"How can I print this paper without edges trimmed off?"
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Neural Quantum States
Picture by By Tatiana Shepeleva/shutterstock.comOne of the most challenging problems in modern theoretical physics is the so-called many-body problem. Typical many-body systems are composed of a large number of strongly interacting particles. Few such systems are amenable to exact mathematical treatment and numerical techniques are needed to make progress. However, since the resources required to specify a…See More
Connections between Neural Networks and Pure Mathematics
Nowadays, artificial intelligence is present in almost every part of our lives. Smartphones, social media feeds, recommendation engines, online ad networks, and navigation tools are examples of AI-based applications that affect us on a daily basis.Deep learning has been systematically improving the state of the art in areas such as speech recognition, autonomous driving, machine translation, and visual object recognition. However, the reasons why deep learning works so spectacularly well are…See More
"Instead of lags, you could work in the spectral domain. The power spectral density (Fourier transform of the autocorrelation) decays with exponent -(1+2H)."
"only half of it"
How the Mathematics of Fractals Can Help Predict Stock Markets Shifts
In financial markets, two of the most common trading strategies used by investors are the momentum and mean reversion strategies. If a stock exhibits momentum (or trending behavior as shown in the figure below), its price on the current period is more likely to increase (decrease) if it has…See More
How the Mathematics of Fractals Can Help Predict Stock Markets Shifts
In financial markets, two of the most common trading strategies used by investors are the momentum and mean reversion strategies. If a stock exhibits momentum (or trending behavior as shown in the figure below), its price on the current period is more likely to increase (decrease) if it has…See More
Profile Information
- Company:
- Prior Solutions
- Job Title:
- Co-Founder and CTO
- Seniority:
- Executive
- Job Function:
- Data Science, Machine Learning, Deep Learning
- Industry:
- Consulting
- Short Bio:
- I am a theoretical physicist and data scientist. During my Ph.D. at New York University, my research was on quantum many-body systems out of equilibrium, one of today's hottest research fields in theoretical physics. In 2015 I earned a Ph.D. for my thesis "Prethermalization, universal scaling at macroscopic short times, and thermalization following a quantum quench." Subsequently, I spent two years as a postdoctoral researcher focusing on applications of computational physics methods to areas such as quantum chaos, non-equilibrium quantum dynamics, and thermalization viability. I've published several articles in the most prestigious peer-reviewed journals in the world.
I have 15 years of experience building mathematical/statistical models spanning a wide range of disciplines, including: non-equilibrium quantum systems, marketing attribution for digital and offline channels (using machine learning, game theory, stochastic processes and hierarchical Bayesian models), influencer marketing, marketing mix modeling, record linkage/data matching/entity recognition, conjoint analysis (using support vector machines), bidding optimization for digital media (using original functional optimization techniques) and many others.
I was a speaker at the American Physical Society (APS) March Meeting, the largest physics conference in the United States, in 2013, 2015 and 2016 (for more details and also information about other conferences see my personal website www.marcotavora.me)
In 2017 I co-founded Prior Solutions, a data-driven consulting company with clients in more than ten countries around the world.
- LinkedIn Profile:
- http://marcotavora.me
- Interests:
- Contributing, Networking
Marco Tavora's Blog
Connections between Neural Networks and Pure Mathematics
Posted on January 5, 2020 at 5:30am 0 Comments 2 Likes
Nowadays, artificial intelligence is present in almost every part of our lives. Smartphones, social media feeds, recommendation engines, online ad networks, and navigation tools are examples of AI-based applications that affect us on a daily basis.
Deep learning has been systematically improving the state of the art in areas such as speech recognition, autonomous driving, machine translation,…
ContinueNeural Quantum States
Posted on January 5, 2020 at 4:30am 0 Comments 0 Likes
Picture by By Tatiana Shepeleva/shutterstock.com
One of the most challenging problems in modern theoretical physics is the so-called many-body problem. Typical many-body systems are composed of a large number of strongly interacting particles. Few such systems are amenable to exact…
ContinueHow the Mathematics of Fractals Can Help Predict Stock Markets Shifts
Posted on July 4, 2019 at 12:30am 3 Comments 5 Likes
In financial markets, two of the most common trading strategies used by investors are the momentum and mean reversion strategies. If a stock exhibits momentum…
Deep Learning Explainability: Hints from Physics
Posted on May 20, 2019 at 11:46am 0 Comments 2 Likes
Nowadays, artificial intelligence is present in almost every part of our lives. Smartphones, social media feeds, recommendation engines, online ad networks, and navigation tools are some…
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