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1 <head>
2 <TITLE>Software Packages for Graphical Models / Bayesian Networks</TITLE>
3 </head>
4
5 <body>
6
7 <h1>
8 Software Packages for Graphical Models / Bayesian Networks
9 </h1>
10 <p>
11 Written by Kevin Murphy.
12 <br>
13 Last updated 31 October 2005.
14
15 <h3>Remarks</h3>
16 <ul>
17
18 <li>
19 A much more detailed comparison of some of these software packages is
20 available from Appendix B of
21 <a href="http://www.csse.monash.edu.au/bai/">Bayesian AI</a>, by
22 Ann Nicholson and Kevin Korb.
23 This appendix is
24 available
25 <a
26 href="http://www.csse.monash.edu.au/bai/book/appendix_b.pdf">here</a>,
27 and is based on the online comparison below.
28
29 <li>
30 An online <a
31 href="http://servasi.insa-rouen.fr/enseignement/siteUV/rna/BNT/software.html">French
32 version</a> of this page is also available (not necessarily up-to-date).
33
34 <!--
35 <li>
36 Matt Turk has made a
37 <a href="http://ilab.cs.ucsb.edu/BayesNets/Bayesia_Software.pdf">pdf
38 version of this page</a> (not necessarily up-to-date) with some extra
39 comments on the packages.
40 -->
41 <!--
42 <br>
43 (He also has a
44 <a href="http://ilab.cs.ucsb.edu/BayesNets">cached copy</a> of several of
45 the packages listed below, which you can look at if links are down.)
46 -->
47
48 </ul>
49
50 <h3>What do the headers in the table mean?</h3>
51
52 <ul>
53 <li> Src = source code included? (N=no) If so, what language?
54
55 <li> API = application program interface included?
56 (N means the program cannot be integrated into your code, i.e., it
57 must be run as a standalone executable.)
58
59 <li> Exec = Executable runs on W = Windows (95/98/NT), U = Unix, M =
60 Mac, or - = any machine with a compiler.
61
62 <li> Cts = are continuous (latent) nodes supported?
63 G = (conditionally) Gaussians nodes supported analytically,
64 Cs = continuous nodes supported by sampling,
65 Cd = continuous nodes supported by discretization,
66 Cx = continuous nodes supported by some unspecified method,
67 D = only discrete nodes supported.
68
69
70 <li> GUI = Graphical User Interface included?
71
72 <li> Learns parameters?
73
74 <li> Learns structure? CI = means uses conditional independency tests
75
76 <!--
77 <li> Sample = sampling methods (e.g., likelihood weighting, MCMC) supported?
78 -->
79
80 <li> Utility = utility and decision nodes (i.e., influence diagrams)
81 supported?
82
83 <li> Free?
84 0 = free (although possibly only for academic use).
85 $ = commercial software (although most have free versions
86 which are restricted in
87 various ways, e.g., the model size is limited, or models cannot be
88 saved, or there is no API.)
89
90
91 <li> Undir?
92 What kind of graphs are supported?
93 U = only undirected graphs,
94 D = only directed graphs,
95 UD = both undirected and directed,
96 CG = chain graphs (mixed directed/undirected).
97
98
99 <li> Inference = which inference algorithm is used?
100 jtree = junction tree,
101 varelim = variable (bucket) elimination,
102 MH = Metropols Hastings,
103 G = Gibbs sampling,
104 IS = importance sampling,
105 sampling = some other Monte Carlo method,
106 polytree = Pearl's algorithm restricted to a graph with no cycles,
107 none = no inference supported (hence the program is only designed for
108 structure learning from completely observed data)
109
110 <li> Comments.
