Stochastic Processes - Histórico de revisão

V1z: moved prev periods

2024-08-08T01:51:14Z

moved prev periods

← Edição anterior		Edição das 22h51min de 7 de agosto de 2024
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	This is the main page of an undergraduate-level course in stochastic processes targeted at engineering students (mainly computer engineering and its interface with mechanical engineering), being taught in 2024 (2024.2 period) at the Polytechnic Institute [http://pt.wikipedia.org/wiki/IPRJ IPRJ]/UERJ.		This is the main page of an undergraduate-level course in stochastic processes targeted at engineering students (mainly computer engineering and its interface with mechanical engineering), being taught in 2024 (2024.2 period) at the Polytechnic Institute [http://pt.wikipedia.org/wiki/IPRJ IPRJ]/UERJ.

	~~Previous periods: 2023 (see wiki history) [[Stochastic_Processes_2022.2\|2022.2]], [[Stochastic_Processes_2021_condensed\|2021 condensed]], [[Stochastic_Processes_2021.2_2022\|2021.2 (2022)]].~~

	[[Image:Mocap_transfer.png\|right\|250px\|thumb\|Recent application of [https://en.wikipedia.org/wiki/Gaussian_process Gaussian stochastic processes] for 3D motion capture transfer [http://openaccess.thecvf.com/content_cvpr_2017/papers/Boukhayma_Surface_Motion_Capture_CVPR_2017_paper.pdf (CVPR 2017)] ]]		[[Image:Mocap_transfer.png\|right\|250px\|thumb\|Recent application of [https://en.wikipedia.org/wiki/Gaussian_process Gaussian stochastic processes] for 3D motion capture transfer [http://openaccess.thecvf.com/content_cvpr_2017/papers/Boukhayma_Surface_Motion_Capture_CVPR_2017_paper.pdf (CVPR 2017)] ]]
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	== Keywords ==		== Keywords ==
	random fields, stochastic modeling, data science, queue theory, machine learning, poisson process, markov chains, Gaussian processes, Bernoulli processes, soft computing, random process, Brownian motion, robot path planning, artificial intelligence, simulation, sampling, pattern formation, signal processing, text processing, image processing, dimentionality reduction, diffusion, Markov Chain Monte Carlo MCMC, tracking, branching process, stochastic calculus, SDEs		random fields, stochastic modeling, data science, queue theory, machine learning, poisson process, markov chains, Gaussian processes, Bernoulli processes, soft computing, random process, Brownian motion, robot path planning, artificial intelligence, simulation, sampling, pattern formation, signal processing, text processing, image processing, dimentionality reduction, diffusion, Markov Chain Monte Carlo MCMC, tracking, branching process, stochastic calculus, SDEs

			== See Also ==
			Previous periods: 2023 (see wiki history) [[Stochastic_Processes_2022.2\|2022.2]], [[Stochastic_Processes_2021_condensed\|2021 condensed]], [[Stochastic_Processes_2021.2_2022\|2021.2 (2022)]].


	[[Category:Lab Macambira]] [[Category:IPRJ]]		[[Category:Lab Macambira]] [[Category:IPRJ]]

V1z: 2024.2, criterio de avaliacao simplificado

2024-08-08T01:50:21Z

2024.2, criterio de avaliacao simplificado

← Edição anterior		Edição das 22h50min de 7 de agosto de 2024
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	This is the main page of an undergraduate-level course in stochastic processes targeted at engineering students (mainly computer engineering and its interface with mechanical engineering), being taught in ~~2022~~ (~~2022~~.2 period) at the Polytechnic Institute [http://pt.wikipedia.org/wiki/IPRJ IPRJ]/UERJ.		This is the main page of an undergraduate-level course in stochastic processes targeted at engineering students (mainly computer engineering and its interface with mechanical engineering), being taught in 2024 (2024.2 period) at the Polytechnic Institute [http://pt.wikipedia.org/wiki/IPRJ IPRJ]/UERJ.

