KYMiao

Accelerating-Neural-ODEs

Code for ICML submission: How Deep Do We Need

Kalman-and-Bayesian-Filters-in-Python

Kalman Filter book using Jupyter Notebook. Focuses on building intuition and experience, not formal proofs. Includes Kalman filters,extended Kalman filters, unscented Kalman filters, particle filters, and more. All exercises include solutions.

KYMiao.github.io

L4DC_Neural_ODEs_Observer

page for longer version of L4DC paper

torchdiffeq

Differentiable ODE solvers with full GPU support and O(1)-memory backpropagation.

torchdyn

A PyTorch library entirely dedicated to neural differential equations, implicit models and related numerical methods.

KYMiao/L4DC_Neural_ODEs_Observer

page for longer version of L4DC paper

KYMiao/Kalman-and-Bayesian-Filters-in-Python

Kalman Filter book using Jupyter Notebook. Focuses on building intuition and experience, not formal proofs. Includes Kalman filters,extended Kalman filters, unscented Kalman filters, particle filters, and more. All exercises include solutions.

KYMiao/Accelerating-Neural-ODEs

Code for ICML submission: How Deep Do We Need

KYMiao/KYMiao.github.io

KYMiao/torchdiffeq

Differentiable ODE solvers with full GPU support and O(1)-memory backpropagation.

KYMiao/torchdyn

A PyTorch library entirely dedicated to neural differential equations, implicit models and related numerical methods.