Frank Nielsen @FrnkNlsn
Machine Learning & AI, Information Sciences & Information Geometry, Distances & Statistical models, HPC. "Geometry defines the architecture of spaces" @SonyCSL franknielsen.github.io/index.html Tokyo 東京 Joined February 2010-
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Selected books on optimal transport and its geometry: Wasserstein distances, Kantorovich-Rubinstein duality, Sinkhorn divergence, etc Applications in machine learning, AI, economics and finance
Some selected books on Algebraic Statistics, a field which considers computational algebra, algebraic geometry, and combinatorics among others to tackle problems in statistics.
Merci!
Mathematics, physics: the endless landscape. "Taxonomy of Principal Distances and Divergences" — ranging from Euclidean Geometry (upper left) to Quantum and Matrix Geometry (lower right). By Frank Nielsen, @FrnkNlsn, franknielsen.github.io/Divergence/ind…, Used with permission.
Forthcoming event for French-speaking attendees: Entropy and divergences: modeling, statistics, and algorithms, 14-17 mai 2024 Caen, France edmsa.sciencesconf.org/resource/page/… Present recent results: Fisher-Rao, max invariants, duo Bregman franknielsen.github.io/npublications.… franknielsen.github.io/Divergence/ind…
① Densities of an exponential family with fixed support truncation form another exponential family ② Kullback-Leibler divergence between truncated densities of an exponential family is a duo Bregman divergence when finite: Duo: generators F1≥F2 👉mdpi.com/1099-4300/24/3…
Upper bound differential entropy of any random variable X by differential entropy of *any exponential family* for the moment parameter η=E_X[t(x)] where t(x) is the sufficient statistics of the exponential family {p_θ}: H(X) ≤ H(p_θ)=-F^*(E_X[t(x)]) 👉arxiv.org/abs/1612.02954
A moduli space is a set of isomorphism classes turned into a topological space using a notion of closeness between equivalence classes. Nice blog by John Baez on the moduli space of acute triangles. Acute triangles are encoded in the upper space. golem.ph.utexas.edu/category/2023/…
User-friendly Introduction to PAC-Bayes Bounds by @PierreAlquier nowpublishers.com/article/Detail… arxiv.org/abs/2110.11216 Book added to my curated list of books! franknielsen.github.io/Books/CuratedB…
Great work collection!
Today's two cents while programming... Optimizing is easier task than knowing what to optimize!
ALT
Lattice Gaussian/normal distributions are discrete distributions with sample spaces lattices. Lattice Gaussians maximize entropy, form an exponential family with cumulant function related to Riemann theta function. 👉 Web page with paper+slides+video: franknielsen.github.io/LatticeGaussia…
What are powerful words used implicitly in mathematics? For example, imho, "identify" allows to cast spaces to other spaces using common sense.
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22K Followers 693 Following Co-founder & CEO @pika_labs | ex @StanfordAILab @HarvardHaving a lot fun with this book describing some of the great #experiences of science, eg. test of general relativity, measuring the Earth's size, DNA, cloning, observing microbes, speed of light, neutrinos,... When at school, I wish I was taught #physics this way!
First 3 chapters of the book in pdf: bayes.wustl.edu/etj/prob/book.…
Can you assign a size to every object? Surprisingly: no trib.al/Qy5aOnw
@geogristle @FrnkNlsn I came across it when looking for Sturmfels' writing on the Grassmannian-Cayley algebra, and learned a bit about mixture models and phylogenetic statistics.
@FrnkNlsn I had forgotten about that Sturmfels book. Thanks
That’s a wrap on the #NAS161 Research Briefings! Thank you to everyone who joined us in person & online to learn about the pioneering research our new #NASmembers are working on. Join us again tomorrow for the 2024 NAS Awards Ceremony as we honor more contributions to science!
Evaluating MCMC samplers statmodeling.stat.columbia.edu/2024/04/27/eva…
Merci!
Achat du jour. Superbe ouvrage de @FrnkNlsn , dont je comprends pas qu'il ne soit pas plus connu.
Calabi-Yau manifolds, 6D shapes that are crucial to string theory, were named after the late Eugenio Calabi (right), who proposed the shapes in the 1950s, and Shing-Tung Yau, who in the 1970s set out to prove Calabi wrong but ended up doing the opposite. quantamagazine.org/ai-starts-to-s…
Achat du jour. Superbe ouvrage de @FrnkNlsn , dont je comprends pas qu'il ne soit pas plus connu.
To make sense of four-dimensional spaces, mathematicians study surfaces embedded within them. A recent paper shows that these surfaces can be a lot more complicated than they seem. quantamagazine.org/mathematicians…
📢Our April issue is now live, and it includes a Comment on taking inspiration from epidemic modeling to improve wildfire resilience, and a Resource for high-resolution simulation of large biological tissues, among other exciting manuscripts! Check it out! nature.com/natcomputsci/v…
Great book! Biography of Henri Poincar\'e, mathematician and theoretical physicist, who was nominated for Nobel prize. Famous works cover non-Euclidean geometry chaos (3-body problem ), algebraic topology (fundamental group+homology), special relativity (Lorentz group) 1/2
Mathematics, physics: the endless landscape. "Taxonomy of Principal Distances and Divergences" — ranging from Euclidean Geometry (upper left) to Quantum and Matrix Geometry (lower right). By Frank Nielsen, @FrnkNlsn, franknielsen.github.io/Divergence/ind…, Used with permission.
@gdb @nvidia So appreciative of Jensen’s contribution to #AI! This was when he delivered the world’s first @nvidia DGX-1 to our lab @StanfordSVL back in 2016! 😍
@nvidia CEO JensenHuang delivered the world's 1st AI supercomputer DGX-1 today to SAIL! @jcniebles @silviocinguetta
In our latest Editorial, we highlight - from the perspective of our editor @JPanPanJ - the vibrant discussions on quantum computing and quantum algorithms that took place at the 2024 @APSphysics March Meeting. nature.com/articles/s4358…
InfoNCE is variational inference in a recognition parameterised model Laurence Aitchison, Stoil Krasimirov Ganev. Action editor: Jinwoo Shin. openreview.net/forum?id=chbRs… #supervised #prior #likelihood
For some reason, doing what the calendar tells me, "showing up for my booking" works for me. I see @pnbeymer booked me for two hours to look at our R&R, I just do it. It outsources the prioritization and takes the pressure off of me to get back to them by a certain time. 8/
Double Descent and Overfitting under Noisy Inputs and Distribution Shift for Linear Denoisers Chinmaya Kausik, Kashvi Srivastava, Rishi Sonthalia. Action editor: Pierre Alquier. openreview.net/forum?id=HxfqT… #denoising #supervised #empirical