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Future Blog Post

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List of Causal Libraries

causalaiSalesforcePythonDiscovery | Time Series | basic-inference
pycidCausal Incentives Working
Group a collaboration with
Oxford, DeepMind
and Toronto researchers
Pythonbayesian-networks | influence-diagrams
causal-learnCenter for Causal Discovery, pittsbughPythondiscovery |hidden-causal | Time Series
basic-inference | tetrad
CausalImpactGoogle, IncRBayesian time-series
EconMLMicrosoft ResearchPythonMachine Learning Based Estimation
of Heterogeneous Treatment Effects
causalnexPetuumPythonaugment model | structure learning
dowhyMicrosoft ResearchPythonDouble ML | Matching | Balancing
Synthetic control
Outcome-based Learners (e.f. X-Learner)
Dif&Dif | basic-inference
causalToolboxUniversity of CaliforniaRX-learner
showwhyMicrosoft ResearchTypeScriptno-code interfaces
The University of Texas at Austin
Rcomputer-vision | earth-observation
gCastleHuawei Noah's Ark LabPythonStructure Learning
gradient-based learning
causal-cmdCenter for Causal Discovery, pittsbughjavaCMD based | discovery
ResearchMapUCLAJSOptimal experiments | augmented models

Список для чтения по поведенческой и экспериментальной экономике

5 лет назад совместно с «Всероссийской государственной библиотекой иностранной литературы имени М.И.Рудомино» я сделал рекомендательный список литературы и периодики, посвященных поведенческой экономике. Публикую его сегодня, следуя рекомендации, когда-то данной мне Быковским – спустя 5 лет, и сопровождая сегодняшними комментариями.





Teaching experience 1

This is a description of a teaching experience. You can use markdown like any other post.

Teaching experience 2

This is a description of a teaching experience. You can use markdown like any other post.