Efficient Training of Neural SDEs Using Stochastic Optimal Control
Fuente:
arXiv
Saved in:
| Main Authors: | Daems, Rembert, Opper, Manfred, Crevecoeur, Guillaume, Birdal, Tolga |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Variational Inference for Lévy Process-Driven SDEs via Neural Tilting
by: Kindap, Yaman, et al.
Published: (2026)
by: Kindap, Yaman, et al.
Published: (2026)
Fractional Diffusion Bridge Models
by: Nobis, Gabriel, et al.
Published: (2025)
by: Nobis, Gabriel, et al.
Published: (2025)
KeyCLD: Learning Constrained Lagrangian Dynamics in Keypoint Coordinates from Images
by: Daems, Rembert, et al.
Published: (2022)
by: Daems, Rembert, et al.
Published: (2022)
Neural Laplace for learning Stochastic Differential Equations
by: Carrel, Adrien
Published: (2024)
by: Carrel, Adrien
Published: (2024)
HOG-Diff: Higher-Order Guided Diffusion for Graph Generation
by: Huang, Yiming, et al.
Published: (2025)
by: Huang, Yiming, et al.
Published: (2025)
Explicit Density Approximation for Neural Implicit Samplers Using a Bernstein-Based Convex Divergence
by: de Frutos, José Manuel, et al.
Published: (2025)
by: de Frutos, José Manuel, et al.
Published: (2025)
Bridging discrete and continuous state spaces: Exploring the Ehrenfest process in time-continuous diffusion models
by: Winkler, Ludwig, et al.
Published: (2024)
by: Winkler, Ludwig, et al.
Published: (2024)
Beyond Propagation of Chaos: A Stochastic Algorithm for Mean Field Optimization
by: Tankala, Chandan, et al.
Published: (2025)
by: Tankala, Chandan, et al.
Published: (2025)
Neural Expectation Operators
by: Qi, Qian
Published: (2025)
by: Qi, Qian
Published: (2025)
Quantitative CLTs in Deep Neural Networks
by: Favaro, Stefano, et al.
Published: (2023)
by: Favaro, Stefano, et al.
Published: (2023)
Feature Learning Dynamics in Infinite-Depth Neural Networks
by: Yao, Zihan, et al.
Published: (2025)
by: Yao, Zihan, et al.
Published: (2025)
Neural Network Parameter-optimization of Gaussian pmDAGs
by: Saremi, Mehrzad
Published: (2023)
by: Saremi, Mehrzad
Published: (2023)
Neural Thermodynamic Laws for Large Language Model Training
by: Liu, Ziming, et al.
Published: (2025)
by: Liu, Ziming, et al.
Published: (2025)
Neural Brownian Motion
by: Qi, Qian
Published: (2025)
by: Qi, Qian
Published: (2025)
Large Learning Rates Simultaneously Achieve Robustness to Spurious Correlations and Compressibility
by: Barsbey, Melih, et al.
Published: (2025)
by: Barsbey, Melih, et al.
Published: (2025)
Adversarial Attacks Leverage Interference Between Features in Superposition
by: Stevinson, Edward, et al.
Published: (2025)
by: Stevinson, Edward, et al.
Published: (2025)
Generalization at the Edge of Stability
by: Tuci, Mario, et al.
Published: (2026)
by: Tuci, Mario, et al.
Published: (2026)
Optimal Symmetries in Binary Classification
by: Ngairangbam, Vishal S., et al.
Published: (2024)
by: Ngairangbam, Vishal S., et al.
Published: (2024)
On Training-Test (Mis)alignment in Unsupervised Combinatorial Optimization: Observation, Empirical Exploration, and Analysis
by: Bu, Fanchen, et al.
Published: (2025)
by: Bu, Fanchen, et al.
Published: (2025)
Learning Chaotic Systems and Long-Term Predictions with Neural Jump ODEs
by: Krach, Florian, et al.
Published: (2024)
by: Krach, Florian, et al.
Published: (2024)
Efficient Risk-sensitive Planning via Entropic Risk Measures
by: Marthe, Alexandre, et al.
Published: (2025)
by: Marthe, Alexandre, et al.