111 If in "quotes", I am quoting the authors at their request.
112
113 </ul>
114
115
116
117 <!--
118 The following table is automatically generated as follows
119 bnsoft_to_html.pl < bnsoft.txt > ! soft.html
120 Then soft.html is inserted and the last line is tidied up.
121 -->
122
123 <table border>
124 <tr>
125 <td> Name
126 <td> Authors
127 <td> Src
128 <td> API
129 <td> Exec
130 <td> Cts
131 <td> GUI
132 <td> Params
133 <td> Struct
134 <td> Utility
135 <td> Free
136 <td> Undir
137 <td> Inference
138 <td> Comments
139
140
141 <tr>
142 <td> <!--Name--> <a href=http://www.agenarisk.com > AgenaRisk</a>
143 <td> <!--Authors-->Agena
144 <td> <!--Src-->N
145 <td> <!--API-->Y
146 <td> <!--Exec-->W,U
147 <td> <!--Cts-->Cx
148 <td> <!--GUI-->Y
149 <td> <!--Params-->Y
150 <td> <!--Struct-->N
151 <td> <!--Utility-->N
152 <td> <!--Free-->$
153 <td> <!--Undir-->D
154 <td> <!--Inference-->JTree
155 <td> <!--Comments-->Simulation by Dynamic discretisation
156
157 <tr>
158 <td> <!--Name--> <a href=http://www.lumina.com > Analytica</a>
159 <td> <!--Authors-->Lumina
160 <td> <!--Src-->N
161 <td> <!--API-->Y
162 <td> <!--Exec-->W,M
163 <td> <!--Cts-->G
164 <td> <!--GUI-->Y
165 <td> <!--Params-->N
166 <td> <!--Struct-->N
167 <td> <!--Utility-->Y
168 <td> <!--Free-->$
169 <td> <!--Undir-->D
170 <td> <!--Inference-->sampling
171 <td> <!--Comments-->spread sheet compatible
172
173 <tr>
174 <td> <!--Name--> <a href=http://www.cs.duke.edu/~amink/software/banjo/> Banjo</a>
175 <td> <!--Authors-->Hartemink
176 <td> <!--Src-->Java
177 <td> <!--API-->Y
178 <td> <!--Exec-->W,U,M
179 <td> <!--Cts-->Cd
180 <td> <!--GUI-->N
181 <td> <!--Params-->N
182 <td> <!--Struct-->Y
183 <td> <!--Utility-->N
184 <td> <!--Free-->0
185 <td> <!--Undir-->D
186 <td> <!--Inference-->none
187 <td> <!--Comments--> structure learning of
188 static or dynamic networks of discrete variables
189
190
191 <tr>
192 <td><a href=http://www.cs.Helsinki.FI/research/fdk/bassist/> Bassist</a>
193 <td> U. Helsinki
194 <td> C++
195 <td> Y
196 <td> U
197 <td> G
198 <td> N
199 <td> Y
200 <td> N
201 <td> N
202 <td> 0
203 <td> D
204 <td> MH
205 <td> Generates C++ for MCMC.
206
207 <tr>
208 <td><a href=http://www.cs.Helsinki.FI/research/cosco/Projects/NONE/SW/ > Bayda</a>
209 <td> U. Helsinki
210 <td> Java
211 <td> Y
212 <td> WUM
213 <td> G
214 <td> Y
215 <td> Y
216 <td> N
217 <td> N
218 <td> 0
219 <td> D
220 <td> ?
221 <td> Bayesian Naive Bayes classifier.
222
223 <tr>
224 <td><a href=http://www.mbfys.kun.nl/snn/Research/bayesbuilder/ > BayesBuilder</a>
225 <td> Nijman (U. Nijmegen)
226 <td> N
227 <td> N
228 <td> W
229 <td> D
230 <td> Y
231 <td> N
232 <td> N
233 <td> N
234 <td> 0
235 <td> D
236 <td> ?
237 <td> -
238
239 <tr>
240 <td> <!--Name--> <a
241 href="http://www.bayesia.com">BayesiaLab</a>
242 <td> <!--Authors-->Bayesia Ltd
243 <td> <!--Src-->N
244 <td> <!--API-->N
245 <td> <!--Exec-->-
246 <td> <!--Cts-->Cd
247 <td> <!--GUI-->Y
248 <td> <!--Params-->Y
249 <td> <!--Struct-->Y
250 <td> <!--Utility-->N
251 <td> <!--Free-->$
252 <td> <!--Undir-->CG
253 <td> <!--Inference-->jtree,G
254 <td> <!--Comments-->
255 <!--
256 Structural learning (association discovery,
257 classification), Bayesian clustering with analysis report generation,
258 missing values
259 processing, essential graphs, analysis toolbox, adaptive
260 questionnaires, dynamic models
261 -->
262 Structural learning, adaptive
263 questionnaires, dynamic models
264
265
266
267
268 <tr>
269
270 <td><a href=http://www.bayesware.com>Bayesware Discoverer</a>
271 <td> Bayesware
272 <td> N
273 <td> N
274 <td> WUM
275 <td> Cd
276 <td> Y
277 <td> Y
278 <td> Y
279 <td> N
280 <td> $
281 <td> D
282 <td> ?
