Brownian diffuser
Project description
brownian-diffuser
Forward integrate torch neural networks
Similar to torchsde.sdeint
or torchdiffeq.odeint
but for vanilla neural networks as implemented by TorchNets
Example usage
BrownianDiffuser
from brownian_diffuser import BrownianDiffuser
diffuser = BrownianDiffuser()
from torch_nets import TorchNet
import torch
net = TorchNet(50, 50, [400, 400])
X0 = torch.randn([200, 50])
t = torch.Tensor([2, 4, 6])
X_pred = diffuser(net, X0, t, n_steps=40, stdev=0.5, max_steps=None, return_all=False)
X_pred.shape
torch.Size([3, 200, 50])
BrownianMotion
from brownian_diffuser import BrownianMotion
X_state = torch.randn([400, 50])
BM = BrownianMotion(X_state, stdev=0.5, n_steps=40)
Z = BM()
Z.shape
torch.Size([40, 400, 50])
Installation
pip install brownian-diffuser
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