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Title: GitHub - janosh/awesome-normalizing-flows: Awesome resources on normalizing flows. · GitHub

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View sourcehttps://github.com/janosh/diagrams/blob/main/assets/normalizing-flow/normalizing-flow.typ
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Table of Contentshttps://github.com/janosh/awesome-normalizing-flows#-table-of-contents
📝 Publications (60)https://github.com/janosh/awesome-normalizing-flows#-publications-60
🛠️ Applications (8)https://github.com/janosh/awesome-normalizing-flows#%EF%B8%8F-applications-8
📺 Videos (8)https://github.com/janosh/awesome-normalizing-flows#-videos-8
📦 Packages (14)https://github.com/janosh/awesome-normalizing-flows#-packages-14
PyTorch Packageshttps://github.com/janosh/awesome-normalizing-flows#-pytorch-packages
TensorFlow Packageshttps://github.com/janosh/awesome-normalizing-flows#-tensorflow-packages
JAX Packageshttps://github.com/janosh/awesome-normalizing-flows#-jax-packages
Julia Packageshttps://github.com/janosh/awesome-normalizing-flows#-julia-packages
🧑‍💻 Repos (18)https://github.com/janosh/awesome-normalizing-flows#-repos-18
PyTorch Reposhttps://github.com/janosh/awesome-normalizing-flows#-pytorch-repos
TensorFlow Reposhttps://github.com/janosh/awesome-normalizing-flows#-tensorflow-repos
JAX Reposhttps://github.com/janosh/awesome-normalizing-flows#-jax-repos
Other Reposhttps://github.com/janosh/awesome-normalizing-flows#-other-repos
🌐 Blog Posts (5)https://github.com/janosh/awesome-normalizing-flows#-blog-posts-5
🚧 Contributinghttps://github.com/janosh/awesome-normalizing-flows#-contributing
https://github.com/janosh/awesome-normalizing-flows#-publications-60
Transferable Boltzmann Generatorshttps://arxiv.org/abs/2406.14426
Codehttps://osf.io/n8vz3/?view_only=1052300a21bd43c08f700016728aa96e
FInC Flow: Fast and Invertible k×k Convolutions for Normalizing Flowshttps://arxiv.org/abs/2301.09266
Codehttps://github.com/aditya-v-kallappa/FInCFlow
Invertible Monotone Operators for Normalizing Flowshttps://arxiv.org/abs/2210.08176
Codehttps://github.com/mlvlab/MonotoneFlows
ManiFlow: Implicitly Representing Manifolds with Normalizing Flowshttps://arxiv.org/abs/2208.08932
Graphical Normalizing Flowshttps://arxiv.org/abs/2006.02548
Codehttps://github.com/AWehenkel/Graphical-Normalizing-Flows
Multi-scale Attention Flow for Probabilistic Time Series Forecastinghttps://arxiv.org/abs/2205.07493
Adaptive Monte Carlo augmented with normalizing flowshttps://doi.org/10.1073/pnas.2109420119
Codehttps://zenodo.org/records/4783701#.Yfv53urMJD8
E(n) Equivariant Normalizing Flowshttps://arxiv.org/abs/2105.09016
Efficient Bayesian Sampling Using Normalizing Flows to Assist Markov Chain Monte Carlo Methodshttps://arxiv.org/abs/2107.08001
CInC Flow: Characterizable Invertible 3x3 Convolutionhttps://arxiv.org/abs/2107.01358
Codehttps://github.com/Naagar/Normalizing_Flow_3x3_inv
Orthogonalizing Convolutional Layers with the Cayley Transformhttps://arxiv.org/abs/2104.07167
Codehttps://github.com/locuslab/orthogonal-convolutions
Improving Normalizing Flows via Better Orthogonal Parameterizationshttps://invertibleworkshop.github.io/INNF_2019/accepted_papers/pdfs/INNF_2019_paper_30.pdf
Multivariate Probabilistic Time Series Forecasting via Conditioned Normalizing Flowshttps://arxiv.org/abs/2002.06103
OpenReview.nethttps://openreview.net/forum?id=WiGQBFuVRv
Codehttps://github.com/zalandoresearch/pytorch-ts
Haar Wavelet based Block Autoregressive Flows for Trajectorieshttps://arxiv.org/abs/2009.09878
AdvFlow: Inconspicuous Black-box Adversarial Attacks using Normalizing Flowshttps://arxiv.org/abs/2007.07435
Codehttps://github.com/hmdolatabadi/AdvFlow