283 <td> Uses bound and collapse for learning with missing data.
284
285 <tr>
286 <td><a href=http://B-Course.hiit.fi/> B-course</a>
287 <td> U. Helsinki
288 <td> N
289 <td> N
290 <td> WUM
291 <td> Cd
292 <td> Y
293 <td> Y
294 <td> Y
295 <td> N
296 <td> 0
297 <td> D
298 <td> ?
299 <td> Runs on their server: view results using a web browser.
300
301 <!--
302 <tr>
303 <td><a href="http://www.aist.go.jp/ETL/etl/suri/motomura/BN/bn-java.html">Bayonnet</a>
304 <td> Motomura (ETL)
305 <td> Java
306 <td> Y
307 <td> WUM
308 <td> NN
309 <td> Cx
310 <td> Y
311 <td> N
312 <td> N
313 <td> 0
314 <td> D
315 <td> ?
316 <td> For learning, represents BN as a neural net.
317 -->
318
319 <tr>
320 <td><a href=http://www.cs.ualberta.ca/~jcheng/bnpc.htm > Belief net power constructor</a>
321 <td> Cheng (U.Alberta)
322 <td> N
323 <td> W
324 <td> W
325 <td> D
326 <td> Y
327 <td> Y
328 <td> CI
329 <td> N
330 <td> 0
331 <td> D
332 <td> ?
333 <td> -
334
335 <tr>
336 <td><a href=http://www.cs.berkeley.edu/~murphyk/Bayes/bnt.html > BNT</a>
337 <td> Murphy (U.C.Berkeley)
338 <td> Matlab/C
339 <td> Y
340 <td> WUM
341 <td> G
342 <td> N
343 <td> Y
344 <td> Y
345 <td> Y
346 <td> 0
347 <td> D,U
348 <td> Many
349 <td> Also handles dynamic models, like HMMs and Kalman filters.
350
351
352 <tr>
353 <td> <!--Name--> <a href="http://bndev.sourceforge.net/">BNJ</a>
354 <td> <!--Authors-->Hsu (Kansas)
355 <td> <!--Src-->Java
356 <td> <!--API-->-
357 <td> <!--Exec-->-
358 <td> <!--Cts-->D
359 <td> <!--GUI-->Y
360 <td> <!--Params-->N
361 <td> <!--Struct-->Y
362 <td> <!--Utility-->N
363 <td> <!--Free-->0
364 <td> <!--Undir-->D
365 <td> <!--Inference-->jtree, IS
366 <td> <!--Comments-->-
367
368 <!--
369 <tr>
370 <td><a href=http://94.parkview-court.net/project/ > BN Toolkit</a>
371 <td> Gowans (Imperial)
372 <td> Visual Basic
373 <td> Y
374 <td> W
375 <td> D
376 <td> Y
377 <td> N
378 <td> Y
379 <td> N
380 <td> 0
381 <td> D
382 <td> Polytree
383 <td> Parser and GUI for the XML-BIF format.
384 -->
385
386 <tr>
387 <td><a href=http://www.ics.uci.edu/~irinar > BucketElim</a>
388 <td> Rish (U.C.Irvine)
389 <td> C++
390 <td> Y
391 <td> WU
392 <td> D
393 <td> N
394 <td> N
395 <td> N
396 <td> N
397 <td> 0
398 <td> D
399 <td> Varelim
400 <td> -
401
402 <tr>
403 <td><a href=http://www.mrc-bsu.cam.ac.uk/bugs > BUGS</a>
404 <td> MRC/Imperial College
405 <td> N
406 <td> N
407 <td> WU
408 <td> Cs
409 <td> W
410 <td> Y
411 <td> N
412 <td> N
413 <td> 0
414 <td> D
415 <td> Gibbs
416 <td> -
417
418 <tr>
419 <td><a href=http://www.data-digest.com > Business Navigator 5</a>
420 <td> Data Digest Corp
421 <td> N
422 <td> N
423 <td> W
424 <td> Cd
425 <td> Y
426 <td> Y
427 <td> Y
428 <td> N
429 <td> $
430 <td> D
431 <td> Jtree
432 <td> -
433
434 <tr>
435 <td><a href=http://www-pcd.stanford.edu/cousins/caben-1.1.tar.gz > CABeN</a>
436 <td> Cousins et al. (Wash. U.)
