRL method based on the sequence-to-sequence model is proposed to solve the problem. This is the research paper link: https://arxiv.org/abs/1708.05930. Source code of this method can be found in the project.
tomdbar/eco-dqn
Implementation of ECO-DQN as reported in "Exploratory Combinatorial Optimization with Reinforcement Learning".
The-OpenROAD-Project/TritonRoute
UCSD Detailed Router
CityBrainChallenge/KDDCup2021-CityBrainChallenge-starter-kit
martius-lab/CombOptNet
Source code for the Paper: CombOptNet: Fit the Right NP-Hard Problem by Learning Integer Programming Constraints}
Juzhan/TAP-Net
TAP-Net: Transport-and-Pack using Reinforcement Learning
princeton-vl/PackIt
Code for reproducing results in ICML 2020 paper "PackIt: A Virtual Environment for Geometric Planning"
JHL-HUST/VSR-LKH
Combining Reinforcement Learning with Lin-Kernighan-Helsgaun Algorithm for the Traveling Salesman Problem
scottemmons/sgm
Sparse Graphical Memory for Robust Planning
xinkang/fgm
omurammm/apex_dqn
EDAAC/EDAAC
EDA Analytics Central
huangqx/NeurIPS19_Cycle
Lyken17/Echoo
Let your program echo to you.
huangyf530/DocumentSearch
Big Homework for Search Engine Course