Alternatives and similar repositories for beta-nll

Users that are interested in beta-nll are comparing it to the libraries listed below

• vdutor / neural-diffusion-processes
  Neural Diffusion Processes
  ☆81Updated last year
• cambridge-mlg / DUN
  Code for "Depth Uncertainty in Neural Networks" (https://arxiv.org/abs/2006.08437)
  ☆76Updated last year
• FrederikWarburg / LaplaceAE
  ☆32Updated 3 years ago
• giannifranchi / LP_BNN
  This repository contains an official implementation of LPBNN.
  ☆38Updated 2 years ago
• sharpenb / Posterior-Network
  Posterior Network: Uncertainty Estimation without OOD Samples via Density-Based Pseudo-Counts (Neurips 2020)
  ☆78Updated 3 years ago
• borchero / natural-posterior-network
  Official Implementation of "Natural Posterior Network: Deep Bayesian Predictive Uncertainty for Exponential Family Distributions" (ICLR, …
  ☆85Updated 2 years ago
• ifiaposto / Distance_Aware_Bottleneck
  Official Implementation of the paper: "A Rate-Distorion View of Uncertainty Quantification", ICML 2024
  ☆28Updated 11 months ago
• mbilos / neural-flows-experiments
  Experiments for Neural Flows paper
  ☆97Updated 3 years ago
• MJ10 / DEUP
  Code for experiments to learn uncertainty
  ☆30Updated 2 years ago
• fregu856 / regression_uncertainty
  Official implementation of "How Reliable is Your Regression Model's Uncertainty Under Real-World Distribution Shifts?", TMLR 2023.
  ☆18Updated last year
• TeaPearce / Bayesian_NN_Ensembles
  AISTATS paper 'Uncertainty in Neural Networks: Approximately Bayesian Ensembling'
  ☆89Updated 4 years ago
• cambridge-mlg / convcnp
  Implementation of the Convolutional Conditional Neural Process
  ☆125Updated 4 years ago
• bobby-he / bayesian-ntk
  Code to accompany paper 'Bayesian Deep Ensembles via the Neural Tangent Kernel'
  ☆26Updated 4 years ago
• wgrathwohl / VERA
  ☆63Updated last year
• tranbahien / you-need-a-good-prior
  All You Need is a Good Functional Prior for Bayesian Deep Learning (JMLR 2022)
  ☆20Updated 3 years ago
• AnthonyRentsch / calibrated_regression
  A tutorial for the 2018 paper Accurate Uncertainties for Deep Learning Using Calibrated Regression by Kuleshov et al.
  ☆52Updated 5 years ago
• dngfra / repulsive_ensembles
  Repo for our paper "Repulsive deep ensembles are Bayesian"
  ☆19Updated 3 years ago
• izmailovpavel / bnn_covariate_shift
  Supporting code for the paper "Dangers of Bayesian Model Averaging under Covariate Shift"
  ☆33Updated 2 years ago
• cambridge-mlg / neural_diffusion_processes
  ☆13Updated 2 years ago
• crisbodnar / ndp
  Official code for the ICLR 2021 paper Neural ODE Processes
  ☆74Updated 3 years ago
• bmucsanyi / untangle
  Large-scale uncertainty benchmark in deep learning.
  ☆62Updated 3 months ago
• Jiacheng-Zhu-AIML / WGPOT
  The Wasserstein Distance and Optimal Transport Map of Gaussian Processes
  ☆53Updated 5 years ago
• PetrMokrov / Large-Scale-Wasserstein-Gradient-Flows
  Source code for Large-Scale Wasserstein Gradient Flows (NeurIPS 2021)
  ☆35Updated 3 years ago
• runame / laplace-refinement
  Posterior Refinement Improves Sample Efficiency in Bayesian Neural Networks
  ☆10Updated 2 years ago
• pasteurlabs / unreasonable_effective_der
  Supplementary material to reproduce "The Unreasonable Effectiveness of Deep Evidential Regression"
  ☆27Updated 2 years ago
• YoungseogChung / calibrated-quantile-uq
  Repository for Beyond Pinball Loss: Quantile Methods for Calibrated Uncertainty Quantification (NeurIPS 2024)
  ☆43Updated 9 months ago
• nikitadurasov / masksembles
  Official repository for the paper "Masksembles for Uncertainty Estimation" (CVPR 2021).
  ☆101Updated 2 months ago
• EmoryMLIP / OT-Flow
  PyTorch implementation of the OT-Flow approach in arXiv:2006.00104
  ☆56Updated last year
• TianrongChen / DMSB
  Official implementation of Deep Momentum Schrödinger Bridge
  ☆27Updated last year
• zdhNarsil / Diffusion-Generative-Flow-Samplers
  PyTorch implementation for our ICLR 2024 paper "Diffusion Generative Flow Samplers: Improving learning signals through partial trajectory…
  ☆24Updated last year