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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/jmcardenas/cas4dl

공식 코드

CAS4DL: Christoffel Adaptive Sampling for function approximation via Deep Learning

https://github.com/jmdvinodjmd/HyperITE

공식 코드

A Brief Review of Hypernetworks in Deep Learning

https://github.com/jmwalchessen/neural_likelihood

공식 코드

Neural Likelihood Surfaces for Spatial Processes with Computationally Intensive or Intractable Likelihoods

https://github.com/jonasvj/onlocalposteriorstructureindeepensembles

공식 코드

On Local Posterior Structure in Deep Ensembles

https://github.com/josh0tt/PIGPSEE

공식 코드

Physics-informed Gaussian Processes for Safe Envelope Expansion

https://github.com/josh3142/lowranklaplaceapproximation

공식 코드

Optimal Subspace Inference for the Laplace Approximation of Bayesian Neural Networks

https://github.com/jplmlia/uq4k

공식 코드

Uncertainty Quantification of the 4th kind; optimal posterior accuracy-uncertainty tradeoff with the minimum enclosing ball

https://github.com/juice500ml/dysarthria-gop

공식 코드

Speech Intelligibility Assessment of Dysarthric Speech by using Goodness of Pronunciation with Uncertainty Quantification

https://github.com/juliagni/geometricmachinelearning.jl

공식 코드

Symplectic Autoencoders for Model Reduction of Hamiltonian Systems

https://github.com/junting-ren/model_uncertainty_using_feature_confidence_set

공식 코드

Model uncertainty quantification using feature confidence sets for outcome excursions

https://github.com/jwen307/taskuq

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Task-Driven Uncertainty Quantification in Inverse Problems via Conformal Prediction

https://github.com/jx-zhong-for-academic-purpose/Uncertainty-aware-INVASE

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Uncertainty-aware INVASE: Enhanced Breast Cancer Diagnosis Feature Selection

https://github.com/kainmueller-lab/arctique

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Arctique: An artificial histopathological dataset unifying realism and controllability for uncertainty quantification

https://github.com/kaleidophon/nlp-uncertainty-zoo

공식 코드

On Uncertainty In Natural Language Processing

https://github.com/kangmintong/rob-fcp

공식 코드

Certifiably Byzantine-Robust Federated Conformal Prediction

https://github.com/katharinahech/labelembeddings

공식 코드

Human-in-the-loop: Towards Label Embeddings for Measuring Classification Difficulty

https://github.com/katiana22/GDM-PCE

공식 코드

Manifold learning-based polynomial chaos expansions for high-dimensional surrogate models

https://github.com/kavyarsaxena/me_reg_taslp

공식 코드

Regression-based Melody Estimation with Uncertainty Quantification

https://github.com/kclip/bayesian-snn

공식 코드

Bayesian Continual Learning via Spiking Neural Networks

https://github.com/kclip/quantum-cp

공식 코드

Quantum Conformal Prediction for Reliable Uncertainty Quantification in Quantum Machine Learning

https://github.com/keanson/md-bsfc

공식 코드

Accelerating Convergence in Bayesian Few-Shot Classification

https://github.com/kejzlarv/VBI_Calibration

공식 코드

Variational Inference with Vine Copulas: An efficient Approach for Bayesian Computer Model Calibration

https://github.com/kerrydrx/evidentialada

공식 코드

Evidential Uncertainty Quantification: A Variance-Based Perspective

https://github.com/kevinliang888/IntroPlan

공식 코드

Introspective Planning: Aligning Robots' Uncertainty with Inherent Task Ambiguity

https://github.com/kevopoulosk/Parametric-kernel-based-DMD-using-deep-learning

공식 코드

A parametric framework for kernel-based dynamic mode decomposition using deep learning

https://github.com/kilianzepf/laplacian_segmentation

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Laplacian Segmentation Networks Improve Epistemic Uncertainty Quantification

https://github.com/kjetil-lye/learning_airfoils

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Deep learning observables in computational fluid dynamics

https://github.com/klemens-floege/svn_ensembles

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Stein Variational Newton Neural Network Ensembles

https://github.com/klicperajo/dimenet

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Fast and Uncertainty-Aware Directional Message Passing for Non-Equilibrium Molecules

https://github.com/kminartz/epns

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Equivariant Neural Simulators for Stochastic Spatiotemporal Dynamics

https://github.com/kolyanray/Bayesian-Causal-Inference

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Debiased Bayesian inference for average treatment effects

https://github.com/konstantinhess/bayesian-neural-cde

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Bayesian Neural Controlled Differential Equations for Treatment Effect Estimation

https://github.com/konstantinklemmer/pe-gnn

공식 코드

Positional Encoder Graph Quantile Neural Networks for Geographic Data

https://github.com/lamps-lab/uqtta

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Uncertainty Quantification in Table Structure Recognition

https://github.com/lanl/COVID-19-Predictions

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Daily Forecasting of New Cases for Regional Epidemics of Coronavirus Disease 2019 with Bayesian Uncertainty Quantification

https://github.com/lanl/openfwi

공식 코드

OpenFWI: Large-Scale Multi-Structural Benchmark Datasets for Seismic Full Waveform Inversion

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