437 <td> C
438 <td> Y
439 <td> WU
440 <td> D
441 <td> N
442 <td> N
443 <td> N
444 <td> N
445 <td> 0
446 <td> D
447 <td> 5 Sampling methods
448 <td> -
449
450 <tr>
451 <td> <!--Name--> <a href=
452 http://discover1.mc.vanderbilt.edu/discover/public/>Causal discoverer</a>
453 <td> <!--Authors-->Vanderbilt
454 <td> <!--Src-->N
455 <td> <!--API-->N
456 <td> <!--Exec-->W
457 <td> <!--Cts-->-
458 <td> <!--GUI-->-
459 <td> <!--Params-->N
460 <td> <!--Struct-->Y
461 <td> <!--Utility-->N
462 <td> <!--Free-->0
463 <td> <!--Undir-->D
464 <td> <!--Inference-->-
465 <td> <!--Comments-->structure learning only
466
467
468 <tr>
469 <td><a href=http://www.math.auc.dk/~jhb/CoCo/information.html > CoCo+Xlisp</a>
470 <td> Badsberg (U. Aalborg)
471 <td> C/lisp
472 <td> Y
473 <td> U
474 <td> D
475 <td> Y
476 <td> Y
477 <td> CI
478 <td> N
479 <td> 0
480 <td> U
481 <td> Jtree
482 <td> Designed for contingency tables.
483
484 <tr>
485 <td><a href=http://www.cs.ubc.ca/labs/lci/CIspace/ > CIspace</a>
486 <td> Poole et al. (UBC)
487 <td> Java
488 <td> N
489 <td> WU
490 <td> D
491 <td> Y
492 <td> N
493 <td> N
494 <td> N
495 <td> 0
496 <td> D
497 <td> Varelim
498 <td> -
499
500 <tr>
501 <td> <!--Name--> <a href="http://www.robots.ox.ac.uk/~parg/software.html">DBNbox</a>
502 <td> <!--Authors-->Roberts et al
503 <td> <!--Src-->Matlab
504 <td> <!--API-->-
505 <td> <!--Exec-->-
506 <td> <!--Cts-->Y
507 <td> <!--GUI-->N
508 <td> <!--Params-->Y
509 <td> <!--Struct-->N
510 <td> <!--Utility-->N
511
512 <td> <!--Free-->Y
513 <td> <!--Undir-->D
514 <td> <!--Inference-->Various
515 <td> <!--Comments-->DBNs
516
517 <tr>
518 <td> <!--Name--><a href=http://www.math.auc.dk/novo/deal>Deal</a>
519 <td> <!--Authors-->Bottcher et al
520 <td> <!--Src-->R
521 <td> <!--API-->-
522 <td> <!--Exec-->-
523 <td> <!--Cts-->G
524 <td> <!--GUI-->Y
525 <td> <!--Params-->Y
526 <td> <!--Struct-->Y
527 <td> <!--Utility-->N
528 <td> <!--Free-->0
529 <td> <!--Undir-->D
530 <td> <!--Inference-->None
531 <td> <!--Comments-->
532 Structure learning.
533
534 <tr>
535 <td><a href=http://www.deriveit.com >DeriveIt</a>
536 <td> <!--Authors-->DeriveIt LLC
537 <td> <!--Src-->N
538 <td> <!--API-->-
539 <td> <!--Exec-->-
540 <td> <!--Cts-->?
541 <td> <!--GUI-->?
542 <td> <!--Params-->Y
543 <td> <!--Struct-->Y
544 <td> <!--Utility-->?
