Unifying Variational Autoencoder (VAE) implementations in Pytorch (NeurIPS 2022)
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Updated
Apr 9, 2024 - Python
Unifying Variational Autoencoder (VAE) implementations in Pytorch (NeurIPS 2022)
Normalizing flows in PyTorch
Awesome resources on normalizing flows.
Pytorch implementations of density estimation algorithms: BNAF, Glow, MAF, RealNVP, planar flows
Official PyTorch code for WACV 2022 paper "CFLOW-AD: Real-Time Unsupervised Anomaly Detection with Localization via Conditional Normalizing Flows"
An extension of XGBoost to probabilistic modelling
Repository for Deep Structural Causal Models for Tractable Counterfactual Inference
Reimplementation of Variational Inference with Normalizing Flows (https://arxiv.org/abs/1505.05770)
Implementation of normalizing flows in TensorFlow 2 including a small tutorial.
Neural Spline Flow, RealNVP, Autoregressive Flow, 1x1Conv in PyTorch.
PyTorch Implementation of PortaSpeech: Portable and High-Quality Generative Text-to-Speech
Pytorch implementation of Block Neural Autoregressive Flow
DGMs for NLP. A roadmap.
Implementation of "Intensity-Free Learning of Temporal Point Processes" (Spotlight @ ICLR 2020)
Real NVP PyTorch a Minimal Working Example | Normalizing Flow
Code for reproducing Flow ++ experiments
Manifold-learning flows (ℳ-flows)
Official code for "Maximum Likelihood Training of Score-Based Diffusion Models", NeurIPS 2021 (spotlight)
An extension of LightGBM to probabilistic modelling
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