cunningham-lab / cb_and_ccLinks
☆36Updated 2 years ago
Alternatives and similar repositories for cb_and_cc
Users that are interested in cb_and_cc are comparing it to the libraries listed below
Sorting:
- Pytorch implementation of the Power Spherical distribution☆74Updated last year
- ☆54Updated last year
- Normalizing Flows in Jax☆107Updated 5 years ago
- Code for the Thermodynamic Variational Objective☆26Updated 3 years ago
- ☆181Updated 6 years ago
- Pytorch implementation of Block Neural Autoregressive Flow☆181Updated 4 years ago
- Autoregressive Energy Machines☆78Updated 2 years ago
- Codebase for Learning Invariances in Neural Networks☆96Updated 3 years ago
- PyTorch implementation of Continuously Indexed Flows paper, with many baseline normalising flows☆31Updated 4 years ago
- Official PyTorch BIVA implementation (BIVA: A Very Deep Hierarchy of Latent Variables for Generative Modeling)☆84Updated 2 years ago
- PyTorch-SSO: Scalable Second-Order methods in PyTorch☆147Updated 2 years ago
- [IJCAI'19, NeurIPS'19] Anode: Unconditionally Accurate Memory-Efficient Gradients for Neural ODEs☆106Updated 4 years ago
- Approximate Inference Turns Deep Networks into Gaussian Processes (dnn2gp)☆48Updated 5 years ago
- ☆64Updated last year
- Riemannian Convex Potential Maps☆67Updated 2 years ago
- Pytorch version of "Deep Convolutional Networks as shallow Gaussian Processes" by Adrià Garriga-Alonso, Carl Rasmussen and Laurence Aitch…☆32Updated 5 years ago
- Neural likelihood-free methods in PyTorch.☆39Updated 5 years ago
- PyTorch implementation of Bidirectional Monte Carlo, Annealed Importance Sampling, and Hamiltonian Monte Carlo.☆52Updated 4 years ago
- Code for "'Hey, that's not an ODE:' Faster ODE Adjoints via Seminorms" (ICML 2021)☆88Updated 2 years ago
- Experiments for Meta-Learning Symmetries by Reparameterization☆57Updated 4 years ago
- A PyTorch re-implementation of "Doubly Reparameterized Gradient Estimators for Monte Carlo Objectives"☆18Updated 6 years ago
- Bayesianize: A Bayesian neural network wrapper in pytorch☆89Updated last year
- ☆170Updated last year
- [NeurIPS 2020] Neural Manifold Ordinary Differential Equations (https://arxiv.org/abs/2006.10254)☆121Updated 2 years ago
- Reference implementation of variational sequential Monte Carlo proposed by Naesseth et al. "Variational Sequential Monte Carlo" (2018)☆65Updated 6 years ago
- Experiments for the Neural Autoregressive Flows paper☆125Updated 4 years ago
- Jupyter Notebook corresponding to 'Going with the Flow: An Introduction to Normalizing Flows'☆27Updated 4 years ago
- Sample code for running deterministic variational inference to train Bayesian neural networks☆100Updated 7 years ago
- Code to accompany the paper Radial Bayesian Neural Networks: Beyond Discrete Support In Large-Scale Bayesian Deep Learning☆33Updated 5 years ago
- Code required to reproduce the experiments in Auxiliary Variational MCMC☆17Updated 7 years ago