Imagen de Portada

Not all uncertainty is alike: volatility, stochasticity, and exploration

Fuente: arXiv

Guardado en:

Detalles Bibliográficos
Autor principal:	Piray, Payam
Formato:	Preprint
Publicado:	2026
Materias:	Artificial Intelligence
Acceso en línea:	Acceder al recurso
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

Ejemplares similares

ASR: Attention-alike Structural Re-parameterization
por: Zhong, Shanshan, et al.
Publicado: (2023)

Is 'Hope' a person or an idea? A pilot benchmark for NER: comparing traditional NLP tools and large language models on ambiguous entities
por: Latifi, Payam
Publicado: (2025)

DreamerV3-XP: Optimizing exploration through uncertainty estimation
por: Bierling, Lukas, et al.
Publicado: (2025)

Intelligent prospector v2.0: exploration drill planning under epistemic model uncertainty
por: Mern, John, et al.
Publicado: (2024)

Do great minds think alike? Investigating Human-AI Complementarity in Question Answering with CAIMIRA
por: Gor, Maharshi, et al.
Publicado: (2024)

Graph Neural Networks in Multi-Omics Cancer Research: A Structured Survey
por: Zohari, Payam, et al.
Publicado: (2025)

AI Models for Depressive Disorder Detection and Diagnosis: A Review
por: Aleagha, Dorsa Macky, et al.
Publicado: (2025)

Bilinear Fuzzy Genetic Algorithm and Its Application on the Optimum Design of Steel Structures with Semi-rigid Connections
por: Farahmand-Tabar, Salar, et al.
Publicado: (2024)

The future of AI in critical mineral exploration
por: Caers, Jef
Publicado: (2025)

From Federated Learning to X-Learning: Breaking the Barriers of Decentrality Through Random Walks
por: Salihovic, Allan, et al.
Publicado: (2025)

Two-Stage Representation Learning for Analyzing Movement Behavior Dynamics in People Living with Dementia
por: Cui, Jin, et al.
Publicado: (2025)

Analyzing Patient Daily Movement Behavior Dynamics Using Two-Stage Encoding Model
por: Cui, Jin, et al.
Publicado: (2025)

The unification process of databases of categories from all Specific Artificial Intelligences for Artificial Research by Application
por: García Pedraza, Rubén
Publicado: (2025)

Heuristics and Biases in AI Decision-Making: Implications for Responsible AGI
por: Saeedi, Payam, et al.
Publicado: (2024)

Permutative redundancy and uncertainty of the objective in deep learning
por: Glukhov, Vacslav
Publicado: (2024)

Improving reasoning at inference time via uncertainty minimisation
por: Legrand, Nicolas, et al.
Publicado: (2026)

The challenge of uncertainty quantification of large language models in medicine
por: Atf, Zahra, et al.
Publicado: (2025)

Representations of epistemic uncertainty and awareness in data-driven strategies
por: Angelelli, Mario, et al.
Publicado: (2021)

A Novel Framework for Automated Warehouse Layout Generation
por: Shahroudnejad, Atefeh, et al.
Publicado: (2024)

Epistemically-guided forward-backward exploration
por: Urpí, Núria Armengol, et al.
Publicado: (2025)

AI-as-exploration: Navigating intelligence space
por: Mollo, Dimitri Coelho
Publicado: (2024)

What are the odds? Risk and uncertainty about AI existential risk
por: Grossi, Marco
Publicado: (2025)

Ensemble based approach to quantifying uncertainty of LLM based classifications
por: Rajamohan, Srijith, et al.
Publicado: (2025)

Enabling Regional Explainability by Automatic and Model-agnostic Rule Extraction
por: Chen, Yu, et al.
Publicado: (2024)

REL: Working out is all you need
por: Simonds, Toby, et al.
Publicado: (2024)

Self-supervised network distillation: an effective approach to exploration in sparse reward environments
por: Pecháč, Matej, et al.
Publicado: (2023)

Online inductive learning from answer sets for efficient reinforcement learning exploration
por: Veronese, Celeste, et al.
Publicado: (2025)

GUI-explorer: Autonomous Exploration and Mining of Transition-aware Knowledge for GUI Agent
por: Xie, Bin, et al.
Publicado: (2025)

Fairness under uncertainty in sequential decisions
por: Lee, Michelle Seng Ah, et al.
Publicado: (2026)

Learning controllable dynamics through informative exploration
por: Loxley, Peter N., et al.
Publicado: (2025)

The impact of intrinsic rewards on exploration in Reinforcement Learning
por: Kayal, Aya, et al.
Publicado: (2025)

Narrative Studio: Visual narrative exploration using LLMs and Monte Carlo Tree Search
por: Ghaffari, Parsa, et al.
Publicado: (2025)

Continual uncertainty learning
por: Yonezawa, Heisei, et al.
Publicado: (2026)

Propaganda is all you need
por: Kronlund-Drouault, Paul
Publicado: (2024)

Beyond checkmate: exploring the creative chokepoints in AI text
por: Tripto, Nafis Irtiza, et al.
Publicado: (2025)

Compression is all you need: Modeling Mathematics
por: Aksenov, Vitaly, et al.
Publicado: (2026)

Comparative reversal learning reveals rigid adaptation in LLMs under non-stationary uncertainty
por: Wang, Haomiaomiao, et al.
Publicado: (2026)

Multi-Modal Multi-Task (M3T) Federated Foundation Models for Embodied AI: Potentials and Challenges for Edge Integration
por: Borazjani, Kasra, et al.
Publicado: (2025)

Numerical exploration of the range of shape functionals using neural networks
por: Martinet, Eloi, et al.
Publicado: (2026)

Adaptive mine planning under geological uncertainty: A POMDP framework for sequential decision-making
por: Khalifi, Hamza, et al.
Publicado: (2026)