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Non-adversarial Training of Neural SDEs with Signature Kernel Scores
9/9 checkable references clean · checked 2026-08-02
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resolves10.1137/19M1254489
A Stochastic Partial Differential Equation Model for Limit Order Book Dynamics
The 40 references without a DOI — listed, not checked
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no DOI — not checkedLearning to simulate realistic limit order book markets from data as a world agent
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no DOI — not checkedNew directions in the applications of rough path theory
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no DOI — not checkedLimit order books, diffusion approximations and reflected spdes: from microscopic to macroscopic models
no DOI — not checkedProbability distribution in the sabr model of stochastic volatility
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no DOI — not checkedDeep signature transforms
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no DOI — not checkedNeural controlled differential equations for irregular time series
no DOI — not checkedSiggpde: Scaling sparse gaussian processes on sequential data
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no DOI — not checkedGenerative moment matching networks
no DOI — not checkedScalable gradients and variational inference for stochastic differential equations
no DOI — not checkedOn the choice of interpolation scheme for neural cdes
no DOI — not checkedChoosing a strictly proper scoring rule
no DOI — not checkedNMK + 18] Adamantios Ntakaris, Martin Magris, Juho Kanniainen, Moncef Gabbouj, and Alexandros Iosifidis. Benchmark dataset for mid-price forecasting of limit order book data with machine learning methods
no DOI — not checkedSig-wasserstein gans for time series generation
no DOI — not checkedVariational inference for stochastic differential equations
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no DOI — not checkedThe lob recreation model: Predicting the limit order book from taq history using an ordinary differential equation recurrent neural network
no DOI — not checkedKernel distribution embeddings: Universal kernels, characteristic kernels and kernel metrics on distributions
no DOI — not checkedNeural stochastic pdes: Resolution-invariant learning of continuous spatiotemporal dynamics
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no DOI — not checkedGet real: Realism metrics for robust limit order book market simulations
no DOI — not checkedScore-based generative modeling in latent space
no DOI — not checkedA kernel two-sample test for functional data
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