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By interpreting the forward dynamics of the latent representation of neural networks as an ordinary differential equation, Neural Ordinary Differential Equation (Neural ODE) emerged as an effective framework for modeling a system dynamics in the continuous time domain.
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Neural stochastic differential equations: Deep latent gaussian models in the diffusion limit
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Equivariant Flows: sampling configurations for multi-body systems with symmetric energies
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Graph Neural Ordinary Differential Equations
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Theory of impulsive differential equations , volume 6
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The effectiveness of antiterrorism policies: A vector-autoregression-intervention analysis
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Scalable Gradients for Stochastic Differential Equations
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The effectiveness of music as an intervention for hospital patients: a systematic review
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Massaroli, S.; Poli, M.; Park, J.; Yamashita, A.; and Asama, H. 2020b · 2002
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Segmented regression analysis of interrupted time series studies in medication use research
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Cranmer, M.; Greydanus, S.; Hoyer, S.; Battaglia, P.; Spergel, D.; and Ho, S. 2020 · 2003
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Massaroli, S.; Poli, M.; Bin, M.; Park, J.; Yamashita, A.; and Asama, H. 2020a · 2003
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Hypersolvers: Toward Fast Continuous-Depth Models
Poli, M.; Massaroli, S.; Yamashita, A.; Asama, H.; and Park, J. 2020 · 2007
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Design and analysis of timeseries experiments
Glass, G. V.; Willson, V. L.; and Gottman, J. M. 2008 · 2008
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Causality
Pearl, J. 2009 · 2009
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Reliable decision support using counterfactual models
Schulam, P.; and Saria, S. 2017 · 2017
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Treatment-response models for counterfactual reasoning with continuous-time, continuous-valued interventions
Soleimani, H.; Subbaswamy, A.; and Saria, S. 2017 · 2017
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Double continuum limit of deep neural networks
Sonoda, S.; and Murata, N. 2017 · 2017
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Recurrent neural networks for multivariate time series with missing values
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Neural ordinary differential equations
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Forecasting treatment responses over time using recurrent marginal structural networks
Lim, B. 2018 · 2018
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Patient subtyping via time-aware LSTM networks
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Multi-level residual networks from dynamical systems view
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Stable architectures for deep neural networks
Haber, E.; and Ruthotto, L. 2017 · 2017
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The eICU Collaborative Research Database, a freely available multi-center database for critical care research
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Convolutional neural networks combined with runge-kutta methods
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De Brouwer, E.; Simm, J.; Arany, A.; and Moreau, Y. 2019 · 2019
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Hamiltonian neural networks
Greydanus, S.; Dzamba, M.; and Yosinski, J. 2019 · 2019
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Neural jump stochastic differential equations
Jia, J.; and Benson, A. R. 2019 · 2019
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Latent Ordinary Differential Equations for Irregularly-Sampled Time Series
Rubanova, Y.; Chen, T. Q.; and Duvenaud, D. K. 2019 · 2019
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ODE2VAE: Deep generative second order ODEs with Bayesian neural networks
Yildiz, C.; Heinonen, M.; and Lahdesmaki, H. 2019 · 2019
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Estimating counterfactual treatment outcomes over time through adversarially balanced representations
Bica, I.; Alaa, A. M.; Jordon, J.; and van der Schaar, M. 2020 · 2020
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