545 <td> <!--Free-->$
546 <td> <!--Undir-->D
547 <td> <!--Inference-->Jtree
548 <td> <!--Comments-->
549 Exploits local structure in CPDs.
550
551
552 <tr>
553 <td><a href=http://www.noeticsystems.com>Ergo</>
554 <td> <!--Authors-->Noetic systems
555 <td> <!--Src-->N
556 <td> <!--API-->Y
557 <td> <!--Exec-->W,M
558 <td> <!--Cts-->D
559 <td> <!--GUI-->Y
560 <td> <!--Params-->N
561 <td> <!--Struct-->N
562 <td> <!--Utility-->N
563 <td> <!--Free-->$
564 <td> <!--Undir-->D
565 <td> <!--Inference-->jtree
566 <td> <!--Comments-->-
567
568 <!--
569 <tr>
570 <td><a href=http://www.ens-lyon.fr/~jnarboux/Floue/index.html>FLoUE/BIFtoN</a>
571 <td> ENS Lyon
572 <td> Java
573 <td> Y
574 <td> WUM
575 <td> D
576 <td> N
577 <td> N
578 <td> N
579 <td> N
580 <td> 0
581 <td> D
582 <td> Jtree
583 <td> -
584 -->
585
586 <tr>
587 <td><a href=http://www.staff.ncl.ac.uk/d.j.wilkinson/software/gdagsim/ > GDAGsim</a>
588 <td> Wilkinson (U. Newcastle)
589 <td> C
590 <td> Y
591 <td> WUM
592 <td> G
593 <td> N
594 <td> N
595 <td> N
596 <td> N
597 <td> 0
598 <td> D
599 <td> Exact
600 <td> Bayesian analysis of large linear Gaussian directed models.
601
602
603 <tr>
604 <td><a href=http://www2.sis.pitt.edu/~genie > Genie</a>
605 <td> U. Pittsburgh
606 <td> N
607 <td> WU
608 <td> WU
609 <td> D
610 <td> W
611 <td> N
612 <td> N
613 <td> Y
614 <td> 0
615 <td> D
616 <td> Jtree
617 <td> -
618
619 <tr>
620 <td><a href=http://www.math.ntnu.no/~hrue/GMRFsim/ > GMRFsim</a>
621 <td> Rue (U. Trondheim)
622 <td> C
623 <td> Y
624 <td> WUM
625 <td> G
626 <td> N
627 <td> N
628 <td> N
629 <td> N
630 <td> 0
631 <td> U
632 <td> MCMC
633 <td> Bayesian analysis of large linear Gaussian undirected models.
634
635
636 <tr>
637 <td> <!--Name--> <a href=http://ssli.ee.washington.edu/~bilmes/gmtk/>GMTk</a>
638 <td> <!--Authors-->Bilmes (UW), Zweig (IBM)
639 <td> <!--Src-->N
640 <td> <!--API-->Y
641 <td> <!--Exec-->U
642 <td> <!--Cts-->D
643 <td> <!--GUI-->N
644 <td> <!--Params-->Y
645 <td> <!--Struct-->Y
646 <td> <!--Utility-->N
647 <td> <!--Free-->0
648 <td> <!--Undir-->D
649 <td> <!--Inference-->Jtree
650 <td> <!--Comments-->
651 Designed for speech recognition.
652
653 <tr>
654 <td> <!--Name--> <a href=http://www.r-project.org/gR>gR</a>
655 <td> <!--Authors-->Lauritzen et al.