	Previous periods: [[Stochastic_Processes_2022.2\|2022.2]], [[Stochastic_Processes_2021_condensed\|2021 condensed]], [[Stochastic_Processes_2021.2_2022\|2021.2 (2022)]].		Previous periods: 2023 (see wiki history) [[Stochastic_Processes_2022.2\|2022.2]], [[Stochastic_Processes_2021_condensed\|2021 condensed]], [[Stochastic_Processes_2021.2_2022\|2021.2 (2022)]].

	[[Image:Mocap_transfer.png\|right\|250px\|thumb\|Recent application of [https://en.wikipedia.org/wiki/Gaussian_process Gaussian stochastic processes] for 3D motion capture transfer [http://openaccess.thecvf.com/content_cvpr_2017/papers/Boukhayma_Surface_Motion_Capture_CVPR_2017_paper.pdf (CVPR 2017)] ]]		[[Image:Mocap_transfer.png\|right\|250px\|thumb\|Recent application of [https://en.wikipedia.org/wiki/Gaussian_process Gaussian stochastic processes] for 3D motion capture transfer [http://openaccess.thecvf.com/content_cvpr_2017/papers/Boukhayma_Surface_Motion_Capture_CVPR_2017_paper.pdf (CVPR 2017)] ]]
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	== General Info ==		== General Info ==
	* Instructor: prof. [http://rfabbri.github.io Ricardo Fabbri], Ph.D. Brown University		* Instructor: prof. [http://rfabbri.github.io Ricardo Fabbri], Ph.D. Brown University
	* Meeting times (in-person): tuesdays T2,T3 and wednesdays T6,N1.
	* Chat: IRC #labmacambira for random chat		* Chat: IRC #labmacambira for random chat

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	<pre>		<pre>
	P = (P1 + P2)/2		P = (P1 + P2)/2
	~~N = 0.9P + 0.1T~~
	~~Onde T = nota de todos tabalhos e tarefas.~~

	if N >= 7 --> passa ~~direto, final opcional~~		if P >= 5 --> passa direto
	~~if 4 <= N < 7 --> final obrigatoria~~
	~~if N < 4 --> reprova~~ direto

	M = (F + N)/2 para os que fizerem final		Trabalhos serão dados após a P1 de acordo com a demanda da turma, sendo a pontuação inclusa na P2.

			Final F opcional

			M = (F + P)/2 para os que fizerem final

	if M >= 5 --> passa		if M >= 5 --> passa

V1z: /* Evaluation criteria */

2023-08-16T19:46:08Z

Evaluation criteria

← Edição anterior		Edição das 16h46min de 16 de agosto de 2023
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	<pre>		<pre>
	P = (P1 + P2)/2		P = (P1 + P2)/2
	N = 0.8P + 0.2T		N = 0.9P + 0.1T
	Onde T = nota de todos tabalhos e tarefas.		Onde T = nota de todos tabalhos e tarefas.

V1z: /* Evaluation criteria */

2023-08-16T19:45:19Z

Evaluation criteria

← Edição anterior		Edição das 16h45min de 16 de agosto de 2023
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	<pre>		<pre>
	P = (P1 + P2)/2		P = (P1 + P2)/2
	N = 0.7P + 0.3T		N = 0.8P + 0.2T
	Onde T = nota de todos tabalhos e tarefas.		Onde T = nota de todos tabalhos e tarefas.

V1z: /* Exams */

2023-08-16T19:06:39Z

Exams

← Edição anterior		Edição das 16h06min de 16 de agosto de 2023
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	== Exams ==		== Exams ==
	* '''P1:''' ter19set23		* '''P1:''' ter19set23
	* '''P2:'''' ter17out23		* '''P2:''' ter17out23
	* '''Final-Sub:''' ter19dez2		* '''Final-Sub:''' ter19dez2

V1z: p1 p2 final

2023-08-16T19:06:10Z

p1 p2 final

← Edição anterior		Edição das 16h06min de 16 de agosto de 2023
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	== Exams ==		== Exams ==
	* '''P1:''' ~~07dec22~~		* '''P1:''' ter19set23
	* '''P2:'''' ~~01fev22~~		* '''P2:'''' ter17out23
	* '''Final-Sub:''' ~~15fev22~~		* '''Final-Sub:''' ter19dez2

