Cover Image

Probabilistic Trust Intervals for Out of Distribution Detection

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Singh, Gagandeep, Mishra, Ishan, Mishra, Deepak
Format:	Preprint
Published:	2021
Subjects:	Machine Learning Artificial Intelligence
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Generative Adversarial Evasion and Out-of-Distribution Detection for UAV Cyber-Attacks
by: Panda, Deepak Kumar, et al.
Published: (2025)

MLVICX: Multi-Level Variance-Covariance Exploration for Chest X-ray Self-Supervised Representation Learning
by: Singh, Azad, et al.
Published: (2024)

Dynamic LLM Routing and Selection based on User Preferences: Balancing Performance, Cost, and Ethics
by: Piskala, Deepak Babu, et al.
Published: (2025)

Data Shifts Hurt CoT: A Theoretical Study
by: Yin, Lang, et al.
Published: (2025)

mHC-GNN: Manifold-Constrained Hyper-Connections for Graph Neural Networks
by: Mishra, Subhankar
Published: (2026)

Preventing Curriculum Collapse in Self-Evolving Reasoning Systems
by: Mishra, Vaibhav
Published: (2026)

DECODE: Data-driven Energy Consumption Prediction leveraging Historical Data and Environmental Factors in Buildings
by: Mishra, Aditya, et al.
Published: (2023)

Out-of-Distribution Detection using Counterfactual Distance
by: Stoica, Maria, et al.
Published: (2025)

DEEDEE: Fast and Scalable Out-of-Distribution Dynamics Detection
by: Aljaafari, Tala, et al.
Published: (2025)

SGOOD: Substructure-enhanced Graph-Level Out-of-Distribution Detection
by: Ding, Zhihao, et al.
Published: (2023)

Mitigating Overconfidence in Out-of-Distribution Detection by Capturing Extreme Activations
by: Azizmalayeri, Mohammad, et al.
Published: (2024)

Taming False Positives in Out-of-Distribution Detection with Human Feedback
by: Vishwakarma, Harit, et al.
Published: (2024)

GOODAT: Towards Test-time Graph Out-of-Distribution Detection
by: Wang, Luzhi, et al.
Published: (2024)

Feature Bank Enhancement for Distance-based Out-of-Distribution Detection
by: Liu, Yuhang, et al.
Published: (2025)

ConjNorm: Tractable Density Estimation for Out-of-Distribution Detection
by: Peng, Bo, et al.
Published: (2024)

Rectified Lagrangian for Out-of-Distribution Detection in Modern Hopfield Networks
by: Moriai, Ryo, et al.
Published: (2025)

Out-of-Distribution Detection with a Single Unconditional Diffusion Model
by: Heng, Alvin, et al.
Published: (2024)

Rethinking Out-of-Distribution Detection for Reinforcement Learning: Advancing Methods for Evaluation and Detection
by: Nasvytis, Linas, et al.
Published: (2024)

Trust Regions for Explanations via Black-Box Probabilistic Certification
by: Dhurandhar, Amit, et al.
Published: (2024)

Mechanistic Interpretability of Brain-to-Speech Models Across Speech Modes
by: Maghsoudi, Maryam, et al.
Published: (2026)

Schreier-Coset Graph Propagation
by: Mishra, Aryan, et al.
Published: (2025)

QUAIL: Quantization Aware Unlearning for Mitigating Misinformation in LLMs
by: Mishra, Himanshu, et al.
Published: (2026)

Towards Metric-Faithful Neural Graph Matching
by: Shivottam, Jyotirmaya, et al.
Published: (2026)

Adaptive Scoring and Thresholding with Human Feedback for Robust Out-of-Distribution Detection
by: Yamada, Daisuke, et al.
Published: (2025)

Universal Black-Box Reward Poisoning Attack against Offline Reinforcement Learning
by: Xu, Yinglun, et al.
Published: (2024)

Mechanistic Interpretability of GPT-like Models on Summarization Tasks
by: Mishra, Anurag
Published: (2025)

Dissecting Chronos: Sparse Autoencoders Reveal Causal Feature Hierarchies in Time Series Foundation Models
by: Mishra, Anurag
Published: (2026)

Multi-Layer Confidence Scoring for Detection of Out-of-Distribution Samples, Adversarial Attacks, and In-Distribution Misclassifications
by: Capelli, Lorenzo, et al.
Published: (2025)

Client Contribution Normalization for Enhanced Federated Learning
by: Kundalwal, Mayank Kumar, et al.
Published: (2024)

Uncertainty Quantification via Stable Distribution Propagation
by: Petersen, Felix, et al.
Published: (2024)

Pseudo-label Induced Subspace Representation Learning for Robust Out-of-Distribution Detection
by: Azad, Tarhib Al, et al.
Published: (2025)

Perturb-and-Compare Approach for Detecting Out-of-Distribution Samples in Constrained Access Environments
by: Lee, Heeyoung, et al.
Published: (2024)

Combine and Conquer: A Meta-Analysis on Data Shift and Out-of-Distribution Detection
by: Dadalto, Eduardo, et al.
Published: (2024)

Learning to Explore: Policy-Guided Outlier Synthesis for Graph Out-of-Distribution Detection
by: Sun, Li, et al.
Published: (2026)

Adaptive Dual-Weighting Framework for Federated Learning via Out-of-Distribution Detection
by: Ling, Zhiwei, et al.
Published: (2026)

Sparsity and Out-of-Distribution Generalization
by: Aaronson, Scott, et al.
Published: (2026)

Entropic Projection Alignment: Estimating, Explaining, and Improving Model Performance Under Distribution Shift
by: Amoukou, Salim I., et al.
Published: (2026)

A Fragile Number Sense: Probing the Elemental Limits of Numerical Reasoning in LLMs
by: Rahman, Roussel, et al.
Published: (2025)

Certifying Knowledge Comprehension in LLMs
by: Chaudhary, Isha, et al.
Published: (2024)

Smart IoT-Based Wearable Device for Detection and Monitoring of Common Cow Diseases Using a Novel Machine Learning Technique
by: Mishra, Rupsa Rani, et al.
Published: (2026)