marketdesignresearch / NOMULinks
NOMU: Neural Optimization-based Model Uncertainty
☆10Updated 2 years ago
Alternatives and similar repositories for NOMU
Users that are interested in NOMU are comparing it to the libraries listed below
Sorting:
- [ICLR 2022] "Bayesian Modeling and Uncertainty Quantification for Learning to Optimize: What, Why, and How" by Yuning You, Yue Cao, Tianl…☆14Updated 3 years ago
- [NeurIPS 2020] Task-Agnostic Amortized Inference of Gaussian Process Hyperparameters (AHGP)☆23Updated 4 years ago
- Code for experiments to learn uncertainty☆30Updated 2 years ago
- Posterior Refinement Improves Sample Efficiency in Bayesian Neural Networks☆10Updated 3 years ago
- ☆11Updated 4 years ago
- Implicit Deep Adaptive Design (iDAD): Policy-Based Experimental Design without Likelihoods☆21Updated 3 years ago
- PyTorch implementation of the paper "Continuous Wasserstein-2 Barycenter Estimation without Minimax Optimization" (ICLR 2021)☆24Updated 3 years ago
- NeurIPS'23: Energy Discrepancies: A Score-Independent Loss for Energy-Based Models☆17Updated last year
- Supporting code for the paper "Dangers of Bayesian Model Averaging under Covariate Shift"☆33Updated 3 years ago
- Official Implementation of the paper: "A Rate-Distorion View of Uncertainty Quantification", ICML 2024☆28Updated last year
- "How to Trust Your Diffusion Models: A Convex Optimization Approach to Conformal Risk Control"☆18Updated 5 months ago
- ☆20Updated 3 years ago
- Code to accompany paper 'Bayesian Deep Ensembles via the Neural Tangent Kernel'☆26Updated 4 years ago
- On Uncertainty, Tempering, and Data Augmentation in Bayesian Classification☆21Updated 3 years ago
- Implementations of orthogonal and semi-orthogonal convolutions in the Fourier domain with applications to adversarial robustness☆47Updated 4 years ago
- Laplace Redux -- Effortless Bayesian Deep Learning☆44Updated 5 months ago
- ☆10Updated 3 years ago
- Self-Similarity Priors: Neural Collages as Differentiable Fractal Representations☆28Updated 2 years ago
- Bayesian Optimization with Density-Ratio Estimation☆24Updated 2 years ago
- beta-NLL introduced in our paper "On the Pitfalls of Heteroscedastic Uncertainty Estimation with Probabilistic Neural Networks" ICLR 2022☆45Updated 3 years ago
- ☆15Updated 3 years ago
- UQGAN: A Unified Model for Uncertainty Quantification of Deep Classifiers trained via Conditional GANs☆11Updated 2 years ago
- Official implementation of Transformer Neural Processes☆78Updated 3 years ago
- PyTorch implementation for our ICLR 2024 paper "Diffusion Generative Flow Samplers: Improving learning signals through partial trajectory…☆25Updated last year
- ☆18Updated 4 years ago
- Post-processing for fair classification☆16Updated 4 months ago
- ModelDiff: A Framework for Comparing Learning Algorithms☆59Updated 2 years ago
- Supporing code for the paper "Bayesian Model Selection, the Marginal Likelihood, and Generalization".☆37Updated 3 years ago
- Bayesian and Maximum Likelihood Implementation of the Normalizing Flow Network (NFN): https://arxiv.org/abs/1907.08982☆22Updated 4 years ago
- Repo for our paper "Repulsive deep ensembles are Bayesian"☆19Updated 3 years ago