656 <td> <!--Src-->R
657 <td> <!--API-->-
658 <td> <!--Exec-->-
659 <td> <!--Cts-->-
660 <td> <!--GUI-->-
661 <td> <!--Params-->-
662 <td> <!--Struct-->-
663 <td> <!--Utility-->-
664 <td> <!--Free-->0
665 <td> <!--Undir-->-
666 <td> <!--Inference-->-
667 <td> <!--Comments-->Currently vaporware
668
669
670 <tr>
671 <td> <!--Name--> <a href=http://www.stats.bris.ac.uk/~peter/Grappa/>Grappa</a>
672 <td> <!--Authors-->Green (Bristol)
673 <td> <!--Src-->R
674 <td> <!--API-->-
675 <td> <!--Exec-->-
676 <td> <!--Cts-->D
677 <td> <!--GUI-->N
678 <td> <!--Params-->N)
679 <td> <!--Struct-->N
680 <td> <!--Utility-->N
681 <td> <!--Free-->0
682 <td> <!--Undir-->D
683 <td> <!--Inference-->Jtree
684 <td> <!--Comments-->-
685
686
687 <tr>
688 <td><a href=http://www.hugin.com > Hugin Expert</a>
689 <td> Hugin
690 <td> N
691 <td> Y
692 <td> W
693 <td> G
694 <td> W
695 <td> Y
696 <td> CI
697 <td> Y
698 <td> $
699 <td> CG
700 <td> Jtree
701 <td> -
702
703
704 <tr>
705 <td> <!--Name--> <a href=http://www.warnes.net/GregsSoftwareLinks/index_html?Tab=MCMC>Hydra</a>
706 <td> <!--Authors-->Warnes (U.Wash.)
707 <td> <!--Src-->Java
708 <td> <!--API-->-
709 <td> <!--Exec-->-
710 <td> <!--Cts-->Cs
711 <td> <!--GUI-->Y
712 <td> <!--Params-->Y
713 <td> <!--Struct-->N
714 <td> <!--Utility-->N
715 <td> <!--Free-->0
716 <td> <!--Undir-->U,D
717 <td> <!--Inference-->MCMC
718 <td> <!--Comments-->-
719
720
721 <tr>
722 <!-- http://www.rpal.rockwell.com/ideal.html -->
723 <td><a href=http://yoda.cis.temple.edu:8080/ideal>Ideal</a>
724 <td> Rockwell
725 <td> Lisp
726 <td> Y
727 <td> WUM
728 <td> D
729 <td> Y
730 <td> N
731 <td> N
732 <td> Y
733 <td> 0
734 <td> D
735 <td> Jtree
736 <td> GUI requires Allegro Lisp.
737
738 <tr>
739 <td><a href=http://www.cs.cmu.edu/~javabayes/Home/ > Java Bayes</a>
740 <td> Cozman (CMU)
741 <td> Java
742 <td> Y
743 <td> WUM
744 <td> D
745 <td> Y
746 <td> N
747 <td> N
748 <td> Y
749 <td> 0
750 <td> D
751 <td> Varelim, jtree
752 <td> -
753
754
755 <tr>
756 <td> <!--Name--><a href="http://www.codeas.com/kbaseai.php" >KBaseAI</a>
757 <td> <!--Authors-->Codeas
758 <td> <!--Src-->N
759 <td> <!--API-->Y
760 <td> <!--Exec-->W,U
761 <td> <!--Cts-->D
762 <td> <!--GUI-->N
763 <td> <!--Params-->N
764 <td> <!--Struct-->N
765 <td> <!--Utility-->N
766 <td> <!--Free-->$
767 <td> <!--Undir-->D
768 <td> <!--Inference-->varelim
769 <td> <!--Comments-->client/server architecture, multiple users, access
770 control, query language
771
772
773 <tr>
774 <td> <!--Name--> <a href=http://www.cs.huji.ac.il/labs/compbio/LibB>LibB</a>
775 <td> <!--Authors-->Friedman (Hebrew U)
776 <td> <!--Src-->N
777 <td> <!--API-->Y
778 <td> <!--Exec-->W
779 <td> <!--Cts-->D
780 <td> <!--GUI-->N
781 <td> <!--Params-->Y
782 <td> <!--Struct-->Y
783 <td> <!--Utility-->N
784 <td> <!--Free-->0
785 <td> <!--Undir-->D
786 <td> <!--Inference-->none
787 <td> <!--Comments-->
788 Structure learning
789
790 <tr>
791 <td><a href=http://www.hypergraph.dk/ > MIM</a>
792 <td> HyperGraph Software
793 <td> N
794 <td> N
795 <td> W
796 <td> G
797 <td> Y
798 <td> Y
799 <td> Y
800 <td> N
801 <td> $
802 <td> CG
803 <td> Jtree
804 <td> Up to 52 variables.
