langevin-mc

There are 0 repository under langevin-mc topic.

MI2G / sampling-tutorials
Imaging Inverse Problems and Bayesian Computation - Python tutorials to learn about (accelerated) sampling for uncertainty quantification and other advanced inferences
bayesian-inference bayesian-inverse-problems deblurring inverse-problems langevin-mc mcmc mcmc-sampling sampling total-variation
Language:Jupyter Notebook 7
fabienpesquerel / MCMC
Python implementation (from scratch) of some MCMC samplers that can leverage pyTorch's autodifferentiation (with examples).
mcmc mcmc-sampler computational-statistics metropolis-monte-carlo langevin-mc mcmc-pytorch
Language:Python 4
hmishfaq / LMC-LSVI
The official code release for Provable and Practical: Efficient Exploration in Reinforcement Learning via Langevin Monte Carlo, ICLR 2024.
exploration-exploitation langevin-mc reinforcement-learning thompson-sampling
Language:Python 4
panxulab / LSVI-ASE
The official code release for "More Efficient Randomized Exploration for Reinforcement Learning via Approximate Sampling", Reinforcement Learning Conference (RLC) 2024
exploration-exploitation langevin-dynamics langevin-mc reinforcement-learning thompson-sampling
Language:Python 2
JuliaEpi / MathepiaInference.jl
Bayesian inference tools. Including state-of-the-art inference methods: HMC family, ABC family, Data assimilation, and so on. Part of Mathepia.jl
monto-carlo mcmc mcmc-sampler abc approximate-bayesian-computation likelihood-free-inference simulation-based-inference data-assimilation langevin-mc
Language:Julia 1
nandahkrishna / RNNReactivation
Code for "Sufficient conditions for offline reactivation in recurrent neural networks" (ICLR 2024)
attractor-learning attractor-network computational-neuroscience diffusion langevin-dynamics langevin-mc learning path-integration pytorch reactivation recurrent-networks recurrent-neural-nets recurrent-neural-network recurrent-neural-networks replay rnn spatial-navigation head-direction iclr iclr2024
0
SmBito / Hybrid_Monte_Carlo_University_Project_2018
Comparing the performance of Hybrid MC, Langevin MC and a simple random walk
hybrid-mc langevin-mc simple-random-walk artificial-intelligence
Language:Jupyter Notebook 0

langevin-mc

MI2G / sampling-tutorials

fabienpesquerel / MCMC

hmishfaq / LMC-LSVI

panxulab / LSVI-ASE

JuliaEpi / MathepiaInference.jl

nandahkrishna / RNNReactivation

SmBito / Hybrid_Monte_Carlo_University_Project_2018