SurVAE Flows: Surjections to Bridge the Gap between VAEs and Flowshttps://arxiv.org/abs/2007.02731
Videohttps://youtu.be/bXp8fk4MRXQ
Codehttps://github.com/didriknielsen/survae_flows
Why Normalizing Flows Fail to Detect Out-of-Distribution Datahttps://arxiv.org/abs/2006.08545
Tweethttps://twitter.com/polkirichenko/status/1272715634544119809
Codehttps://github.com/PolinaKirichenko/flows_ood
Equivariant Flows: exact likelihood generative learning for symmetric densitieshttps://arxiv.org/abs/2006.02425
The Convolution Exponential and Generalized Sylvester Flowshttps://arxiv.org/abs/2006.01910
Codehttps://github.com/ehoogeboom/convolution_exponential_and_sylvester
iUNets: Fully invertible U-Nets with Learnable Upand Downsamplinghttps://arxiv.org/abs/2005.05220
Normalizing Flows with Multi-Scale Autoregressive Priorshttps://arxiv.org/abs/2004.03891
Codehttps://github.com/visinf/mar-scf
Flows for simultaneous manifold learning and density estimationhttps://arxiv.org/abs/2003.13913
Tweethttps://twitter.com/kylecranmer/status/1250129080395223040
Codehttps://github.com/johannbrehmer/manifold-flow
Gaussianization Flowshttps://arxiv.org/abs/2003.01941
Codehttps://github.com/chenlin9/Gaussianization_Flows
Gradient Boosted Normalizing Flowshttps://arxiv.org/abs/2002.11896
Codehttps://github.com/robert-giaquinto/gradient-boosted-normalizing-flows
Modeling Continuous Stochastic Processes with Dynamic Normalizing Flowshttps://arxiv.org/abs/2002.10516
Tweethttps://twitter.com/r_giaquinto/status/1309648804824723464
Stochastic Normalizing Flowshttps://arxiv.org/abs/2002.09547
Stochastic Normalizing Flows (SNF)https://arxiv.org/abs/2002.06707
Tweethttps://twitter.com/FrankNoeBerlin/status/1229734899034329103
Training Normalizing Flows with the Information Bottleneck for Competitive Generative Classificationhttps://arxiv.org/abs/2001.06448
Codehttps://github.com/vislearn/IB-INN
Invertible Generative Modeling using Linear Rational Splineshttps://arxiv.org/abs/2001.05168
Normalizing Flows for Probabilistic Modeling and Inferencehttps://arxiv.org/abs/1912.02762
Unconstrained Monotonic Neural Networkshttps://arxiv.org/abs/1908.05164
Codehttps://github.com/AWehenkel/UMNN
Normalizing Flows: An Introduction and Review of Current Methodshttps://arxiv.org/abs/1908.09257
Noise Regularization for Conditional Density Estimationhttps://arxiv.org/abs/1907.08982
Bloghttps://siboehm.com/articles/19/normalizing-flow-network
MintNet: Building Invertible Neural Networks with Masked Convolutionshttps://arxiv.org/abs/1907.07945
Codehttps://github.com/ermongroup/mintnet
Densely connected normalizing flowshttps://arxiv.org/abs/2106.04627
Codehttps://github.com/matejgrcic/DenseFlow
Invertible Convolutional Flowhttps://proceedings.neurips.cc/paper/2019/hash/b1f62fa99de9f27a048344d55c5ef7a6-Abstract.html
Codehttps://github.com/Karami-m/Invertible-Convolutional-Flow
Invertible Convolutional Networkshttps://invertibleworkshop.github.io/INNF_2019/accepted_papers/pdfs/INNF_2019_paper_26.pdf
Neural Spline Flowshttps://arxiv.org/abs/1906.04032
Graph Normalizing Flowshttps://arxiv.org/abs/1905.13177
Fast Flow Reconstruction via Robust Invertible n x n Convolutionhttps://arxiv.org/abs/1905.10170
Integer Discrete Flows and Lossless Compressionhttps://arxiv.org/abs/1905.07376
Block Neural Autoregressive Flowhttps://arxiv.org/abs/1904.04676
Block Neural Autoregressive Flowhttps://arxiv.org/abs/1904.04676
Codehttps://github.com/nicola-decao/BNAF
MaCow: Masked Convolutional Generative Flowhttps://arxiv.org/abs/1902.04208
Emerging Convolutions for Generative Normalizing Flowshttps://arxiv.org/abs/1901.11137
Codehttps://github.com/ehoogeboom/emerging
FloWaveNet : A Generative Flow for Raw Audiohttps://arxiv.org/abs/1811.02155
Codehttps://github.com/ksw0306/FloWaveNet
