A brief study conducted as a part of major "Applied mathematics and computer science" at the HSE University.
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Updated
Apr 25, 2022 - Python
A brief study conducted as a part of major "Applied mathematics and computer science" at the HSE University.
Using Neural ODEs to fit a networked UIV model to an SIR model of an epidemic.
A ReCoDE Project Introducing Neural Ordinary Differential Equations starting from ODE theory, working through differentiable implementations of integrators, and finally incorporating neural networks into the solution.
Thesis repository on neural ordinary differential equations used for coarse-graining molecular dynamics
SIGIR'2024: ReCODE: Modeling Repeat Consumption with Neural ODE
First two problems of my Master's Thesis on Coarse-Graining of Molecular Dynamics with Neural Ordinary Differential Equations
Putting [A]NODEs ([Augmented] Neural ODEs) to work, for Time Series prediction and simulation
neural ordinary differential equations for undergraduate students
I created a Graph Neural Ordinary Differential Equation (GNODE) for modeling Newtonian gravity.
Parallel-in-time integration of Neural ODEs with reduced basis approximation
Approximately Bayesian Ensembling for Parameterized Neural ODEs.
Experimenting with Neural Ordinary Differential Equations (NODE)
Reimplementations of some normalizing flow algorithms using tensorflow 2.1 and tensorflow probability 0.9
Kinetics-Constrained Neural Ordinary Differential Equations (KCNODE) that can be trained even with small data
Graph neural ordinary differential equations
Adversarially Robust Prototypical Few-shot Segmentation with Neural-ODEs
Climate Modeling with Neural Diffusion Equation, ICDM'21
Code and figures for "Neural network differential equations for ion channel modelling".
Neural Ordinary Differential Equations for Inverse Kinematics
Code accompanying paper "Input-to-State Stable Neural Ordinary Differential Equations with Applications to Transient Modeling of Circuits" at L4DC 2022.
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