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Implementations of different neural network pruning techniques
A Novel Approach for Neural Network Compression
Simple (and cheap!) neural network uncertainty estimation
Codes for "Learning Sparse Sharing Architectures for Multiple Tasks"
A differentiable PDE solving framework for machine learning
MOMPA: a high performance multi-objective optimizer based on marine predator algorithm
This is the code of QQLMPA, which is proposed in <A quasi-opposition learning and Q-learning based marine predators algorithm for global continuous optimization problems>
Python module for CEC 2017 single objective optimization test function suite.
🚀AI拟声: 5秒内克隆您的声音并生成任意语音内容 Clone a voice in 5 seconds to generate arbitrary speech in real-time
Implementations of IQL, QMIX, VDN, COMA, QTRAN, MAVEN, CommNet, DyMA-CL, and G2ANet on SMAC, the decentralised micromanagement scenario of StarCraft II
MPA is a new metaheuristic for continuous optimization inspired by nature
An elegant PyTorch deep reinforcement learning library.
Approximate BNN using HMC(hamiltorch) or SGHMC(bohamiann)
code for the paper "Stein Variational Gradient Descent (SVGD): A General Purpose Bayesian Inference Algorithm"
All You Need is a Good Functional Prior for Bayesian Deep Learning (JMLR 2022)
A Python package for approximate Bayesian inference and optimization using Gaussian processes
Data and code to accompany paper "Accelerating sequential Monte Carlo with surrogate likelihoods"
🦁 Lion, new optimizer discovered by Google Brain using genetic algorithms that is purportedly better than Adam(w), in Pytorch
🐦 Opytimizer is a Python library consisting of meta-heuristic optimization algorithms.
Kernel Density Estimation: accelerated, multi-dimensional, and adaptive bandwidth
PyTorch implementation of Bidirectional Monte Carlo, Annealed Importance Sampling, and Hamiltonian Monte Carlo.
Bayesian Physics-Informed Neural Networks for Uncertainty Quantification in Inverse Eikonal problem