Interactive Scientific-ML Playgrounds

Physics-informed and Neural-ODE demos that train live in your browser — no install. Inverse kinetics with maximum-likelihood uncertainty (KINNs / rKINNs), Neural-ODE structure discovery from noisy data, and more.

PINN · Inverse problem

Kinetics-Informed Neural Networks

Recover the rate constants of a known reaction from noisy, sparse transients — a physics-informed inverse problem with maximum-likelihood uncertainty, no tuned weights.
Neural ODE · Discovery

Neural ODE: discover the Lotka–Volterra rate law 🐇 🐺

Learn the unknown Lotka–Volterra predator–prey vector field through the integrator, then recover its structure: black-box with physics priors, a hybrid power-law network, and sparse discovery with learnable exponents (SINDy inside the Neural ODE).
Neural ODE · Pharmacokinetics

Pharmacokinetics: a non-negative mean-variance Neural ODE 💊 🩸

Learn the unknown absorption-then-elimination rate law of a drug from sparse, noisy blood samples through the integrator (discrete adjoint), kept non-negative by construction. As a mean-variance Neural ODE it predicts its own plus/minus sigma error bar. Real theophylline data, runs in the browser.