	== Evaluation criteria ==		== Evaluation criteria ==

V1z: first pass for 2023

2023-08-16T19:01:17Z

first pass for 2023

← Edição anterior		Edição das 16h01min de 16 de agosto de 2023
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	This is the main page of an undergraduate-level course in stochastic processes targeted at engineering students (mainly computer engineering and its interface with mechanical engineering), being taught in 2022 (2022.2 period) at the Polytechnic Institute [http://pt.wikipedia.org/wiki/IPRJ IPRJ]/UERJ.		This is the main page of an undergraduate-level course in stochastic processes targeted at engineering students (mainly computer engineering and its interface with mechanical engineering), being taught in 2022 (2022.2 period) at the Polytechnic Institute [http://pt.wikipedia.org/wiki/IPRJ IPRJ]/UERJ.

	Previous periods: [[Stochastic_Processes_2021_condensed\|2021 condensed]], [[Stochastic_Processes_2021.2_2022\|2021.2 (2022)]].		Previous periods: [[Stochastic_Processes_2022.2\|2022.2]], [[Stochastic_Processes_2021_condensed\|2021 condensed]], [[Stochastic_Processes_2021.2_2022\|2021.2 (2022)]].

	[[Image:Mocap_transfer.png\|right\|250px\|thumb\|Recent application of [https://en.wikipedia.org/wiki/Gaussian_process Gaussian stochastic processes] for 3D motion capture transfer [http://openaccess.thecvf.com/content_cvpr_2017/papers/Boukhayma_Surface_Motion_Capture_CVPR_2017_paper.pdf (CVPR 2017)] ]]		[[Image:Mocap_transfer.png\|right\|250px\|thumb\|Recent application of [https://en.wikipedia.org/wiki/Gaussian_process Gaussian stochastic processes] for 3D motion capture transfer [http://openaccess.thecvf.com/content_cvpr_2017/papers/Boukhayma_Surface_Motion_Capture_CVPR_2017_paper.pdf (CVPR 2017)] ]]
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	== General Info ==		== General Info ==
	* Instructor: prof. [http://rfabbri.github.io Ricardo Fabbri], Ph.D. Brown University		* Instructor: prof. [http://rfabbri.github.io Ricardo Fabbri], Ph.D. Brown University
	* Meeting times (in-person): tuesdays T2,T3 e wednesdays T6,N1.		* Meeting times (in-person): tuesdays T2,T3 and wednesdays T6,N1.
	* Chat: IRC #labmacambira for random chat		* Chat: IRC #labmacambira for random chat

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	<pre>		<pre>
	P = (P1 + P2)/2		P = (P1 + P2)/2
	N = 0.6P + 0.4T		N = 0.7P + 0.3T
	Onde T = nota de todos tabalhos e tarefas.		Onde T = nota de todos tabalhos e tarefas.

V1z: /* Evaluation criteria */

2022-10-22T13:17:20Z

Evaluation criteria

← Edição anterior		Edição das 10h17min de 22 de outubro de 2022
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	== Evaluation criteria ==		== Evaluation criteria ==
	~~```~~		<pre>
	P = (P1 + P2)/2		P = (P1 + P2)/2
	N = 0.6P + 0.4T		N = 0.6P + 0.4T
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	if M >= 5 --> passa		if M >= 5 --> passa
	else reprova		else reprova
	~~```~~		</pre>

	== Awesome Links ==		== Awesome Links ==

V1z: /* Evaluation criteria */

2022-10-22T13:16:52Z

Evaluation criteria

@@ Linha 134: / Linha 134: @@
 == Evaluation criteria ==
-See course plan on moodle, tab "Boas-vindas".
+```
 == Awesome Links ==

