juankuntz / ParEM
Code for "Particle algorithms for maximum likelihood training of latent variable models" (Kuntz, Lim, Johansen, AISTATS, 2023).
☆9Updated last year
Alternatives and similar repositories for ParEM:
Users that are interested in ParEM are comparing it to the libraries listed below
- Demos for the paper Generalized Variational Inference (Knoblauch, Jewson & Damoulas, 2019)☆20Updated 5 years ago
- Light-weighted code for Orthogonal Additive Gaussian Processes☆41Updated 6 months ago
- All You Need is a Good Functional Prior for Bayesian Deep Learning (JMLR 2022)☆21Updated 2 years ago
- Code for the causal benchmark library☆11Updated 4 months ago
- csl: PyTorch-based Constrained Learning☆12Updated 2 years ago
- ☆15Updated 2 years ago
- Repo for our paper "Repulsive deep ensembles are Bayesian"☆19Updated 3 years ago
- Improving predictions of Bayesian neural nets via local linearization, AISTATS 2021☆17Updated 2 years ago
- PyTorch linear operators for curvature matrices (Hessian, Fisher/GGN, KFAC, ...)☆31Updated this week
- PyTorch implementation for "HyperSPNs: Compact and Expressive Probabilistic Circuits", NeurIPS 2021☆13Updated 3 years ago
- Lightweight library of stochastic gradient MCMC algorithms written in JAX.☆100Updated last year
- Implicit Deep Adaptive Design (iDAD): Policy-Based Experimental Design without Likelihoods☆18Updated 3 years ago
- Posterior Refinement Improves Sample Efficiency in Bayesian Neural Networks☆9Updated 2 years ago
- Code for Knowledge-Adaptation Priors based on the NeurIPS 2021 paper by Khan and Swaroop.☆16Updated 3 years ago
- Source code for my PhD thesis: Backpropagation Beyond the Gradient☆20Updated last year
- Fast hyperparameter settings for non-smooth estimators:☆39Updated last year
- Approximate Computation via Odds Ratio Estimation in Likelihood Free Inference☆8Updated last year
- Fully Bayesian Inference in GPs - Gaussian and Generic Likelihoods☆22Updated last year
- An ultra-lightweight JAX implementation of sparse Gaussian processes via pathwise sampling.☆22Updated 3 years ago
- A community repository for benchmarking Bayesian methods☆11Updated last year
- Codes for ICLR 21 paper: Neural Approximate Sufficient Statistics for Implicit Models☆19Updated 2 years ago
- Bayesian Learning from Sequential Data using Gaussian Processes with Signature Covariances☆46Updated last year
- Code for Gaussian Score Matching Variational Inference☆32Updated 4 months ago
- Gaussian Processes for Sequential Data☆18Updated 4 years ago
- ☆10Updated 2 years ago
- "Variational inference tools to leverage estimator sensitivity."☆16Updated last year
- Conformal Histogram Regression: efficient conformity scores for non-parametric regression problems☆21Updated 2 years ago
- Efficient, lightweight variational inference and approximation bounds☆43Updated last year
- Implementation of the Gaussian Process Autoregressive Regression Model☆62Updated last month
- Sampling with gradient-based Markov Chain Monte Carlo approaches☆97Updated 10 months ago