FFJORD: Free-form Continuous Dynamics for Scalable Reversible Generative Modelshttps://arxiv.org/abs/1810.01367
Glow: Generative Flow with Invertible 1x1 Convolutionshttps://arxiv.org/abs/1807.03039
Deep Density Destructorshttps://proceedings.mlr.press/v80/inouye18a.html
Neural Autoregressive Flowshttps://arxiv.org/abs/1804.00779
Codehttps://github.com/CW-Huang/NAF
Sylvester Normalizing Flow for Variational Inferencehttps://arxiv.org/abs/1803.05649
Convolutional Normalizing Flowshttps://arxiv.org/abs/1711.02255
Masked Autoregressive Flow for Density Estimationhttps://arxiv.org/abs/1705.07057
https://github.com/janosh/diagrams/tree/main/assets/masked-autoregressive-flow
Multiplicative Normalizing Flows for Variational Bayesian Neural Networkshttps://arxiv.org/abs/1703.01961
Improving Variational Inference with Inverse Autoregressive Flowhttps://arxiv.org/abs/1606.04934
Codehttps://github.com/openai/iaf
Density estimation using Real NVPhttps://arxiv.org/abs/1605.08803
https://github.com/janosh/diagrams/tree/main/assets/rnvp-affine-coupling-layer
Variational Inference with Normalizing Flowshttps://arxiv.org/abs/1505.05770
Masked Autoencoder for Distribution Estimationhttps://arxiv.org/abs/1502.03509
https://github.com/janosh/diagrams/tree/main/assets/made
Non-linear Independent Components Estimationhttps://arxiv.org/abs/1410.8516
Iterative Gaussianization: from ICA to Random Rotationshttps://arxiv.org/abs/1602.00229
https://github.com/janosh/awesome-normalizing-flows#️-applications-8
Normalizing Kalman Filters for Multivariate Time Series Analysishttps://assets.amazon.science/ea/0c/88b7bdd54eae8c08983fa4cc3e06/normalizing-kalman-filters-for-multivariate-time-series-analysis.pdf
Amazon Sciencehttps://amazon.science/publications/normalizing-kalman-filters-for-multivariate-time-series-analysis
On the Sentence Embeddings from Pre-trained Language Modelshttps://aclweb.org/anthology/2020.emnlp-main.733
https://github.com/bohanli/BERT-flowhttps://github.com/bohanli/BERT-flow
Targeted free energy estimation via learned mappingshttps://aip.scitation.org/doi/10.1063/5.0018903
Faster Uncertainty Quantification for Inverse Problems with Conditional Normalizing Flowshttps://arxiv.org/abs/2007.07985
Videohttps://youtu.be/nPvZIKaRBkI
SRFlow: Learning the Super-Resolution Space with Normalizing Flowhttps://arxiv.org/abs/2006.14200
NeuTra-lizing Bad Geometry in Hamiltonian Monte Carlo Using Neural Transporthttps://arxiv.org/abs/1903.03704
Analyzing Inverse Problems with Invertible Neural Networkshttps://arxiv.org/abs/1808.04730
Latent Space Policies for Hierarchical Reinforcement Learninghttps://arxiv.org/abs/1804.02808
https://github.com/janosh/awesome-normalizing-flows#-videos-8
Normalizing Flows - Motivations, The Big Idea & Essential Foundationshttps://youtu.be/IuXU2dBOJyw
Kapil Sachdevahttps://github.com/ksachdeva
Normalizing Flowshttps://youtu.be/7TOvhz93G9o
Marc Deisenrothhttps://mml-book.github.io/slopes-expectations.html
full serieshttps://youtube.com/playlist?list=PL93aLKqThq4h7UpgeNhkOtEeCnX3DMseS
Introduction to Normalizing Flowshttps://youtu.be/u3vVyFVU_lI
Marcus Brubakerhttps://mbrubake.github.io
Stanhttps://mc-stan.org
Flow Modelshttps://youtu.be/JBb5sSC0JoY
Pieter Abbeelhttps://sites.google.com/view/berkeley-cs294-158-sp20/home
What are normalizing flows?https://youtu.be/i7LjDvsLWCg
Ari Seffhttps://scholar.google.com/citations?user=IxBGctYAAAAJ
A primer on normalizing flowshttps://youtu.be/P4Ta-TZPVi0
Laurent Dinhhttps://laurent-dinh.github.io
Graph Normalizing Flowshttps://youtu.be/frMPP30QQgY
Sylvester Normalizing Flow for Variational Inferencehttps://youtu.be/VeYyUcIDVHI
https://github.com/janosh/awesome-normalizing-flows#-packages-14
https://github.com/janosh/awesome-normalizing-flows/blob/main/assets/pytorch.svg