V1z: datas provas

2022-10-22T12:57:03Z

datas provas

← Edição anterior		Edição das 09h57min de 22 de outubro de 2022
Linha 1:		Linha 1:
	This is the main page of an undergraduate-level course in stochastic processes targeted at engineering students (mainly computer engineering and its interface with mechanical engineering), being taught in 2022 (2022.2 period) at the Polytechnic Institute [http://pt.wikipedia.org/wiki/IPRJ IPRJ]/UERJ.		This is the main page of an undergraduate-level course in stochastic processes targeted at engineering students (mainly computer engineering and its interface with mechanical engineering), being taught in 2022 (2022.2 period) at the Polytechnic Institute [http://pt.wikipedia.org/wiki/IPRJ IPRJ]/UERJ.

	Previous periods: [[Stochastic_Processes_2021_condensed\|2021 condensed]] [[Stochastic_Processes_2021.2_2022\|2021.2 (2022)]].		Previous periods: [[Stochastic_Processes_2021_condensed\|2021 condensed]], [[Stochastic_Processes_2021.2_2022\|2021.2 (2022)]].

	[[Image:Mocap_transfer.png\|right\|250px\|thumb\|Recent application of [https://en.wikipedia.org/wiki/Gaussian_process Gaussian stochastic processes] for 3D motion capture transfer [http://openaccess.thecvf.com/content_cvpr_2017/papers/Boukhayma_Surface_Motion_Capture_CVPR_2017_paper.pdf (CVPR 2017)] ]]		[[Image:Mocap_transfer.png\|right\|250px\|thumb\|Recent application of [https://en.wikipedia.org/wiki/Gaussian_process Gaussian stochastic processes] for 3D motion capture transfer [http://openaccess.thecvf.com/content_cvpr_2017/papers/Boukhayma_Surface_Motion_Capture_CVPR_2017_paper.pdf (CVPR 2017)] ]]
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	* ''An Introduction to Stochastic Modeling'', Taylor & Karlin		* ''An Introduction to Stochastic Modeling'', Taylor & Karlin
	* ''Pattern Theory: The Stochastic Analysis of Real-World Signals'', David Mumford and Agnes Desolneux - the first chapters already cover many types of stochastic processes in text, signal and image AI [[Image:Mumford-book.jpg]]		* ''Pattern Theory: The Stochastic Analysis of Real-World Signals'', David Mumford and Agnes Desolneux - the first chapters already cover many types of stochastic processes in text, signal and image AI [[Image:Mumford-book.jpg]]
	* My own machine learning and computational modeling book draft, co-written with prof. Francisco Duarte Moura Neto and focused on diffusion processes on graphs like PageRank. There is a probability chapter which is the basis for this course~~. We have many copies at [[IPRJ]]'s library~~.		* My own machine learning and computational modeling book draft, co-written with prof. Francisco Duarte Moura Neto and focused on diffusion processes on graphs like PageRank. There is a probability chapter which is the basis for this course.

	==== Other books to look at ====		==== Other books to look at ====
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	=== Assignment 5: Exercise list for chapter 5 (MCMC) ===		=== Assignment 5: Exercise list for chapter 5 (MCMC) ===
	4 Exercises: 5.1, 5.2, 5.5, 5.6		4 Exercises: 5.1, 5.2, 5.5, 5.6
	* Due date: ~~terca 5abr22 23:59~~		* Due date: before P2 (suggested)

	=== Assignment 6: Exercise list for chapter 6 ===		=== Assignment 6: Exercise list for chapter 6 ===
	4 Exercises: 6.3, 6.4, 6.7, 6.8		4 Exercises: 6.3, 6.4, 6.7, 6.8
	* Due date: ~~Ter12abr22~~		* Due date: before P2 (suggested)

	== Exams ==		== Exams ==
	* '''P1:''' ~~22mar22~~		* '''P1:''' 07dec22
	* '''P2:'''' ~~16-18mai22 (escolher)~~		* '''P2:'''' 01fev22
	* '''Final-Sub:''' ~~19-20mai22 (escolher)~~		* '''Final-Sub:''' 15fev22

	== Evaluation criteria ==		== Evaluation criteria ==