805
806 <tr>
807 <td><a href=http://research.microsoft.com/adapt/MSBNx/ > MSBNx</a>
808 <td> Microsoft
809 <td> N
810 <td> Y
811 <td> W
812 <td> D
813 <td> W
814 <td> N
815 <td> N
816 <td> Y
817 <td> 0
818 <td> D
819 <td> Jtree
820 <td> -
821
822 <tr>
823 <td><a href=http://www.norsys.com > Netica</a>
824 <td> Norsys
825 <td> N
826 <td> WUM
827 <td> W
828 <td> G
829 <td> W
830 <td> Y
831 <td> N
832 <td> Y
833 <td> $
834 <td> D
835 <td> jtree
836 <td> -
837
838 <tr>
839 <td> <!--Name--> <a href="http://www.autonlab.org/autonweb/showSoftware/149/">Optimal
840 Reinsertion</a>
841 <td> <!--Authors-->Moore, Wong (CMU)
842 <td> <!--Src-->N
843 <td> <!--API-->N
844 <td> <!--Exec-->W,U
845 <td> <!--Cts-->D
846 <td> <!--GUI-->N
847 <td> <!--Params-->Y
848 <td> <!--Struct-->Y
849 <td> <!--Utility-->N
850 <td> <!--Free-->0
851 <td> <!--Undir-->D
852 <td> <!--Inference-->none
853 <td> <!--Comments-->structure learning
854
855
856 <tr>
857 <td> <!--Name--> <a href="http://people.bu.edu/vladimir/pmt/index.html">PMT</a>
858 <td> <!--Authors-->Pavlovic (BU)
859 <td> <!--Src-->Matlab/C
860 <td> <!--API-->-
861 <td> <!--Exec-->-
862 <td> <!--Cts-->D
863 <td> <!--GUI-->N
864 <td> <!--Params-->Y
865 <td> <!--Struct-->N
866 <td> <!--Utility-->N
867 <td> <!--Free-->0
868 <td> <!--Undir-->D
869 <td> <!--Inference-->special purpose
870 <td> <!--Comments-->-
871
872
873
874 <tr>
875 <td> <!--Name--> <a href=http://www.intel.com/research/mrl/pnl/>PNL</a>
876 <td> <!--Authors-->Eruhimov (Intel)
877 <td> <!--Src-->C++
878 <td> <!--API-->-
879 <td> <!--Exec-->-
880 <td> <!--Cts-->D
881 <td> <!--GUI-->N
882 <td> <!--Params-->Y
883 <td> <!--Struct-->Y
884 <td> <!--Utility-->N
885 <td> <!--Free-->0
886 <td> <!--Undir-->U,D
887 <td> <!--Inference-->Jtree
888 <td> <!--Comments-->
889 A C++ version of BNT; will be released 12/03.
890
891
892 <tr>
893 <td><a href=http://iridia.ulb.ac.be/pulcinella/Welcome.html > Pulcinella</a>
894 <td> IRIDIA
895 <td> Lisp
896 <td> Y
897 <td> WUM
898 <td> D
899 <td> Y
900 <td> N
901 <td> N
902 <td> N
903 <td> 0
904 <td> D
905 <td> ?
906 <td> Uses valuation systems for non-probabilistic calculi.
907
908 <tr>
909 <!-- http://civil.colorado.edu/~dodier/sonero-mirror/index.html -->
910 <td><a href=http://sourceforge.net/projects/riso>RISO</a>
911 <td> Dodier (U.Colorado)
912 <td> Java
913 <td> Y
914 <td> WUM
915 <td> G
916 <td> Y
917 <td> N
918 <td> N
919 <td> N
920 <td> 0
921 <td> D
922 <td> Polytree
923 <td> Distributed implementation.
924
925
926
927 <tr>
928 <td> <!--Name--> <a href=http://reasoning.cs.ucla.edu/samiam/> Sam Iam</a>
929 <td> <!--Authors-->Darwiche (UCLA)
930 <td> <!--Src-->N
931 <td> <!--API-->N ?
932 <td> <!--Exec-->WU ? (Java executable)
933 <td> <!--Cts-->G ?
934 <td> <!--GUI-->Y
935 <td> <!--Params-->Y
936 <td> <!--Struct-->N ?
