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Comment below with questions or thoughts about the reading for this week's workshop.
Please make your comments by Wednesday 11:59 PM, and upvote at least five of your peers' comments on Thursday pr…
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Post questions here for this week's fundamental readings:
Grimmer, Justin, Molly Roberts, Brandon Stewart. 2022. Text as Data. Princeton University Press: Chapters 17, 18, 20, 21, 22 —“An Overview …
lkcao updated
3 months ago
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I am not sure if I can ask here, or email the authors of the paper.... I really do not know with whom to discuss this, but I will try my luck here.
After reading the DICE paper, my understanding is…
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Ciao @gdario! I'm also learning (on-and-off) about the methods involved in causal inference :smile:. Hope we get a chance to exchange notes!!
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- Advanced type of Language Model using Deep learning techniques using heavy text data.
- Capable of generating human like text. QnA, Text2Text
- Concepts like n-gram to Neural Networks are used. …
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- [x] [Cooper GF. A simple algorithm for efficiently mining observational databases for causal relationships](https://www.dbmi.pitt.edu/sites/default/files/Cooper_9.pdf)
- [x] [Detection of pharmacov…
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### Describe the workflow you want to enable
Conformal prediction (CP) is a statistical technique for producing prediction sets without assumptions on the predictive algorithm (often a machine learni…
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This is a proposal for a simplified approach to graphs and rules that operate on them, using ideas that have been developed over many decades in the field of Cognitive Psychology. The starting point i…
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In terms of functionality, the mid-term end goal is to achieve an offering of ML algorithms and pre-processing routines comparable to what is currently available in Python's [`scikit-learn`](https://s…
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### Task motivation
Gene Regulatory Network (GRN) inference is pivotal in systems biology, offering profound insights into the complex mechanisms that govern gene expression and cellular behavior. Th…