Image de couverture de livre

SCOPED: Score-Curvature Out-of-distribution Proximity Evaluator for Diffusion

Fuente: arXiv

Enregistré dans:

Détails bibliographiques
Auteurs principaux:	Barkley, Brett, Culbertson, Preston, Fridovich-Keil, David
Format:	Preprint
Publié:	2025
Sujets:	Machine Learning
Accès en ligne:	Acceder al recurso
Tags:	Ajouter un tag Pas de tags, Soyez le premier à ajouter un tag!

Documents similaires

Scaling Pretrained Representations Enables Label-Free Out-of-Distribution Detection Without Fine-Tuning
par: Barkley, Brett, et autres
Publié: (2026)

A Forensic Analysis of Synthetic Data in RL: Diagnosing and Solving Algorithmic Failures in Model-Based Policy Optimization
par: Barkley, Brett, et autres
Publié: (2025)

Stealing That Free Lunch: Exposing the Limits of Dyna-Style Reinforcement Learning
par: Barkley, Brett, et autres
Publié: (2024)

Decomposing Control Lyapunov Functions for Efficient Reinforcement Learning
par: Lopez, Antonio, et autres
Publié: (2024)

A Recovery Guarantee for Sparse Neural Networks
par: Fridovich-Keil, Sara, et autres
Publié: (2025)

KLIP: localized distribution shift detection via KL-divergence with diffusion priors in Inverse Problems
par: Kheirandish, Alireza, et autres
Publié: (2026)

Learning to Walk from Three Minutes of Real-World Data with Semi-structured Dynamics Models
par: Levy, Jacob, et autres
Publié: (2024)

Learning responsibility allocations for multi-agent interactions: A differentiable optimization approach with control barrier functions
par: Remy, Isaac, et autres
Publié: (2024)

Beyond Scores: Proximal Diffusion Models
par: Fang, Zhenghan, et autres
Publié: (2025)

Neural Operators for Multi-Task Control and Adaptation
par: Sewell, David, et autres
Publié: (2026)

Solving Inverse Problems in Protein Space Using Diffusion-Based Priors
par: Levy, Axel, et autres
Publié: (2024)

Monotonic Transformation Invariant Multi-task Learning
par: Murthy, Surya, et autres
Publié: (2025)

Symbolic Regression on Sparse and Noisy Data with Gaussian Processes
par: Hsin, Junette, et autres
Publié: (2023)

Generalized Information Gathering Under Dynamics Uncertainty
par: Palafox, Fernando, et autres
Publié: (2026)

Diffusion Model for Manifold Data: Score Decomposition, Curvature, and Statistical Complexity
par: Zhang, Zixuan, et autres
Publié: (2026)

A Framework for Finding Local Saddle Points in Two-Player Zero-Sum Black-Box Games
par: Agarwal, Shubhankar, et autres
Publié: (2025)

Controllability in preference-conditioned multi-objective reinforcement learning
par: Molins, Pau de las Heras, et autres
Publié: (2026)

A Flow Matching Algorithm for Many-Shot Adaptation to Unseen Distributions
par: Ingebrand, Tyler, et autres
Publié: (2026)

Bayesian Inverse Games with High-Dimensional Multi-Modal Observations
par: Jain, Yash, et autres
Publié: (2026)

Data-Driven Modeling and Correction of Vehicle Dynamics
par: Ly, Nguyen, et autres
Publié: (2025)

Accurate, provable and fast polychromatic tomographic reconstruction: A variational inequality approach
par: Lou, Mengqi, et autres
Publié: (2025)

SHIELD: Safety on Humanoids via CBFs In Expectation on Learned Dynamics
par: Yang, Lizhi, et autres
Publié: (2025)

Dense Dynamics-Aware Reward Synthesis: Integrating Prior Experience with Demonstrations
par: Koprulu, Cevahir, et autres
Publié: (2024)

Meta-Learning Online Dynamics Model Adaptation in Off-Road Autonomous Driving
par: Levy, Jacob, et autres
Publié: (2025)

Deceptive Exploration in Multi-armed Bandits
par: Vurankaya, I. Arda, et autres
Publié: (2025)

Active Inverse Learning in Stackelberg Trajectory Games
par: Ward, William, et autres
Publié: (2023)

Auto-Encoding Bayesian Inverse Games
par: Liu, Xinjie, et autres
Publié: (2024)

A Multi-Fidelity Control Variate Approach for Policy Gradient Estimation
par: Liu, Xinjie, et autres
Publié: (2025)

PATE: Proximity-Aware Time series anomaly Evaluation
par: Ghorbani, Ramin, et autres
Publié: (2024)

Out-of-Sample Embedding with Proximity Data: Projection versus Restricted Reconstruction
par: Trosset, Michael W., et autres
Publié: (2025)

Enhancing Supervised Visualization through Autoencoder and Random Forest Proximities for Out-of-Sample Extension
par: Ni, Shuang, et autres
Publié: (2024)

Proximal Diffusion Neural Sampler
par: Guo, Wei, et autres
Publié: (2025)

Diffusion Attribution Score: Evaluating Training Data Influence in Diffusion Models
par: Lin, Jinxu, et autres
Publié: (2024)

Hamiltonian Neural Networks for Robust Out-of-Time Credit Scoring
par: Marín, Javier
Publié: (2024)

Mining In-distribution Attributes in Outliers for Out-of-distribution Detection
par: Lei, Yutian, et autres
Publié: (2024)

Development and Evaluation of a Learning-based Model for Real-time Haptic Texture Rendering
par: Heravi, Negin, et autres
Publié: (2022)

Score-Guided Proximal Projection: A Unified Geometric Framework for Rectified Flow Editing
par: Bansal, Vansh, et autres
Publié: (2026)

Feature Protection For Out-of-distribution Generalization
par: Tan, Lu, et autres
Publié: (2024)

Alternating Diffusion for Proximal Sampling with Zeroth Order Queries
par: Takagi, Hirohane, et autres
Publié: (2026)

Bounding Box Anomaly Scoring for simple and efficient Out-of-Distribution detection
par: Yahiaoui, Mohamed Bahi, et autres
Publié: (2026)