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Uncertainty Quantification

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코드

관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.

https://github.com/ag2435/npr

공식 코드

Supervised Kernel Thinning

https://github.com/agaldran/mhml_calibration

공식 코드

Multi-Head Multi-Loss Model Calibration

https://github.com/ahenkes1/henkes_gan

공식 코드

Three-dimensional microstructure generation using generative adversarial neural networks in the context of continuum micromechanics

https://github.com/ahnobari/autosurf

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Conformal Predictions Enhanced Expert-guided Meshing with Graph Neural Networks

https://github.com/ai4science-westlakeu/le-pde-uq

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Uncertainty Quantification for Forward and Inverse Problems of PDEs via Latent Global Evolution

https://github.com/ai4science-westlakeu/safediffcon

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From Uncertain to Safe: Conformal Fine-Tuning of Diffusion Models for Safe PDE Control

https://github.com/alafage/hlt-ens

공식 코드

Hierarchical Light Transformer Ensembles for Multimodal Trajectory Forecasting

https://github.com/alanjohnvarghese/TransformerG2G

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TransformerG2G: Adaptive time-stepping for learning temporal graph embeddings using transformers

https://github.com/alexandervnikitin/kernel-language-entropy

공식 코드

Kernel Language Entropy: Fine-grained Uncertainty Quantification for LLMs from Semantic Similarities

https://github.com/alextimans/traffic4cast-uncertainty

공식 코드

Uncertainty Quantification for Image-based Traffic Prediction across Cities

https://github.com/alfonsogijon/windturbines_pinns

공식 코드

Prediction of wind turbines power with physics-informed neural networks and evidential uncertainty quantification

https://github.com/aliakbars/dgpsi-picu

공식 코드

Integrative Analysis and Imputation of Multiple Data Streams via Deep Gaussian Processes

https://github.com/alireza-javanmardi/conformal-bps

공식 코드

Optimal Conformal Prediction under Epistemic Uncertainty

https://github.com/alisiahkoohi/seismic-imaging-with-SGLD

공식 코드

A deep-learning based Bayesian approach to seismic imaging and uncertainty quantification

https://github.com/alycia-noel/udj-fl

공식 코드

Achieving Distributive Justice in Federated Learning via Uncertainty Quantification

https://github.com/amazon-science/operator-probconserv

공식 코드

Using Uncertainty Quantification to Characterize and Improve Out-of-Domain Learning for PDEs

https://github.com/amazon-science/probconserv

공식 코드

Learning Physical Models that Can Respect Conservation Laws

https://github.com/aminegha/streampred

공식 코드

Streamflow Prediction with Uncertainty Quantification for Water Management: A Constrained Reasoning and Learning Approach

https://github.com/andreareds/towardsuncertaintyawareworkloadprediction

공식 코드

Forecasting Workload in Cloud Computing: Towards Uncertainty-Aware Predictions and Transfer Learning

https://github.com/andreareds/uncertaintyawareworkloadprediction

공식 코드

Forecasting Workload in Cloud Computing: Towards Uncertainty-Aware Predictions and Transfer Learning

https://github.com/andrewcharlesjones/pcpca

공식 코드

Probabilistic Contrastive Principal Component Analysis

https://github.com/andrewzm/spherepp

공식 코드

Spherical Poisson Point Process Intensity Function Modeling and Estimation with Measure Transport

https://github.com/anger-man/cascaded-null-space-learning

공식 코드

Uncertainty-Aware Null Space Networks for Data-Consistent Image Reconstruction

https://github.com/anger-man/unsupervised-image-transfer-and-uq

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Unsupervised Joint Image Transfer and Uncertainty Quantification Using Patch Invariant Networks

https://github.com/angie-lab-jhu/neuralvarlinucb

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Variance-Aware Linear UCB with Deep Representation for Neural Contextual Bandits

https://github.com/ankurmahesh/earth2mip-fork

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Huge Ensembles Part II: Properties of a Huge Ensemble of Hindcasts Generated with Spherical Fourier Neural Operators

https://github.com/ankurmallick/sample-efficient-uq

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Probabilistic Neighbourhood Component Analysis: Sample Efficient Uncertainty Estimation in Deep Learning

https://github.com/anr-mimico/jfsma_schelling

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Modèles de Substitution pour les Modèles à base d'Agents : Enjeux, Méthodes et Applications

https://github.com/anthony-frion/sentinel2ts

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Koopman Ensembles for Probabilistic Time Series Forecasting

https://github.com/antoinedemathelin/maxwent-expe

공식 코드

Deep Out-of-Distribution Uncertainty Quantification via Weight Entropy Maximization

https://github.com/aoshuang92/css_uq_llms

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CSS: Contrastive Semantic Similarity for Uncertainty Quantification of LLMs

https://github.com/apple/ml-mixupmp

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Posterior Uncertainty Quantification in Neural Networks using Data Augmentation

https://github.com/aprilab-uf/info_driven_guidance

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Uncertainty-Aware Guidance for Target Tracking subject to Intermittent Measurements using Motion Model Learning

https://github.com/arcadelab/fastsam3d_slicer

공식 코드

FastSAM-3DSlicer: A 3D-Slicer Extension for 3D Volumetric Segment Anything Model with Uncertainty Quantification

https://github.com/arkadaw9/PGA_LSTM

공식 코드

Physics-Guided Architecture (PGA) of Neural Networks for Quantifying Uncertainty in Lake Temperature Modeling

https://github.com/arkadaw9/PID-GAN

공식 코드

PID-GAN: A GAN Framework based on a Physics-informed Discriminator for Uncertainty Quantification with Physics

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