937 <td> <!--Utility-->Y
938 <td> <!--Free-->0
939 <td> <!--Undir-->D
940 <td> <!--Inference-->Recursive conditioning
941 <td> <!--Comments-->Also does sensitivity Analysis
942
943
944 <tr>
945 <td><a href=http://www.phil.cmu.edu/tetrad/>Tetrad</a>
946 <td> CMU
947 <td> N
948 <td> N
949 <td> WU
950 <td> G
951 <td> N
952 <td> Y
953 <td> CI
954 <td> N
955 <td> 0
956 <td> U,D
957 <td> None
958 <td> -
959
960
961 <tr>
962 <td> <!--Name--> <a href="https://sourceforge.net/projects/unbbayes/">UnBBayes</a>
963 <td> <!--Authors-->?
964 <td> <!--Src-->Java
965 <td> <!--API-->-
966 <td> <!--Exec-->-
967 <td> <!--Cts-->D
968 <td> <!--GUI-->Y
969 <td> <!--Params-->N
970 <td> <!--Struct-->Y
971 <td> <!--Utility-->N
972 <td> <!--Free-->0
973 <td> <!--Undir-->D
974 <td> <!--Inference-->jtree
975 <td> <!--Comments-->K2 for struct learning
976
977
978 <tr>
979 <td><a href=http://www.inference.phy.cam.ac.uk/jmw39/>Vibes</a>
980 <td> Winn & Bishop (U. Cambridge)
981 <td> Java
982 <td> Y
983 <td> WU
984 <td> Cx
985 <td> Y
986 <td> Y
987 <td> N
988 <td> N
989 <td> 0
990 <td> D
991 <td> Variational
992 <td>
993 Not yet available.
994
995
996 <tr>
997 <td><a href=http://snowhite.cis.uoguelph.ca/faculty_info/yxiang/ww3/> Web Weaver</a>
998 <td> Xiang (U.Regina)
999 <td> Java
1000 <td> Y
1001 <td> WUM
1002 <td> D
1003 <td> Y
1004 <td> N
1005 <td> N
1006 <td> Y
1007 <td> 0
1008 <td> D
1009 <td> ?
1010 <td> -
1011
1012 <tr>
1013 <td><a href=http://research.microsoft.com/~dmax/WinMine/tooldoc.htm > WinMine</a>
1014 <td> Microsoft
1015 <td> N
1016 <td> N
1017 <td> W
1018 <td> Cx
1019 <td> Y
1020 <td> Y
1021 <td> Y
1022 <td> N
1023 <td> 0
1024 <td> U,D
1025 <td> None
1026 <td> Learns BN or dependency net structure.
1027
1028 <tr>
1029 <td><a href=http://www.staff.city.ac.uk/~rgc/webpages/xbpage.html > XBAIES 2.0</a>
1030 <td> Cowell (City U.)
1031 <td> N
1032 <td> N
1033 <td> W
1034 <td> G
1035 <td> Y
1036 <td> Y
1037 <td> N
1038 <td> Y
1039 <td> 0
1040 <td> CG
1041 <td> Jtree
1042 <td> -
1043
1044 <tr>
1045
1046 </table>
1047
1048
1049 <p>
1050 <h2>Other sites related to (software for) graphical models</h2>
1051 <ul>
1052
1053
1054 <li>
1055 <a
1056 href="http://directory.google.com/Top/Computers/Artificial_Intelligence/Belief_Networks/Software/">
1057 Google's list</a> of Bayes net software.
1058
1059 <!--
1060 <li> <a href="http://www.sis.pitt.edu/~dsl/da-software.html">
1061 Decision analysis programs</a>, list maintained by
1062 Marek Druzdzel.
1063 -->
1064
1065 <li> <a href="http://www.cs.cmu.edu/~lorens/papers/mscthesis.html">
1066 Comparison of decision analysis software packages</a> by
1067 Håkan L. Younes. The emphasis is on real-time decision making.
1068
1069 <li> <a href="http://bayes.stat.washington.edu/almond/belief.html">
1070 Older belief net programs</a> (c 1996), a list created (but no longer maintained)
1071 by Russ Almond.
1072
1073 <li>
1074 <a
1075 href="http://www.cs.huji.ac.il/labs/compbio/Repository">
1076 Repository of Bayes nets</a>.
1077
1078 </document>