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High-performance Machine Learning / AI algorithms have been inadequate in precisely explaining their so-called accurate predictions. Balance of engineering and domain expertise helped us build consistent, robust, and domain-expertise-backed models that drive real growth for R&D Labs across the world. Know more: https://polymerize.io/

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Published by POLYMERIZE PTE LTD, 2022-07-18 12:51:58

An exhaustive guide to Explainable AI for Material Science & Informatics

High-performance Machine Learning / AI algorithms have been inadequate in precisely explaining their so-called accurate predictions. Balance of engineering and domain expertise helped us build consistent, robust, and domain-expertise-backed models that drive real growth for R&D Labs across the world. Know more: https://polymerize.io/

An exhaustive guide to
Explainable AI for Material

Science & Informatics

High-performance Machine
Learning / AI algorithms
have been inadequate in
precisely explaining their
so-called accurate
predictions.

In the majority of cases, there are fundamental issues ( overfitting, high
complexity, generalization errors ) with the models and/or the process that
haunt engineers later, after they’ve invested a significant amount of time and

resources, eventually finding out the discrepancy.

Our team of experts ( Polymer and AI Scientists ) solved this problem
by using a comprehensive closed-loop strategy.

The AI engineers made sure
they open the black-box

models (with explainability
and interpretability), to
quantify and highlight

relationships between the
input formulations and output

properties in the data.

Consequently, Polymer Scientists were responsible for analyzing
and validating given relationships with academic research and
development frameworks of the industry before approving the

model for usage.

Power your materials
research with Polymerize

today

Contact Us:


Address:

Polymerize, 11 IRVING PLACE, #09-01,
Singapore, Singapore 369551


Business mail:
[email protected]


Phone:
+65 3138 5586


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