https://github.com/janosh/awesome-normalizing-flows#-pytorch-packages
Zukohttps://github.com/francois-rozet/zuko
François Rozethttps://francois-rozet.github.io
https://camo.githubusercontent.com/e825baa19d294802998625c0a428f13f46dc611cfa1839c426b211b02aca956a/68747470733a2f2f696d672e736869656c64732e696f2f6769746875622f73746172732f6672616e636f69732d726f7a65742f7a756b6f
LAMPEhttps://github.com/francois-rozet/lampe
Jammy Flowshttps://github.com/thoglu/jammy_flows
Thorsten Glüsenkamphttps://github.com/thoglu
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flowtorchhttps://github.com/facebookincubator/flowtorch
Facebook / Metahttps://opensource.fb.com
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nflowshttps://github.com/bayesiains/nflows
Bayesiainshttps://homepages.inf.ed.ac.uk/imurray2/group
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normflowshttps://github.com/VincentStimper/normalizing-flows
Vincent Stimperhttps://github.com/VincentStimper
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FrEIAhttps://github.com/vislearn/FrEIA
VLL Heidelberghttps://github.com/vislearn
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https://github.com/janosh/awesome-normalizing-flows#-tensorflow-packages
TensorFlow Probabilityhttps://github.com/tensorflow/probability
Googlehttps://tensorflow.org/probability
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https://github.com/janosh/awesome-normalizing-flows#-jax-packages
GWKokabhttps://github.com/gwkokab/gwkokab
Meesum Qazalbashhttps://github.com/Qazalbash
Muhammad Zeeshanhttps://ccrg.rit.edu/user/muhammad.zeeshan
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Docshttps://gwkokab.readthedocs.io
flowMChttps://github.com/kazewong/flowMC
Kaze Wonghttps://www.kaze-wong.com/
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Docshttps://pypi.org/project/flowMC
pzflowhttps://github.com/jfcrenshaw/pzflow
John Franklin Crenshawhttps://jfcrenshaw.github.io
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Distraxhttps://github.com/deepmind/distrax
DeepMindhttps://deepmind.com
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NuXhttps://github.com/Information-Fusion-Lab-Umass/NuX
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https://github.com/janosh/awesome-normalizing-flows#-julia-packages
ContinuousNormalizingFlows.jlhttps://github.com/impICNF/ContinuousNormalizingFlows.jl
Hossein Pourbozorghttps://github.com/prbzrg
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Docshttps://impicnf.github.io/ContinuousNormalizingFlows.jl
InvertibleNetworks.jlhttps://github.com/slimgroup/InvertibleNetworks.jl
SLIMhttps://slim.gatech.edu
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DeeProb-kithttps://github.com/deeprob-org/deeprob-kit
Lorenzo Locontehttps://github.com/loreloc
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NICE: Non-linear Independent Components Estimationhttps://github.com/MaximeVandegar/Papers-in-100-Lines-of-Code/tree/main/NICE_Non_linear_Independent_Components_Estimation
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Normalizing Flows - Introduction (Part 1)https://pyro.ai/examples/normalizing_flows_i
pyro.aihttps://pyro.ai
Parts 2 and 3 coming laterhttps://github.com/pyro-ppl/pyro/issues/1992
Density Estimation with Neural ODEs and Density Estimation with FFJORDshttps://git.io/JiWaG
torchdynhttps://torchdyn.readthedocs.io
StyleFlowhttps://github.com/RameenAbdal/StyleFlow
Rameen Abdalhttps://twitter.com/AbdalRameen
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Docshttps://rameenabdal.github.io/StyleFlow
Graphical Normalizing Flowshttps://github.com/AWehenkel/Graphical-Normalizing-Flows
Antoine Wehenkelhttps://awehenkel.github.io
