From 0b96f05325525fecff6a0b17b9ee8ef07b6ef877 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?=E9=99=88=E9=94=AE=E9=A3=9E?= <chrisjianfeichen@gmail.com>
Date: Sat, 19 Dec 2020 22:41:23 +0800
Subject: [PATCH] add sigs/mdp/roadmap_2021.md.

Revised roadmap

Revised roadmap
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 create mode 100644 sigs/mdp/roadmap_2021.md

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+Technical Roadmap for 2021
+====
+
+Probabilistic Programming Layer
+----
+
+Distribution:
+
+- [D1] add support to multivariate continous distributions
+- [D1.1] MultivariateNormal
+- [D1.2] GumbelSoftmax
+- [D1.3] Dirichlet
+
+Expected time: Q3
+
+Modeling Language:
+
+- [M1] Based on the new support of MindSpore, extend the BayesianNet modeling capacity to general
+- [M1.1] Implement with dictionaies
+- [M1.2] Integrate StochasticTensor with Distribution
+
+Expected time: Q1
+
+- [M2] Hybrid BayesianNet + Bijector modeling language
+- [M2.1] Implement a bijector API, and integrate it with the existing bijector in distributions
+- [M2.2] Implement affine coupling layer
+- [M2.3] Reimplement the existing Glow / VFlow in the test folder with the new API
+
+Depends on: M1
+Expected time: Q4
+
+Inference algorithm:
+
+- [I1] Support common black-box algorithms
+- [I1.1] Importance sampling
+- [I1.2] SGLD
+- [I1.3] Reinforce
+- [I1.4] HMC
+
+Depends on: M1
+Expected time: [I1.1]:Q1, [I1.2]:Q2, [I1.3]:Q3, [I1.4]:Q4
+
+Model and Toolbox Layer
+----
+
+- [T1] Reimplement existing model and toolbox with the probabilistic programming layer
+- [T1.1] Reimplement VAE
+- [T1.2] Reimplement BNN
+- [T1.3] Reimplement Uncertainty Estimation
+- [T1.4] Reimplement Anormaly Detection
+
+Depends on: M1
+Expected time: Q2
+
+- [T2] Implement more SOTA algorithms of toolbox
+- [T2.1] BNN with SGLD for uncertainty estimation
+  Depends on: M1, I1.2
+  Expected time: Q2
+- [T2.2] SWAG for uncertainty estimation
+  Depends on: D1.1, M1
+  Expected time: Q3
+
+(Optional) Test uncertainty estimation on language modeling
+
+Appliation
+----
+
+- [A1] Apply our tools to representative applications
+
+Depends on: T2
+Expected time: Q4
+
+Miscellanous
+----
+
+Keep interacting with MindSpore to improve the coding style.
+
+Expected Goal
+----
+
+Q1:
+
+- A general BayesianNet framework, that supports modeling of arbitary Bayesian networks
+
+Q2:
+
+- Support representative inference algorithms in the general format
+- Rewrite applications and examples with the new interface
+
+Q3:
+
+- Implement more distributions, inference algorithms
+- Implement some SOTA algorithms for uncertainty estimation
+- Should have a comparable version of TF ZhuSuan now
+
+Q4:
+
+- Modeling tools for flow bases
+- Tentative applications of uncertainty estimation
+