Get our free extension to see links to code for papers anywhere online!

 Add to Chrome

 Add to Firefox

CatalyzeX Code Finder - Browser extension linking code for ML papers across the web! | Product Hunt Embed
AI Poincaré: Machine Learning Conservation Laws from Trajectories

Nov 09, 2020
Ziming Liu, Max Tegmark

* 5 pages, 3 figs 

  Access Paper or Ask Questions

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

Jun 18, 2020
Silviu-Marian Udrescu, Andrew Tan, Jiahai Feng, Orisvaldo Neto, Tailin Wu, Max Tegmark

* 16 pages, 6 figs 

  Access Paper or Ask Questions

Symbolic Pregression: Discovering Physical Laws from Raw Distorted Video

May 19, 2020
Silviu-Marian Udrescu, Max Tegmark

* 12 pages, including 6 figs 

  Access Paper or Ask Questions

Pareto-optimal data compression for binary classification tasks

Aug 23, 2019
Max Tegmark, Tailin Wu

* 15 pages, 8 figs 

  Access Paper or Ask Questions

Learnability for the Information Bottleneck

Jul 17, 2019
Tailin Wu, Ian Fischer, Isaac L. Chuang, Max Tegmark

* Accepted at UAI 2019 

  Access Paper or Ask Questions

AI Feynman: a Physics-Inspired Method for Symbolic Regression

May 27, 2019
Silviu-Marian Udrescu, Max Tegmark

* 14 pages, 2 figs. Our Feynman Symbolic Regression Database for benchmarking can be downloaded at https://space.mit.edu/home/tegmark/aifeynman.html 

  Access Paper or Ask Questions

The role of artificial intelligence in achieving the Sustainable Development Goals

Apr 30, 2019
Ricardo Vinuesa, Hossein Azizpour, Iolanda Leite, Madeline Balaam, Virginia Dignum, Sami Domisch, Anna Felländer, Simone Langhans, Max Tegmark, Francesco Fuso Nerini


  Access Paper or Ask Questions

Latent Representations of Dynamical Systems: When Two is Better Than One

Feb 20, 2019
Max Tegmark

* Improved references and explanation of why two representations generally outperform one for time-irreversible processes. 6 pages, 4 figs 

  Access Paper or Ask Questions

Toward an AI Physicist for Unsupervised Learning

Nov 05, 2018
Tailin Wu, Max Tegmark

* Typos fixed, references added, discussion improved. 18 pages, 7 figs 

  Access Paper or Ask Questions

Meta-learning autoencoders for few-shot prediction

Jul 26, 2018
Tailin Wu, John Peurifoy, Isaac L. Chuang, Max Tegmark


  Access Paper or Ask Questions

The power of deeper networks for expressing natural functions

Apr 27, 2018
David Rolnick, Max Tegmark

* Replaced to match version published at ICLR 2018. 14 pages, 2 figs 

  Access Paper or Ask Questions

Gated Orthogonal Recurrent Units: On Learning to Forget

Oct 25, 2017
Li Jing, Caglar Gulcehre, John Peurifoy, Yichen Shen, Max Tegmark, Marin Soljačić, Yoshua Bengio


  Access Paper or Ask Questions

Criticality in Formal Languages and Statistical Physics

Aug 23, 2017
Henry W. Lin, Max Tegmark

* Entropy, 19, 299 (2017) 
* Replaced to match final published version. Discussion improved, references added 

  Access Paper or Ask Questions

Why does deep and cheap learning work so well?

Aug 03, 2017
Henry W. Lin, Max Tegmark, David Rolnick

* Replaced to match version published in Journal of Statistical Physics: https://link.springer.com/article/10.1007/s10955-017-1836-5 Improved refs & discussion, typos fixed. 16 pages, 3 figs 

  Access Paper or Ask Questions

Tunable Efficient Unitary Neural Networks (EUNN) and their application to RNNs

Apr 03, 2017
Li Jing, Yichen Shen, Tena Dubček, John Peurifoy, Scott Skirlo, Yann LeCun, Max Tegmark, Marin Soljačić

* 9 pages, 4 figures 

  Access Paper or Ask Questions

Research Priorities for Robust and Beneficial Artificial Intelligence

Feb 10, 2016
Stuart Russell, Daniel Dewey, Max Tegmark

* AI Magazine 36:4 (2015) 
* This article gives examples of the type of research advocated by the open letter for robust & beneficial AI at http://futureoflife.org/ai-open-letter 

  Access Paper or Ask Questions

Friendly Artificial Intelligence: the Physics Challenge

Sep 03, 2014
Max Tegmark

* In proceedings of the AAAI 2015 Workshop On AI and Ethics, p87, Toby Walsh, Ed. (2015) 
* 3 pages 

  Access Paper or Ask Questions

The importance of quantum decoherence in brain processes

Nov 10, 1999
Max Tegmark

* Phys.Rev.E61:4194-4206,2000 
* Minor changes to match accepted PRE version. 15 pages with 5 figs included. Color figures and links at http://www.physics.upenn.edu/~max/brain.html or from [email protected]. Physical Review E, in press 

  Access Paper or Ask Questions