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pytorch-normalizing-flowshttps://github.com/karpathy/pytorch-normalizing-flows
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Unconstrained Monotonic Neural Networks (UMNN)https://github.com/AWehenkel/UMNN
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pytorch_flowshttps://github.com/acids-ircam/pytorch_flows
acids-ircamhttps://github.com/acids-ircam
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normalizing_flowshttps://github.com/kamenbliznashki/normalizing_flows
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pytorch-flowshttps://github.com/ikostrikov/pytorch-flows
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https://github.com/janosh/awesome-normalizing-flows/blob/main/assets/tensorflow.svg
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Variational Inference using Normalizing Flows (VINF)https://github.com/pierresegonne/VINF
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paperhttps://arxiv.org/pdf/1505.05770.pdf
Normalizing Flowshttps://github.com/LukasRinder/normalizing-flows
Lukas Rinderhttps://github.com/LukasRinder
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BERT-flowhttps://github.com/bohanli/BERT-flow
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https://github.com/janosh/awesome-normalizing-flows#-jax-repos
Neural Transporthttps://pyro.ai/numpyro/examples/neutra
numpyrohttps://num.pyro.ai
https://github.com/janosh/awesome-normalizing-flows/blob/main/assets/other.svg
https://github.com/janosh/awesome-normalizing-flows#-other-repos
Destructive Deep Learning (ddl)https://github.com/davidinouye/destructive-deep-learning
David Inouyehttps://davidinouye.com
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Deep Density Destructorshttps://proceedings.mlr.press/v80/inouye18a.html
Normalizing Flows Overviewhttps://www.pymc.io/projects/examples/en/2022.12.0/variational_inference/normalizing_flows_overview.html
Theanohttps://github.com/Theano/Theano
NormFlowshttps://github.com/andymiller/NormFlows
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autogradhttps://github.com/HIPS/autograd
https://github.com/janosh/awesome-normalizing-flows#-blog-posts-5
Chapter on flows from the book 'Deep Learning for Molecules and Materials'https://dmol.pub/dl/flows
Andrew Whitehttps://thewhitelab.org
Change of Variables for Normalizing Flowshttps://nealjean.com/ml/change-of-variables
Flow-based Deep Generative Modelshttps://lilianweng.github.io/lil-log/2018/10/13/flow-based-deep-generative-models
Normalizing Flowshttps://akosiorek.github.io/norm_flows
Normalizing Flows Tutorialhttps://blog.evjang.com/2018/01/nf1.html
Part 1https://blog.evjang.com/2018/01/nf1.html
Part 2https://blog.evjang.com/2018/01/nf2.html
https://github.com/janosh/awesome-normalizing-flows#-contributing
Normalizing Flows topic on GitHubhttps://github.com/topics/normalizing-flows
data/*.ymlhttps://github.com/janosh/awesome-normalizing-flows/edit/main/data
open an issuehttps://github.com/janosh/awesome-normalizing-flows/issues/new
start a discussionhttps://github.com/janosh/awesome-normalizing-flows/discussions
machine-learning https://github.com/topics/machine-learning
awesome-list https://github.com/topics/awesome-list
bayesian-inference https://github.com/topics/bayesian-inference
autoregressive https://github.com/topics/autoregressive
variational-inference https://github.com/topics/variational-inference
density-estimation https://github.com/topics/density-estimation
normalizing-flows https://github.com/topics/normalizing-flows
bayesian-neural-networks https://github.com/topics/bayesian-neural-networks
generative-modeling https://github.com/topics/generative-modeling
Readme https://github.com/janosh/awesome-normalizing-flows#readme-ov-file
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