Update README.md to simplify architecture overview

davidnabergoj · Nov 9, 2023 · 0c05698 · 0c05698
1 parent 8c73cc8
commit 0c05698
Showing 1 changed file with 29 additions and 30 deletions.
diff --git a/README.md b/README.md
@@ -13,7 +13,6 @@ import torch
 from normalizing_flows import Flow
 from normalizing_flows.architectures import RealNVP
 
-
 torch.manual_seed(0)
 
 n_data = 1000
@@ -69,35 +68,35 @@ Sampling from a NF means sampling from the simple distribution and transforming
 We list supported NF architectures below.
 We classify architectures as either autoregressive, residual, or continuous; as defined
 by [Papamakarios et al. (2021)](https://arxiv.org/abs/1912.02762).
-Exact architectures do not use numerical approximations to generate data or compute the log density.
-
-| Architecture                                                           	 | Bijection type           	 | Exact 	 | Two-way |
-|--------------------------------------------------------------------------|:--------------------------:|:-------:|:-------:|
-| [NICE](http://arxiv.org/abs/1410.8516)                              	    |      Autoregressive 	      | ✔     	 |    ✔    |
-| [Real NVP](http://arxiv.org/abs/1605.08803)                         	    |      Autoregressive 	      | ✔     	 |    ✔    |
-| [MAF](http://arxiv.org/abs/1705.07057)                              	    |      Autoregressive 	      | ✔     	 |    ✔    |
-| [IAF](http://arxiv.org/abs/1606.04934)                              	    |      Autoregressive 	      | ✔     	 |    ✔    |
-| [Rational quadratic NSF](http://arxiv.org/abs/1906.04032)           	    |      Autoregressive 	      | ✔     	 |    ✔    |
-| [Linear rational NSF](http://arxiv.org/abs/2001.05168)              	    |      Autoregressive 	      | ✔     	 |    ✔    |
-| [NAF](http://arxiv.org/abs/1804.00779)                              	    |      Autoregressive 	      | ✗     	 |    ✔    |
-| [UMNN](http://arxiv.org/abs/1908.05164)                             	    |      Autoregressive 	      | ✗     	 |    ✔    |
-| [Planar](https://onlinelibrary.wiley.com/doi/abs/10.1002/cpa.21423) 	    |      Residual       	      | ✗     	 |    ✗    |
-| [Radial](https://proceedings.mlr.press/v37/rezende15.html)          	    |      Residual       	      | ✗     	 |    ✗    |
-| [Sylvester](http://arxiv.org/abs/1803.05649)                        	    |      Residual       	      | ✗     	 |    ✗    |
-| [Invertible ResNet](http://arxiv.org/abs/1811.00995)                	    |      Residual       	      | ✗     	 |   ✔*    |
-| [ResFlow](http://arxiv.org/abs/1906.02735)                          	    |      Residual       	      | ✗     	 |   ✔*    |
-| [Proximal ResFlow](http://arxiv.org/abs/2211.17158)                 	    |      Residual       	      | ✗     	 |   ✔*    |
-| [FFJORD](http://arxiv.org/abs/1810.01367)                           	    |      Continuous     	      | ✗     	 |   ✔*    |
-| [RNODE](http://arxiv.org/abs/2002.02798)                            	    |      Continuous     	      | ✗     	 |   ✔*    |
-| [DDNF](http://arxiv.org/abs/1810.03256)                             	    |      Continuous     	      | ✗     	 |   ✔*    |
-| [OT flow](http://arxiv.org/abs/2006.00104)                          	    |      Continuous     	      | ✗     	 |    ✔    |
-
-Two-way architectures support both sampling and density estimation.
-Two-way architectures marked with an asterisk (*) support both, but use a numerical approximation to sample or estimate
-density.
-One-way architectures support either sampling or density estimation, but not both at once.
-
-We also support simple bijections (all exact and two-way):
+We specify whether the forward and inverse passes are exact; otherwise they are numerical or not implemented (Planar,
+Radial, and Sylvester flows).
+An exact forward pass guarantees exact density estimation, whereas an exact inverse pass guarantees exact sampling.
+Note that the directions can always be reversed, which enables exact computation for the opposite task.
+We also specify whether the logarithm of the Jacobian determinant of the transformation is exact or computed numerically.
+
+| Architecture                                                           	 | Bijection type           	 | Exact forward 	 | Exact inverse | Exact log determinant |
+|--------------------------------------------------------------------------|:--------------------------:|:---------------:|:-------------:|:---------------------:|
+| [NICE](http://arxiv.org/abs/1410.8516)                              	    |      Autoregressive 	      |     ✔     	     |       ✔       |           ✔           |
+| [Real NVP](http://arxiv.org/abs/1605.08803)                         	    |      Autoregressive 	      |     ✔     	     |       ✔       |           ✔           |
+| [MAF](http://arxiv.org/abs/1705.07057)                              	    |      Autoregressive 	      |     ✔     	     |       ✔       |           ✔           |
+| [IAF](http://arxiv.org/abs/1606.04934)                              	    |      Autoregressive 	      |     ✔     	     |       ✔       |           ✔           |
+| [Rational quadratic NSF](http://arxiv.org/abs/1906.04032)           	    |      Autoregressive 	      |     ✔     	     |       ✔       |           ✔           |
+| [Linear rational NSF](http://arxiv.org/abs/2001.05168)              	    |      Autoregressive 	      |     ✔     	     |       ✔       |           ✔           |
+| [NAF](http://arxiv.org/abs/1804.00779)                              	    |      Autoregressive 	      |     ✔     	     |       ✗       |           ✔           |
+| [UMNN](http://arxiv.org/abs/1908.05164)                             	    |      Autoregressive 	      |     ✗     	     |       ✗       |           ✔           |
+| [Planar](https://onlinelibrary.wiley.com/doi/abs/10.1002/cpa.21423) 	    |      Residual       	      |     ✔     	     |       ✗       |           ✔           | 
+| [Radial](https://proceedings.mlr.press/v37/rezende15.html)          	    |      Residual       	      |     ✔     	     |       ✗       |           ✔           |
+| [Sylvester](http://arxiv.org/abs/1803.05649)                        	    |      Residual       	      |     ✔     	     |       ✗       |           ✔           |
+| [Invertible ResNet](http://arxiv.org/abs/1811.00995)                	    |      Residual       	      |     ✔     	     |       ✗       |           ✗           |
+| [ResFlow](http://arxiv.org/abs/1906.02735)                          	    |      Residual       	      |     ✔     	     |       ✗       |           ✗           |
+| [Proximal ResFlow](http://arxiv.org/abs/2211.17158)                 	    |      Residual       	      |     ✔     	     |       ✗       |           ✗           |
+| [FFJORD](http://arxiv.org/abs/1810.01367)                           	    |      Continuous     	      |     ✗     	     |       ✗       |           ✗           |
+| [RNODE](http://arxiv.org/abs/2002.02798)                            	    |      Continuous     	      |     ✗     	     |       ✗       |           ✗           |
+| [DDNF](http://arxiv.org/abs/1810.03256)                             	    |      Continuous     	      |     ✗     	     |       ✗       |           ✗           |
+| [OT flow](http://arxiv.org/abs/2006.00104)                          	    |      Continuous     	      |     ✗     	     |       ✗       |           ✗           |
+
+
+We also support simple bijections (all with exact forward passes, inverse passes, and log determinants):
 
 * Permutation
 * Elementwise translation (shift vector)