conftrace_

stochastic differential equation

181 papers

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Also known as

SDE

Co-occurring keywords

diffusion model (3751) stochastic gradient descent (1091) variational inference (2069) neural network (6616) gaussian process (1200) image generation (2073) generative model (2892) markov chain monte carlo (725) score-based generative model (30) diffusion process (68)

Papers

Robust SDE Parameter Estimation Under Missing Time Information Setting AAAI 2026
EPO: Diverse and Realistic Protein Ensemble Generation via Energy Preference Optimization AAAI 2026
Physics-Informed Koopman Neural Estimation of the Heston Model from High-Frequency Observations AAAI 2026
PC-Flow: Preference Alignment in Flow Matching via Classifier AAAI 2026
Model-Based Closed-Loop Control Algorithm for Stochastic Partial Differential Equation Control IJCAI 2025
Sampling and Estimation on Manifolds using the Langevin Diffusion JMLR 2025
Random ReLU Neural Networks as Non-Gaussian Processes JMLR 2025
SRMRI: A Diffusion-Based Super-resolution Framework and Open Dataset for Blind MRI Super-Resolution MIDL 2025
Learning Neural Jump Stochastic Differential Equations with Latent Graph for Multivariate Temporal Point Processes IJCAI 2025
Wasserstein Convergence Guarantees for a General Class of Score-Based Generative Models JMLR 2025
Stochastic Interpolants: A Unifying Framework for Flows and Diffusions JMLR 2025
Learning Extremely High Density Crowds as Active Matters CVPR 2025
Elucidating the Solution Space of Extended Reverse-Time SDE for Diffusion Models WACV 2025
Comprehensive Review of Neural Differential Equations for Time Series Analysis IJCAI 2025
CUNSB-RFIE: Context-Aware Unpaired Neural Schrodinger Bridge in Retinal Fundus Image Enhancement WACV 2025
SaSDim:Self-Adaptive Noise Scaling Diffusion Model for Spatial Time Series Imputation IJCAI 2024
SGD vs GD: Rank Deficiency in Linear Networks NIPS 2024
Fisher information dissipation for time-inhomogeneous stochastic differential equations JMLR 2024
Modeling Latent Neural Dynamics with Gaussian Process Switching Linear Dynamical Systems NIPS 2024
Neural McKean-Vlasov Processes: Distributional Dependence in Diffusion Processes AISTATS 2024
Taming Diffusion Prior for Image Super-Resolution with Domain Shift SDEs NIPS 2024
Exact Gradients for Stochastic Spiking Neural Networks Driven by Rough Signals NIPS 2024
On the Hyperparameters in Stochastic Gradient Descent with Momentum JMLR 2024
Causal Modeling with Stationary Diffusions AISTATS 2024
Stability and Generalizability in SDE Diffusion Models with Measure-Preserving Dynamics NIPS 2024