A Julia framework for invertible neural networks
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Updated
May 23, 2024 - Julia
A Julia framework for invertible neural networks
PyTorch implementation of normalizing flow models
[NeurIPS 2022] (Amortized) distributional control for pre-trained generative models
Code for Transformed Distribution Matching (TDM) for Missing Value Imputation, ICML 2023
A python/pytorch package for invertible neural networks
Repository for "Inverse Kinematics of Tendon Driven Continuum Robots using Invertible Neural Network" (CompAuto 2022)
Null-sampling for Interpretable and Fair Representations
Code for the paper "Guided Image Generation with Conditional Invertible Neural Networks" (2019)
FrEIA sample code
GraphNVP: An Invertible Flow Model for Generating Molecular Graphs
Official repository of "DeepMIH: Deep Invertible Network for Multiple Image Hiding", TPAMI 2022.
Constrained optimization toolkit for PyTorch
Official PyTorch implementation of "HiNet: Deep Image Hiding by Invertible Network" (ICCV 2021)
Learning inverse kinematics using invertible neural networks and GANs. Research project for "Advanced Deep Learning for Robotics".
RID-Noise: Towards Robust Inverse Design under Noisy Environments
Research project for real-time rendering using Neural Radiance Fields (NeRF) and invertible neural networks (INNs)
Code to reproduce results in "Preconditioned training of normalizing flows for variational inference in inverse problems"
Multi-fidelity Generative Deep Learning Turbulent Flows
MintNet: Building Invertible Neural Networks with Masked Convolutions
Project website for 'Estimating "good" variability in speech production using invertible neural networks' (ISSP 2020)
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