Published: (2025)
Causal Effect Identification in Heterogeneous Environments from Higher-Order Moments
by: Kivva, Yaroslav, et al.
Published: (2025)
by: Kivva, Yaroslav, et al.
Published: (2025)
A Unified Theory of $θ$-Expectations
by: Qi, Qian
Published: (2025)
by: Qi, Qian
Published: (2025)
Nonparametric Identification of Latent Concepts
by: Zheng, Yujia, et al.
Published: (2025)
by: Zheng, Yujia, et al.
Published: (2025)
Greedy Selection under Independent Increments: A Toy Model Analysis
by: Yang, Huitao
Published: (2025)
by: Yang, Huitao
Published: (2025)
A Mean-Field Theory of $Θ$-Expectations
by: Qi, Qian
Published: (2025)
by: Qi, Qian
Published: (2025)
Advancing Deep Learning through Probability Engineering: A Pragmatic Paradigm for Modern AI
by: Zhang, Jianyi
Published: (2025)
by: Zhang, Jianyi
Published: (2025)
Deep Conditional Measure Quantization
by: Turinici, Gabriel
Published: (2023)
by: Turinici, Gabriel
Published: (2023)
$α$-TCAV: A Unified Framework for Testing with Concept Activation Vectors
by: Schnoor, Ekkehard, et al.
Published: (2026)
by: Schnoor, Ekkehard, et al.
Published: (2026)
Representative Arm Identification: A fixed confidence approach to identify cluster representatives
by: Gharat, Sarvesh, et al.
Published: (2024)
by: Gharat, Sarvesh, et al.
Published: (2024)
Note on Martingale Theory and Applications
by: Zou, Xiandong
Published: (2026)
by: Zou, Xiandong
Published: (2026)
Soft-to-Hard Routing in Sparse Mixture-of-Experts Models
by: Rastegar, Reza
Published: (2026)
by: Rastegar, Reza
Published: (2026)
Generalisation of Total Uncertainty in AI: A Theoretical Study
by: Shariatmadar, Keivan
Published: (2024)
by: Shariatmadar, Keivan
Published: (2024)
Generalized Gaussian Temporal Difference Error for Uncertainty-aware Reinforcement Learning
by: Kim, Seyeon, et al.
Published: (2024)
by: Kim, Seyeon, et al.
Published: (2024)
On the Equivalence of Random Network Distillation, Deep Ensembles, and Bayesian Inference
by: Zanger, Moritz A., et al.
Published: (2026)
by: Zanger, Moritz A., et al.
Published: (2026)
On the Interaction of Compressibility and Adversarial Robustness
by: Barsbey, Melih, et al.
Published: (2025)
by: Barsbey, Melih, et al.
Published: (2025)
Multi-hop Upstream Anticipatory Traffic Signal Control with Deep Reinforcement Learning
by: Li, Xiaocan, et al.
Published: (2024)
by: Li, Xiaocan, et al.
Published: (2024)
Z-Error Loss for Training Neural Networks
by: Godin, Guillaume
Published: (2025)
by: Godin, Guillaume
Published: (2025)
Variational Smoothing and Inference for SDEs from Sparse Data with Dynamic Neural Flows
by: Wang, Yu, et al.
Published: (2026)
by: Wang, Yu, et al.
Published: (2026)
CuMPerLay: Learning Cubical Multiparameter Persistence Vectorizations
by: Korkmaz, Caner, et al.
Published: (2025)
by: Korkmaz, Caner, et al.
Published: (2025)
Similar Items
-
Variational Inference for Lévy Process-Driven SDEs via Neural Tilting
by: Kindap, Yaman, et al.
Published: (2026) -
Fractional Diffusion Bridge Models
by: Nobis, Gabriel, et al.
Published: (2025) -
KeyCLD: Learning Constrained Lagrangian Dynamics in Keypoint Coordinates from Images
by: Daems, Rembert, et al.
Published: (2022) -
Neural Laplace for learning Stochastic Differential Equations
by: Carrel, Adrien
Published: (2024) -
HOG-Diff: Higher-Order Guided Diffusion for Graph Generation
by: Huang, Yiming, et al.
Published: (2025)