chandler09's Stars
roboticcam/machine-learning-notes
My continuously updated Machine Learning, Probabilistic Models and Deep Learning notes and demos (2000+ slides) 我不间断更新的机器学习,概率模型和深度学习的讲义(2000+页)和视频链接
MilesCranmer/PySR
High-Performance Symbolic Regression in Python and Julia
Thinklab-SJTU/awesome-ml4co
Awesome machine learning for combinatorial optimization papers.
CMA-ES/pycma
Python implementation of CMA-ES
berkeley-abc/abc
ABC: System for Sequential Logic Synthesis and Formal Verification
OptMLGroup/VRP-RL
Reinforcement Learning for Solving the Vehicle Routing Problem
Project-Platypus/Platypus
A Free and Open Source Python Library for Multiobjective Optimization
quancore/social-lstm
Social LSTM implementation in PyTorch
CyberAgentAILab/cmaes
Python library for CMA Evolution Strategy.
MOEAFramework/MOEAFramework
A Free and Open Source Java Framework for Multiobjective Optimization
ariseff/overcoming-catastrophic
Implementation of "Overcoming catastrophic forgetting in neural networks" in Tensorflow
brain-research/guided-evolutionary-strategies
Guided Evolutionary Strategies
numbbo/coco
Numerical Black-Box Optimization Benchmarking Framework
cavalab/srbench
A living benchmark framework for symbolic regression
Evolutionary-Intelligence/pypop
PyPop7: A Pure-Python Library for POPulation-based Black-Box Optimization (BBO), especially their *Large-Scale* versions/variants (evolutionary algorithms/swarm-based optimizers/pattern search/...). [https://pypop.rtfd.io/]
xijunlee/Learning-to-Optimize-Arxiv
The repository archives papers regarding the combination of combinatorial optimization and machine learning and corresponding reading notes.
lsils/benchmarks
EPFL logic synthesis benchmarks
shivamsaboo17/Overcoming-Catastrophic-forgetting-in-Neural-Networks
Elastic weight consolidation technique for incremental learning.
dietmarwo/fast-cma-es
A Python 3 gradient-free optimization library
mbelmadani/moead-py
A Python implementation of the decomposition based multi-objective evolutionary algorithm (MOEA/D)
stokesj/EWC
TensorFlow implementation of Elastic Weight Consolidation
yashkant/Elastic-Weight-Consolidation
This is an implementation of Elastic Weight Consolidation algorithm introduced in Overcoming catastrophic forgetting in neural networks.
LDNN97/Evolutionary-Optimization-Algorithms
DE, CMA-ES, MA-ES, LM-MAES Python Implementation
moead-framework/framework
MOEA/D is a general-purpose algorithm framework. It decomposes a multi-objective optimization problem into a number of single-objective optimization sub-problems and then uses a search heuristic to optimize these sub-problems simultaneously and cooperatively.
vield/less-forgetful-nns
Demo of Elastic Weight Consolidation to allow a neural network to learn different datasets in sequence.
satuma777/evoltier
[WIP] Python implementation of evolution strategy based on Information Geometry. This library includes CMA-ES, NES, CompactGA and PBIL.
lshug/Continual-Keras
Keras-based framework for implementing continual learning methods.
Daikon-Sun/FRAIG
Functionally Reduced And-Inverter Graph
berkeley-abc/ext-hello-abc
An example for how to add an extension module to ABC without modifying ABC itself.
berkeley-abc/abc-library-cmake
An example of using ABC as a Library using CMake