ordinary differential equation

Training Generative Adversarial Networks by Solving Ordinary Differential Equations NeurIPS 2020 Weak Form Generalized Hamiltonian Learning NeurIPS 2020 A Block Coordinate Descent Proximal Method for Simultaneous Filtering and Parameter Estimation ICML 2019 Acceleration via Symplectic Discretization of High-Resolution Differential Equations NeurIPS 2019 ANODEV2: A Coupled Neural ODE Framework NeurIPS 2019 AntisymmetricRNN: A Dynamical System View on Recurrent Neural Networks ICLR 2019 A Solvable High-Dimensional Model of GAN NeurIPS 2019 Efficient Amortised Bayesian Inference for Hierarchical and Nonlinear Dynamical Systems ICML 2019 Fast and Robust Shortest Paths on Manifolds Learned from Data AISTATS 2019 FFJORD: Free-Form Continuous Dynamics for Scalable Reversible Generative Models ICLR 2019 GOODE: A Gaussian Off-The-Shelf Ordinary Differential Equation Solver ICML 2019 Latent Ordinary Differential Equations for Irregularly-Sampled Time Series NeurIPS 2019 Legendre Memory Units: Continuous-Time Representation in Recurrent Neural Networks NeurIPS 2019 ODE2VAE: Deep generative second order ODEs with Bayesian neural networks NeurIPS 2019 ODE-Inspired Network Design for Single Image Super-Resolution CVPR 2019 Shadowing Properties of Optimization Algorithms NeurIPS 2019 Constraining the Dynamics of Deep Probabilistic Models ICML 2018 Direct Runge-Kutta Discretization Achieves Acceleration NeurIPS 2018 Fast Gradient-Based Methods with Exponential Rate: A Hybrid Control Framework ICML 2018 Implicit Probabilistic Integrators for ODEs NeurIPS 2018 Learning unknown ODE models with Gaussian processes ICML 2018 Multiphase MCMC Sampling for Parameter Inference in Nonlinear Ordinary Differential Equations AISTATS 2018 Neural Ordinary Differential Equations NeurIPS 2018 Scalable Variational Inference for Dynamical Systems NeurIPS 2017 Probabilistic Linear Multistep Methods NeurIPS 2016