Copertina

Enhancing the Reliability of Medical AI through Expert-guided Uncertainty Modeling

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Khalin, Aleksei, Zaychenkova, Ekaterina, Yugay, Aleksandr, Goncharov, Andrey, Korchagin, Sergey, Zaytsev, Alexey, Ershov, Egor
Natura:	Preprint
Pubblicazione:	2026
Soggetti:	Machine Learning
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

Expert-aware uncertainty estimation for quality control of neural-based blood typing
di: Zaychenkova, Ekaterina, et al.
Pubblicazione: (2024)

Uniting contrastive and generative learning for event sequences models
di: Yugay, Aleksandr, et al.
Pubblicazione: (2024)

A theoretical framework for self-supervised contrastive learning for continuous dependent data
di: Marusov, Alexander, et al.
Pubblicazione: (2025)

Strong Linear Baselines Strike Back: Closed-Form Linear Models as Gaussian Process Conditional Density Estimators for TSAD
di: Yugay, Aleksandr, et al.
Pubblicazione: (2026)

Language steering in latent space to mitigate unintended code-switching
di: Goncharov, Andrey, et al.
Pubblicazione: (2025)

When an LLM is apprehensive about its answers -- and when its uncertainty is justified
di: Sychev, Petr, et al.
Pubblicazione: (2025)

Complexity-aware fine-tuning
di: Goncharov, Andrey, et al.
Pubblicazione: (2025)

Efficient Neural Controlled Differential Equations via Attentive Kernel Smoothing
di: Serov, Egor, et al.
Pubblicazione: (2026)

Tsururu: A Python-based Time Series Forecasting Strategies Library
di: Kostromina, Alina, et al.
Pubblicazione: (2025)

Holistic Uncertainty Estimation For Open-Set Recognition
di: Erlygin, Leonid, et al.
Pubblicazione: (2024)

Uncertainty Estimation of Transformers' Predictions via Topological Analysis of the Attention Matrices
di: Kostenok, Elizaveta, et al.
Pubblicazione: (2023)

MedSyn: LLM-based Synthetic Medical Text Generation Framework
di: Kumichev, Gleb, et al.
Pubblicazione: (2024)

Label Attention Network for Temporal Sets Prediction: You Were Looking at a Wrong Self-Attention
di: Kovtun, Elizaveta, et al.
Pubblicazione: (2023)

From 2:4 to 8:16 sparsity patterns in LLMs for Outliers and Weights with Variance Correction
di: Maximov, Egor, et al.
Pubblicazione: (2025)

Learning Transactions Representations for Information Management in Banks: Mastering Local, Global, and External Knowledge
di: Bazarova, Alexandra, et al.
Pubblicazione: (2024)

Foundation for unbiased cross-validation of spatio-temporal models for species distribution modeling
di: Koldasbayeva, Diana, et al.
Pubblicazione: (2025)

Beyond Simple Averaging: Improving NLP Ensemble Performance with Topological-Data-Analysis-Based Weighting
di: Proskura, Polina, et al.
Pubblicazione: (2024)

Parameter-Efficient Neural CDEs via Implicit Function Jacobians
di: Kuleshov, Ilya, et al.
Pubblicazione: (2025)

Autobidding Arena: unified evaluation of the classical and RL-based autobidding algorithms
di: Pudovikov, Andrey, et al.
Pubblicazione: (2025)

Recurrent Action Transformer with Memory
di: Cherepanov, Egor, et al.
Pubblicazione: (2023)

Looking around you: external information enhances representations for event sequences
di: Sokerin, Petr, et al.
Pubblicazione: (2025)

Uncertainty Quantification of Click and Conversion Estimates for the Autobidding
di: Zhigalskii, Ivan, et al.
Pubblicazione: (2026)

U-Former ODE: Fast Probabilistic Forecasting of Irregular Time Series
di: Kuleshov, Ilya, et al.
Pubblicazione: (2026)

ELMUR: External Layer Memory with Update/Rewrite for Long-Horizon RL Problems
di: Cherepanov, Egor, et al.
Pubblicazione: (2025)

Ito Diffusion Approximation of Universal Ito Chains for Sampling, Optimization and Boosting
di: Ustimenko, Aleksei, et al.
Pubblicazione: (2023)

Normalizing self-supervised learning for provably reliable Change Point Detection
di: Bazarova, Alexandra, et al.
Pubblicazione: (2024)

WWAggr: A Window Wasserstein-based Aggregation for Ensemble Change Point Detection
di: Stepikin, Alexander, et al.
Pubblicazione: (2025)

Trajectory-Aware Reliability Modeling of Democratic Systems
di: Zaytsev, Dmitry, et al.
Pubblicazione: (2026)

Memory Retention Is Not Enough to Master Memory Tasks in Reinforcement Learning
di: Shchendrigin, Oleg, et al.
Pubblicazione: (2026)

Re:Frame -- Retrieving Experience From Associative Memory
di: Zelezetsky, Daniil, et al.
Pubblicazione: (2025)

ALIEN: Aligned Entropy Head for Improving Uncertainty Estimation of LLMs
di: Zabolotnyi, Artem, et al.
Pubblicazione: (2025)

InDiD: Instant Disorder Detection via Representation Learning
di: Romanenkova, Evgenia, et al.
Pubblicazione: (2021)

Memory, Benchmark & Robots: A Benchmark for Solving Complex Tasks with Reinforcement Learning
di: Cherepanov, Egor, et al.
Pubblicazione: (2025)

Model-based Policy Optimization using Symbolic World Model
di: Gorodetskiy, Andrey, et al.
Pubblicazione: (2024)

Concealed Adversarial attacks on neural networks for sequential data
di: Sokerin, Petr, et al.
Pubblicazione: (2025)

Hiding Backdoors within Event Sequence Data via Poisoning Attacks
di: Ermilova, Alina, et al.
Pubblicazione: (2023)

Unraveling the Complexity of Memory in RL Agents: an Approach for Classification and Evaluation
di: Cherepanov, Egor, et al.
Pubblicazione: (2024)

IDAP++: Advancing Divergence-Based Pruning via Filter-Level and Layer-Level Optimization
di: Samarin, Aleksei, et al.
Pubblicazione: (2025)

KAGE-Bench: Fast Known-Axis Visual Generalization Evaluation for Reinforcement Learning
di: Cherepanov, Egor, et al.
Pubblicazione: (2026)

Never Skip a Batch: Continuous Training of Temporal GNNs via Adaptive Pseudo-Supervision
di: Panyshev, Alexander, et al.
Pubblicazione: (2025)