robert-giaquinto / gradient-boosted-normalizing-flows
We got a stew going!
☆27Updated last year
Alternatives and similar repositories for gradient-boosted-normalizing-flows:
Users that are interested in gradient-boosted-normalizing-flows are comparing it to the libraries listed below
- ☆28Updated 3 years ago
- PyTorch implementation of Continuously Indexed Flows paper, with many baseline normalising flows☆31Updated 3 years ago
- Neural likelihood-free methods in PyTorch.☆39Updated 5 years ago
- Combining smooth constraint for building DAG with normalizing flow in order to replace autoregressive transformations while keeping tract…☆45Updated last year
- Code for "'Hey, that's not an ODE:' Faster ODE Adjoints via Seminorms" (ICML 2021)☆86Updated 2 years ago
- Code repo for "Function-Space Distributions over Kernels"☆31Updated 4 years ago
- Monotone operator equilibrium networks☆51Updated 4 years ago
- Code for the paper Semi-Conditional Normalizing Flows for Semi-Supervised Learning☆28Updated 3 years ago
- repo for paper: Adaptive Checkpoint Adjoint (ACA) method for gradient estimation in neural ODE☆54Updated 3 years ago
- PyTorch implementation of the OT-Flow approach in arXiv:2006.00104☆51Updated 6 months ago
- Jupyter Notebook corresponding to 'Going with the Flow: An Introduction to Normalizing Flows'☆25Updated 3 years ago
- Normalizing Flows using JAX☆82Updated last year
- Approximate Inference Turns Deep Networks into Gaussian Processes (dnn2gp)☆48Updated 5 years ago
- The official code for Efficient Learning of Generative Models via Finite-Difference Score Matching☆11Updated 2 years ago
- Pytorch version of "Deep Convolutional Networks as shallow Gaussian Processes" by Adrià Garriga-Alonso, Carl Rasmussen and Laurence Aitch…☆32Updated 4 years ago
- Normalizing Flows with a resampled base distribution☆44Updated 2 years ago
- Regularized Neural ODEs (RNODE)☆82Updated 3 years ago
- Implementation of stochastic variational inference for differentially deep gaussian processes☆15Updated 6 years ago
- ☆53Updated 6 months ago
- Repository for DTU Special Course, focusing on Variational Inference using Normalizing Flows (VINF). Supervised by Michael Riis Andersen☆25Updated 4 years ago
- Code to accompany paper 'Bayesian Deep Ensembles via the Neural Tangent Kernel'☆27Updated 3 years ago
- ☆36Updated 2 years ago
- General Invertible Transformations for Flow-based Generative Models☆17Updated 4 years ago
- Code for the Thermodynamic Variational Objective☆26Updated 2 years ago
- ☆22Updated 4 years ago
- Code for Understanding and Mitigating Exploding Inverses in Invertible Neural Networks (AISTATS 2021) http://arxiv.org/abs/2006.09347☆29Updated 4 years ago
- ☆67Updated 2 years ago
- Demos for the paper Generalized Variational Inference (Knoblauch, Jewson & Damoulas, 2019)☆20Updated 5 years ago
- Code for paper "Closing the Dequantization Gap: PixelCNN as a Single-Layer Flow"☆19Updated 4 years ago
- Implementations of Normalizing Flows in Pytorch/Pyro☆19Updated 4 years ago