Search Results for author: Andrew Tan

Found 2 papers, 2 papers with code

AI Feynman 2.0: Pareto-optimal symbolic regression exploiting graph modularity

2 code implementations NeurIPS 2020 Silviu-Marian Udrescu, Andrew Tan, Jiahai Feng, Orisvaldo Neto, Tailin Wu, Max Tegmark

We present an improved method for symbolic regression that seeks to fit data to formulas that are Pareto-optimal, in the sense of having the best accuracy for a given complexity.

Symbolic Regression Two-sample testing

Sentiment Predictability for Stocks

1 code implementation15 Dec 2017 Jordan Prosky, Xingyou Song, Andrew Tan, Michael Zhao

In this work, we present our findings and experiments for stock-market prediction using various textual sentiment analysis tools, such as mood analysis and event extraction, as well as prediction models, such as LSTMs and specific convolutional architectures.

Event Extraction Sentiment Analysis +1

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